Diff for "Tutorials/Scripting"

diff-info-rev-size">Size: 71205 diff-info-rev-author">Editor: FrancoisTadel diff-info-rev-comment">Comment: are marked like this. are marked like this. Tutorial 27: Advanced scripting =
'''[TUTORIAL UNDER DEVELOPMENT: NOT READY FOR PUBLIC USE] '''

''Authors: Francois Tadel, Elizabeth Bock, Sylvain Baillet''

This tutorial explains how to use the Brainstorm scripting interface to run a full analysis, from the raw recordings to the source reconstruction. It is based on a median nerve stimulation experiment recorded at the Montreal Neurological Institute in 2011 with a CTF MEG 275 system. The sample dataset contains 6 minutes of recordings at 1200Hz for one subject and includes 100 stimulations of each arm.

The tutorial follows the analysis steps detailed in the three advanced tutorials in the category [[http://neuroimage.usc.edu/brainstorm/Tutorials|Processing continuous recordings]]. You should read them before reading this tutorial, to have the explanations that go with the analysis steps. Tutorial 28: Scripting =
''Authors: Francois Tadel, Elizabeth Bock'''''', Matthias Sure'', Sylvain Baillet''

The previous tutorials explained how to use Brainstorm in an interactive way to process one subject with two acquisition runs. In the context of a typical neuroimaging study, you may have tens or hundreds of subjects to process in the same way, it is unrealistic to do everything manually. Some parts of the analysis can be processed in batches with no direct supervision, others require more attention. This tutorial introduces tools and tricks that will help you assemble an efficient analysis pipeline.

Requirements: You need a license for the Matlab environment in order to use these tools and execute custom scripts. If you are running the compiled version of Brainstorm with the MCR library, the only custom code you can run is through the menu "File > Matlab console" and the process "Run Matlab command". 12: 10: Creating the analysis pipeline ==
Select the menu File > Create new protocol. Name it "'''TutorialScript'''" and select the options:

* "'''No, use individual anatomy'''",
* "'''Yes, use one channel file per subject'''".

To start building your analysis pipeline, just click on the "'''Run'''" button in the Process1 tab. We don't need any file in input, as we are going to select the files to import in the script itself. Then add all the processes listed below. The output of each process is the input of the following one, this is why the order of the processes is important.

=== Import anatomy > Import anatomy folder ===
* Folder to import: sample_raw/Anatomy
File format: "FreeSurfer folder"
* Fiducials: Copy what is indicated below. This is a reason it is usually easier to do this step in interactive mode, and then run only the script starting from the next step.
* Input: None; Output: None

{{http://neuroimage.usc.edu/brainstorm/Tutorials/TutRawScript?action=AttachFile&do=get&target=process_import_freesurfer.gif|process_import_freesurfer.gif|class="attachment"}}

=== Import recordings > Create link to raw file ===
* File to import: Select the folder sample_raw/Data/subj001_somatosensory_20111109_01_AUX-f.ds
* Input: None; Output: Raw file

{{http://neuroimage.usc.edu/brainstorm/Tutorials/TutRawScript?action=AttachFile&do=get&target=process_import_data_raw.gif|process_import_data_raw.gif|class="attachment"}}

=== Pre-process > Notch filter ===
Input: Raw file ; Output: Raw file (new)

{{http://neuroimage.usc.edu/brainstorm/Tutorials/TutRawScript?action=AttachFile&do=get&target=process_sin_remove.gif|process_sin_remove.gif|class="attachment"}}

=== Events > Detect eye blinks ===
Input: Raw file ; Output: Raw file

{{http://neuroimage.usc.edu/brainstorm/Tutorials/TutRawScript?action=AttachFile&do=get&target=process_evt_detect_eog.gif|process_evt_detect_eog.gif|class="attachment"}}

=== Events > Compute SSP: eye blinks ===
Input: Raw file ; Output: Raw file

{{http://neuroimage.usc.edu/brainstorm/Tutorials/TutRawScript?action=AttachFile&do=get&target=process_ssp_eog.gif|process_ssp_eog.gif|class="attachment"}}

=== Import recordings > Import MEG/EEG : Events ===
Input: Raw file ; Output: 199 epochs in 2 conditions

{{http://neuroimage.usc.edu/brainstorm/Tutorials/TutRawScript?action=AttachFile&do=get&target=process_import_data_event.gif|process_import_data_event.gif|class="attachment"}}

=== Pre-process > Remove DC offset ===
Input: 199 epochs ; Output: 199 epochs

{{http://neuroimage.usc.edu/brainstorm/Tutorials/TutRawScript?action=AttachFile&do=get&target=process_baseline.gif|process_baseline.gif|class="attachment"}}

=== Pre-process > Add time offset ===
Input: 199 epochs ; Output: 199 epochs

{{http://neuroimage.usc.edu/brainstorm/Tutorials/TutRawScript?action=AttachFile&do=get&target=process_timeoffset.gif|process_timeoffset.gif|class="attachment"}}

=== Sources > Compute noise covariance ===
Since the epochs are currently selected and pre-processed: we can use them to estimate the noise covariance matrix before we move on with the calculation of the average.

Input: 199 epochs ; Output: 199 epochs

{{http://neuroimage.usc.edu/brainstorm/Tutorials/TutRawScript?action=AttachFile&do=get&target=process_noisecov.gif|process_noisecov.gif|class="attachment"}}

=== Average > Average files ===
Input: 199 epochs ; Output: 2 averages

{{http://neuroimage.usc.edu/brainstorm/Tutorials/TutRawScript?action=AttachFile&do=get&target=process_average.gif|process_average.gif|class="attachment"}}

=== File > Save snapshot: Sensors/MRI registration ===
Input: 2 averages ; Output: 2 averages

{{http://neuroimage.usc.edu/brainstorm/Tutorials/TutRawScript?action=AttachFile&do=get&target=process_snapshot.gif|process_snapshot.gif|class="attachment"}}

=== File > Save snapshot: Recordings time series ===
Input: 2 averages ; Output: 2 averages

{{http://neuroimage.usc.edu/brainstorm/Tutorials/TutRawScript?action=AttachFile&do=get&target=process_snapshot2.gif|process_snapshot2.gif|class="attachment"}}

=== Sources > Compute head model ===
Input: 2 averages ; Output: 2 averages

{{http://neuroimage.usc.edu/brainstorm/Tutorials/TutRawScript?action=AttachFile&do=get&target=process_headmodel.gif|process_headmodel.gif|class="attachment"}}

=== Sources > Compute sources ===
Input: 2 averages ; Output: all the source files (1 raw + 2 average + 199 epochs = 202 files)

{{http://neuroimage.usc.edu/brainstorm/Tutorials/TutRawScript?action=AttachFile&do=get&target=process_inverse.gif|process_inverse.gif|class="attachment"}}

== Save the pipeline ==
=== Save in current workspace ===
Use the menus on top of the pipeline editor to save this list of processes on your computer. The menu "Save > New..." will create an entry readily available in your Brainstorm installation in the Load section of the same menu.

{{http://neuroimage.usc.edu/brainstorm/Tutorials/TutRawScript?action=AttachFile&do=get&target=savePipeline.gif|savePipeline.gif|class="attachment"}}

=== Export as script ===
Use the menu "Generate .m script" to create a Matlab script that would have the exact same result as running this analysis pipeline from the Brainstorm interface.

This script is also available in the Brainstorm distribution: '''brainstorm3/toolbox/script/tutorial_raw.m '''

{{{
% Script generated by Brainstorm v3.2 (22-Jul-2014)
Starting a new script ==
The easiest way to get started with a new Brainstorm script is to use the script generator, already introduced in the tutorial [[http://neuroimage.usc.edu/brainstorm/Tutorials/PipelineEditor#Saving_a_pipeline|Select files and run processes]]. Select some files in the Process1 or Process2 tabs, select a list of processes, and use the menu '''Generate .m script'''. The example below should work with the protocol "TutorialIntroduction" created during the introduction tutorials.

* In the Process1 tab, leave the selection box empty and click on [Run]. Instead of selecting the files from the Brainstorm interface, we will select them directly from the database using a script.
* Select process '''File > Select files: Recordings''' (do not execute immediately)<<BR>>Subject='''Subject01''', Condition='''[Empty]''', File comment='''Avg: deviant''' (the space is important). <<BR>><<BR>> {{attachment:start1.gif||width="400",height="334"}}
* This process selects all the recordings with a comment including the string "Avg: deviant", from all the folders in Subject01 (except for "Intra-subject" and "Common files"). We expect to get two files: the averages of the deviant condition for both runs.
* Add process '''Pre-process > Band-pass filter''': Lower cutoff='''0Hz''', Upper cutoff='''30Hz''', 60dB. <<BR>> '''Add process File > Save snapshot''': Recordings time series, Sensors=MEG. <<BR>> <<BR>> {{attachment:start2.gif||width="536",height="353"}}
* This will apply a low-pass filter at 30Hz and save a screen capture of the signals in the report.
* Do not run the pipeline, select the menu '''Generate .m script '''instead. It saves a new .m file and opens it in the Matlab editor. Close the pipeline editor window and look at the script.<<BR>><<BR>> {{attachment:start3.gif||width="673",height="272"}}
* The script you just generated can be the starting point to your own custom script. The following sections explain line by line how they work and how to edit them.

== Line by line: Header ==
{{{
% Script generated by Brainstorm (19-Jul-2016)
}}}
All the lines starting with a "%" are comments, they are never executed.

{{{ 114: 32: = {...
    'C:\Work\RawData\Tutorials\sample_raw\Anatomy', ...
    'C:\Work\RawData\Tutorials\sample_raw\Data\subj001_somatosensory_20111109_01_AUX-f.ds'};
lines define the script inputs:

* '''sFiles''': The list of files in input. Currently empty because we did not select anything in the Process1 list. If we had selected files, it would contain a cell array of strings with relative file paths.
* '''SubjectNames''': List of subject names that are used in the script. Most of the times, the generated scripts contain only one entry, but it is written as a cell array to make it easier to extend to multiple subjects with a loop (described further in this tutorial).

{{{ 120: 41: Process: Import anatomy folder
sFiles = bst_process('CallProcess', 'process_import_anatomy', ...
    sFiles, [], ...
    'subjectname', SubjectNames{1}, ...
    'mrifile', {RawFiles{1}, 'FreeSurfer'}, ...
    'nvertices', 15000, ...
    'nas', [127, 212, 123], ...
    'lpa', [55, 124, 119], ...
    'rpa', [200, 129, 114], ...
    'ac', [129, 137, 157], ...
    'pc', [129, 113, 157], ...
    'ih', [129, 118, 209]);

% Process: Create link to raw file
sFiles = bst_process('CallProcess', 'process_import_data_raw', ...
    sFiles, [], ...
    'subjectname', SubjectNames{1}, ...
    'datafile', {RawFiles{2}, 'CTF'}, ...
    'channelreplace', 1, ...
    'channelalign', 1);

% Process: Notch filter: 60Hz 120Hz 180Hz
sFiles = bst_process('CallProcess', 'process_notch', ...
    sFiles, [], ...
    'freqlist', [60, 120, 180], ...
    'sensortypes', 'MEG, EEG', ...
    'read_all', 0);

% Process: Detect eye blinks
sFiles = bst_process('CallProcess', 'process_evt_detect_eog', ...
    sFiles, [], ...
    'channelname', 'EEG058', ...
    'timewindow', [], ...
    'eventname', 'blink');

% Process: Detect heartbeats
sFiles = bst_process('CallProcess', 'process_evt_detect_ecg', ...
    sFiles, [], ...
    'channelname', 'EEG057', ...
    'timewindow', [], ...
    'eventname', 'cardiac');

% Process: SSP EOG: blink
sFiles = bst_process('CallProcess', 'process_ssp_eog', ...
    sFiles, [], ...
    'eventname', 'blink', ...
    'sensortypes', 'MEG, EEG', ...
    'usessp', 0);

% Process: Import MEG/EEG: Events
sFiles = bst_process('CallProcess', 'process_import_data_event', ...
    sFiles, [], ...
    'subjectname', SubjectNames{1}, ...
    'condition', '', ...
    'eventname', 'left, right', ...
    'timewindow', [], ...
    'epochtime', [-0.1, 0.3], ...
    'createcond', 1, ...
    'ignoreshort', 1, ...
    'usectfcomp', 1, ...
    'usessp', 1, ...
    'freq', [], ...
    'baseline', [-0.1, -0.0008333333333]);

% Process: Add time offset: -4.20ms
sFiles = bst_process('CallProcess', 'process_timeoffset', ...
    sFiles, [], ...
    'offset', -0.0042, ...
    'overwrite', 1);

% Process: Compute noise covariance
sFiles = bst_process('CallProcess', 'process_noisecov', ...
    sFiles, [], ...
    'baseline', [-0.1042, 0], ...
    'dcoffset', 1, ...
    'method', 1, ... % Full noise covariance matrix
    'copycond', 0, ...
    'copysubj', 0);

% Process: Average: By condition (subject average)
sFiles = bst_process('CallProcess', 'process_average', ...
    sFiles, [], ...
    'avgtype', 3, ...
    'avg_func', 1, ... % Arithmetic average: mean(x)
    'keepevents', 0);

% Process: Snapshot: Sensors/MRI registration
sFiles = bst_process('CallProcess', 'process_snapshot', ...
    sFiles, [], ...
    'target', 1, ... % Sensors/MRI registration
    'modality', 1, ... % MEG (All)
    'orient', 1, ... % left
    'time', 0, ...
    'contact_time', [0, 0.1], ... a new report of activity: Clears all the previous logs and gets ready to record new messages. The report will collect all the messages that are generated during the execution of the script by the various processes. You can explicitly add screen captures and additional messages to the current report with the function bst_report. This report will remain open until the function bst_report('Start') is called again. To display the current report, use the menu [[http://neuroimage.usc.edu/brainstorm/Tutorials/PipelineEditor#Report_viewer|File > Report viewer]].

The syntax '''function_name'''(''''SubFunction'''', arguments) is used a lot in Brainstorm: it calls a subfunction available inside a .m file. This line above calls the function Start() in the file brainstorm3/toolbox/process/bst_report.m. This is made possible with the use of the short script "macro_method". Many of the Brainstorm .m files are actually libraries of functions, rather than simple "scripts" or "functions".

== Line by line: Body ==
{{{
% Process: Select data files in: Subject01/*/Avg: deviant
sFiles = bst_process('CallProcess', 'process_select_files_data', sFiles, [], ...
    'subjectname', SubjectNames{1}, ...
    'condition', '', ...
    'tag', 'Avg: deviant', ...
    'includebad', 0, ...
    'includeintra', 0, ...
    'includecommon', 0);

% Process: Low-pass:30Hz
sFiles = bst_process('CallProcess', 'process_bandpass', sFiles, [], ...
    'sensortypes', 'MEG', ...
    'highpass', 0, ...
    'lowpass', 30, ...
    'attenuation', 'strict', ... % 60dB
    'mirror', 0, ...
    'useold', 0, ...
    'overwrite', 0);

% Process: Snapshot: Recordings time series
sFiles = bst_process('CallProcess', 'process_snapshot', sFiles, [], ...
    'target', 5, ... % Recordings time series
    'modality', 1, ... % MEG (All)
    'orient', 4, ... % bottom
    'time', 0.11, ...
    'contact_time', [0, 0.1], ... 216: 75:     'comment', 'MEG/MRI Registration');

% Process: Snapshot: Recordings time series
sFiles = bst_process('CallProcess', 'process_snapshot', ...
    sFiles, [], ...
    'target', 5, ... % Recordings time series
    'modality', 1, ... % MEG (All)
    'orient', 1, ... % left
    'time', 0, ...
    'contact_time', [0, 0.1], ...
    'contact_nimage', 12, ...
    'comment', 'Evoked response');

% Process: Compute head model
sFiles = bst_process('CallProcess', 'process_headmodel', ...
    sFiles, [], ...
    'comment', '', ...
    'sourcespace', 1, ...
    'meg', 3, ... % Overlapping spheres
    'eeg', 3, ... % OpenMEEG BEM
    'ecog', 2, ... % OpenMEEG BEM
    'seeg', 2, ...
    'openmeeg', struct(...
         'BemFiles', {{}}, ...
         'BemNames', {{'Scalp', 'Skull', 'Brain'}}, ...
         'BemCond', [1, 0.0125, 1], ...
         'BemSelect', [1, 1, 1], ...
         'isAdjoint', 0, ...
         'isAdaptative', 1, ...
         'isSplit', 0, ...
         'SplitLength', 4000));

% Process: Compute sources
sFiles = bst_process('CallProcess', 'process_inverse', ...
    sFiles, [], ...
    'comment', '', ...
    'method', 1, ... % Minimum norm estimates (wMNE)
    'wmne', struct(...
         'NoiseCov', [], ...
         'InverseMethod', 'wmne', ...
         'ChannelTypes', {{}}, ...
         'SNR', 3, ...
         'diagnoise', 0, ...
         'SourceOrient', {{'fixed'}}, ...
         'loose', 0.2, ...
         'depth', 1, ...
         'weightexp', 0.5, ...
         'weightlimit', 10, ...
         'regnoise', 1, ...
         'magreg', 0.1, ...
         'gradreg', 0.1, ...
         'eegreg', 0.1, ...
         'ecogreg', 0.1, ...
         'seegreg', 0.1, ...
         'fMRI', [], ...
         'fMRIthresh', [], ...
         'fMRIoff', 0.1, ...
         'pca', 1), ...
    'sensortypes', 'MEG, MEG MAG, MEG GRAD, EEG', ...
    'output', 1); % Kernel only: shared
bsp;   'threshold', 20, ...
    'Comment', 'Run');
}}}
You will find one block per process you selected in the pipeline editor. They all have the same syntax: <<BR>> output_files = '''bst_process'''('CallProcess', process_name, input_files_A, input_files_B, options_list);

* '''process_name''': String indicating the function corresponding to the process to execute. To know from the pipeline editor what is the path to the process function: hover your mouse over the selected process, as illustrated in [[http://neuroimage.usc.edu/brainstorm/Tutorials/PipelineEditor#Plugin_structure|this tutorial]].
* '''input_files_A''': List of input files in Process1, or FilesA in Process2. It can be a cell array of file names (full path, or relative path from the protocol folder), or an array of structures describing the files in the database (returned by a previous call to bst_process).
* '''input_files_B''': Empty for Process1, or FilesB in Process2. Cell array of strings, or array of struct.
* '''options_list''': Pairs of (option_name, option_values), one pair for each option of the process.
* '''output_files''': Array of structures describing the files in output of the process. If the process created new files, this variable points at them. If the process didn't create new files or was modifying exiting files, this variable points at the input files.

== Line by line: Footer ==
{{{ 279: 90: the current report and saves it in the user report folder ($HOME/.brainstorm/reports). These reports are in .mat format and contain all the information necessary to re-run the execution exactly in the same way, but they are not easy to read.

The parameter "sFiles" is optional, it indicates what are the files that are considered as the final results of the script. You can remove it without breaking your script: ReportFile = bst_report('Save');

{{{ 281: 98: Report viewer ==
Click on Run to start the script.

As this process is taking screen captures, do not use your computer for something else at the same time: if another window covers the Brainstorm figures, it will not capture the right images.

At the end, the report viewer is opened to show the status of all the processes, the information messages, the list of input and output files, and the screen captures. The report is saved in your home folder ($home/.brainstorm/reports). If you close this window, you can get it back with the menu File > Report viewer.

{{http://neuroimage.usc.edu/brainstorm/Tutorials/TutRawScript?action=AttachFile&do=get&target=report1.gif|report1.gif|class="attachment"}}

{{http://neuroimage.usc.edu/brainstorm/Tutorials/TutRawScript?action=AttachFile&do=get&target=report2.gif|report2.gif|class="attachment"}}

<<EmbedContent("http://neuroimage.usc.edu/bst/get_prevnext.php?prev=Tutorials/Connectivity")>> the report viewer to display what happened during the execution. This is equivalent to using the menu [[http://neuroimage.usc.edu/brainstorm/Tutorials/PipelineEditor#Report_viewer|File > Report viewer]]. You can comment this line (ie. add a "%" at the beginning of the line) if you don't want to show the report at the end of the execution.

{{{
% bst_report('Export', ReportFile, ExportDir);
}}}
This function exports the report in readable format, as an HTML file that includes all the screen captures embedded in it. It is disabled by default. If you want to use this feature: remove the "%" at the beginning of the line, and define the variable ExportDir.

ExportDir must be a string that defines where to save the HTML report. It can be either the absolute path to a HTML file (eg. 'C:\Users\myuser\Documents\report_example.html') or just a folder (eg. 'C:\Users\myuser\Documents'). If you enter only a path to a folder, a default file name including the protocol name and a date tag is generated (report_ProtocolName_YYMMDD_HHMMSS.html).

== Simplify the calls ==
The script you generated is like any Matlab script: you can edit it, rename the variables, add tests and loops, etc. The first important thing to understand is how to edit the options and change the inputs/outputs. The script generator uses only one variable for all the file lists ('''sFiles''') and the output process is always the input of the following process. This is usually too restrictive to write a full analysis script: we commonly need to have multiple lists of files or to run two different operations on the same file.

Let's consider the first process call, which selects the averages for the Deviant condition in both runs.

{{{
sFiles = bst_process('CallProcess', 'process_select_files_data', sFiles, [], ...
    'subjectname', SubjectNames{1}, ...
    'condition', '', ...
    'tag', 'Avg: deviant', ...
    'includebad', 0, ...
    'includeintra', 0, ...
    'includecommon', 0);
}}}
There is no need to set the parameter sFiles, because there is no input, you can replace it with an empty matrix []. You can therefore remove the line "sFiles = [];". We can also rename the output variable "sAvgData", to be more specific.

{{{
sAvgData = bst_process('CallProcess', 'process_select_files_data', [], [], ...
}}}
You can omit all the options that are not defined, not used, or kept to their default values:

{{{
sAvgData = bst_process('CallProcess', 'process_select_files_data', [], [], ...
    'subjectname', SubjectNames{1}, ...
    'tag', 'Avg: deviant');
}}}
Edit the call to the low-pass filter: Change the input to sAvgData and the output to sAvgDataLow, this way you will be able to keep track of the two files if you need to use them independently later.

{{{
sAvgDataLow = bst_process('CallProcess', 'process_bandpass', sAvgData, [], ...
    'sensortypes', 'MEG', ...
    'highpass', 0, ...
    'lowpass', 30, ...
    'attenuation', 'strict'); % 60dB
}}}
Edit the call to the snapshot process: Change the input to sAvgDataLow, and remove the output parameter (we are not expecting any output file from it).

{{{
bst_process('CallProcess', 'process_snapshot', sAvgDataLow, [], ...
    'target', 5, ... % Recordings time series
    'modality', 1); % MEG (All)
}}}
Replace the last lines with the following code, in order to export the report instead of opening in the report viewer (edit the file path to point at your own user folder instead).

{{{
ReportFile = bst_report('Save');
bst_report('Export', ReportFile, 'C:\Users\myuser\Documents\report_test.html');
}}}
== Evaluate in Matlab ==
Select the code for the first process in the Matlab editor, right-click > Evaluate selection (or press F9).

{{attachment:edit1.gif}}

If you haven't executed your script yet, you will get the following error in the Matlab command window:

{{{
Undefined variable "SubjectNames" or class "SubjectNames".
}}}
The variable SubjectNames is not defined yet: Execute the first lines "SubjectNames = {'Subject01'}", then try again. You should now have a new variable in your Matlab workspace, which points at the two average files. Type "sAvgData(1)" in your command window to display the first element:

{{{
>> sAvgData(1)
ans =
          iStudy: 6
           iItem: 1
        FileName: '..._01_600Hz_notch/data_deviant_average_160513_1329.mat'
        FileType: 'data'
         Comment: 'Avg: deviant (39 files)'
       Condition: 'S01_AEF_20131218_01_600Hz_notch'
     SubjectFile: 'Subject01/brainstormsubject.mat'
     SubjectName: 'Subject01'
        DataFile: ''
     ChannelFile: 'Subject01/S01_AEF_20131218_01_600Hz_notch/channel_ctf_acc1.mat'
    ChannelTypes: {'ADC A' 'ADC V' 'DAC' 'ECG' 'EOG' 'MEG' 'MEG REF' ...}
}}}
The field "sAvgData(1).FileName" contains the relative path to the to the Deviant average in the first run. This structure sAvgData contains also a lot of information that can be helpful in your script:

* '''iStudy / iItem''': Reference of the file in the database (described later in this tutorial).
* '''FileType''': 'raw' (continuous files), 'data' (recordings), 'results' (sources), 'timefreq' (time-frequency, spectrum and connectivity), or 'matrix' (any time series extracted from other files).
* '''Comment''': Comment field of the file (what is displayed in the database explorer).
* '''Condition''': Name of the condition/folder in which the file is located.
* '''SubjectFile''': Relative path to the subject file (brainstormsubject.mat).
* '''SubjectName''': Name of the subject (must be the same as the folder name).
* '''DataFile''': For types 'results' or 'timefreq', path of the parent file in the database explorer.
* '''ChannelFile''': Relative path to the channel file.
* '''ChannelTypes''': Cell array of channel types available for the input file.

== Naming conventions ==
To help you navigate in the Brainstorm code, here are some naming conventions:

* '''Structures''': Name starting with a "s" followed by a capital letter (eg. sFiles, sStudy, sSubject).
* '''Indices''': Either loop variables or array indices, name starting with a "i" (eg. iSubject, iStudy, iTime).
* '''Counts''': Number of elements in a group, name starting with a "n" (eg. nAvg, nTrials, nSubjects).
* '''Graphic handles''': Matlab graphic objects, name starting with a "h" (eg. hFig, hAxes, hLine, hText).
* '''File names''': Scripts and functions, only lower case, separation with "_" (eg. process_fft, bst_get).
* '''Sub-functions''': Inside a .m file, name starting with a capital, CamelCase (eg. CallProcess, Start).

== Running the script ==
The simplified script looks like this:

{{{
% Input files
SubjectNames = {'Subject01'};
% Start a new report
bst_report('Start');

% Process: Select data files in: Subject01/*/Avg: deviant
sAvgData = bst_process('CallProcess', 'process_select_files_data', [], [], ...
    'subjectname', SubjectNames{1}, ...
    'tag', 'Avg: deviant');
% Process: Low-pass:30Hz
sAvgDataLow = bst_process('CallProcess', 'process_bandpass', sAvgData, [], ...
    'sensortypes', 'MEG', ...
    'highpass', 0, ...
    'lowpass', 30, ...
    'attenuation', 'strict'); % 60dB
% Process: Snapshot: Recordings time series
bst_process('CallProcess', 'process_snapshot', sAvgDataLow, [], ...
    'target', 5, ... % Recordings time series
    'modality', 1); % MEG (All)

% Save and display report
ReportFile = bst_report('Save');
bst_report('Export', ReportFile, 'C:\Users\franc\Documents\report_test.html');
}}}
You have three ways to execute it:

* Select all the lines (Ctrl+A) and evaluate it in Matlab (F9).
* In the Editor toolbar of the Matlab environment, click on the button [Run].
* Save the file, go to this folder with Matlab (or add it to your path) and type the name of the script in the command window (without the ".m" at the end).

At the end of the execution, nothing happens, because we indicated we wanted to export the report instead of opening it. To check out the report of execution: use the menu '''File > Report viewer''' from the Brainstorm window, or open the file '''report_test.html''' that was saved somewhere on your computer.

In this page, you can review everything that happened in the script: when it was executed, how long it took, what are the processes that were executed, some additional messages (two files were selected with the first process) and the screen captures taken by process_snapshot.

. {{attachment:report1.gif||width="593",height="455"}}

== Running the script again ==
If you execute the script again, it will not behave as expected anymore. The selection process we used assumes that there is only one file per folder with a comment that includes "Avg: deviant". This is not the case anymore after the execution, because the low-pass filtered files also contain the same string. The execution of the first process of the script now '''returns 4 files'''.

{{{
>> sAvgData = bst_process('CallProcess', 'process_select_files_data', [], [], ...
    'subjectname', SubjectNames{1}, ...
    'tag', 'Avg: deviant')

sAvgData =
1x4 struct array with fields:
    iStudy
    iItem
    ...
}}}
In order to exclude the low-pass filtered files from this selection, you can add another process that will '''refine the selection'''. Use the script generator again to create a template call for another process, then copy-paste it in your script.

* In Process1: Select any recordings file (we will not run anything, just generate a script).
* Select process '''File > Select files: By tag''': Search="low", Search the comment, '''Ignore '''the files. <<BR>><<BR>> {{attachment:select_tag.gif||width="261",height="252"}}
* Select the menu '''Generate .m script''' (make sure you do not overwrite the script you are currently working on), then close the pipeline editor.
* Copy-paste and edit the call to process_select_tag to your main script.

Now the file selection part of your script should look like this, and should return only two files:

{{{
% Process: Select data files in: Subject01/*/Avg: Deviant
sAvgData = bst_process('CallProcess', 'process_select_files_data', [], [], ...
    'subjectname', SubjectNames{1}, ...
    'tag', 'Avg: deviant');
% Process: Ignore file comments with tag: low
sAvgData = bst_process('CallProcess', 'process_select_tag', sAvgData, [], ...
    'tag', 'low', ...
    'search', 2, ... % Search the file comments
    'select', 2); % Ignore the files with the tag
}}}
With this last modification, your script is more robust. It can be executed multiple times without completely changing its behavior. When you are fetching files from the database using comment tags or file names, always pay attention to this aspect: the database grows and the further you go, the more specific your requests have to be.

A good practice can be to tag explicitly the output files your script generates if you need to fetch them later. You can use the process '''File > Add tag''' and '''File > Set comment'''.

. {{attachment:add_tag.gif||width="456",height="203"}}

== Starting Brainstorm ==
Brainstorm must be running in the background for these scripts to run properly. The interface doesn't have to be visible on the screen, but the database engine must be running for processing requests. At the beginning of your script, you can explicitly start or restart Brainstorm.

* '''brainstorm''': Start Brainstorm with the regular GUI.
* '''brainstorm nogui''': Start in silent mode. The Java GUI is created but hidden, the progress bar is not shown, all the processes run without user interactions, using default options instead of asking interactively. Visualization figures opened in the processing scripts are still created and made visible.
* '''brainstorm server''': Start in headless mode, for execution on a distant computation server that does not have any graphical capability or display attached to it. In this mode, none of the Java GUI elements are created, and the Matlab figures are not displayed. Whether you would be able to add screen captures to your execution reports depends mostly on the Matlab version available of your server (see section below [[https://neuroimage.usc.edu/brainstorm/Tutorials/Scripting#Running_scripts_on_a_cluster|Running scripts on a cluster]]).
* '''brainstorm <script.m> <parameters>''': Start Brainstorm in server mode, execute a script and quit Brainstorm. This allows executing any Matlab or Brainstorm script from the command line. This works also from the compiled version of Brainstorm, add the full path to the script to execute and the script parameters to the start script:<<BR>> '''brainstorm3.bat <script.m>''' or '''brainstorm3.command <script.m>'''.

If you want to start Brainstorm only if it is not already running, you can use the following code:

{{{
if ~brainstorm('status')
    brainstorm nogui
end
}}}
To select a specific protocol at the beginning of your script:

{{{
ProtocolName = 'TutorialIntroduction';
% Get the protocol index
iProtocol = bst_get('Protocol', ProtocolName);
if isempty(iProtocol)
    error(['Unknown protocol: ' ProtocolName]);
end
% Select the current procotol
gui_brainstorm('SetCurrentProtocol', iProtocol);
}}}
To delete the protocol and start over:

{{{
% Delete existing protocol
gui_brainstorm('DeleteProtocol', ProtocolName);
% Create new protocol
gui_brainstorm('CreateProtocol', ProtocolName, 0, 0);
}}}
Additional command line options:

{{{
brainstorm stop % Quit Brainstorm
brainstorm update % Download and install latest Brainstorm update (see bst_update)
brainstorm reset % Re-initialize Brainstorm database and preferences
brainstorm digitize % Digitize electrodes positions and head shape using a Polhemus
brainstorm setpath % Add Brainstorm subdirectories to current path
brainstorm info % Open Brainstorm website
brainstorm forum % Open Brainstorm forum
brainstorm license % Display license
}}}
== Database requests ==
The functions '''bst_get''' and '''bst_set''' allow you to query the database, access the configuration of the software and modify some display parameters. The complete reference documentation of these functions is included directly in their code (brainstorm3/toolbox/core/bst_get.m and bst_set.m).

Let's start with a few simple examples:

{{{
>> ProtocolInfo = bst_get('ProtocolInfo') % Configuration of the current protocol
ProtocolInfo =
              Comment: 'TutorialIntroduction'
              STUDIES: 'C:\Work\Protocols\TutorialIntroduction\data'
             SUBJECTS: 'C:\Work\Protocols\TutorialIntroduction\anat'
               iStudy: 6
       UseDefaultAnat: 0
    UseDefaultChannel: 0

>> isGUI = bst_get('isGUI') % Is the Brainstorm interface displayed (0=no, 1=yes)

>> bst_set('FlipYAxis', 1) % New figures will have the Y axis flipped
>> bst_set('TSDisplayMode', 'butterfly') % New figures will use a "butterfly" view
>> bst_set('FieldTripDir', FieldTripDir) % Set path to the FieldTrip toolbox
}}}
To reference the files in the database, each protocol is subdivided in '''Subjects''' (the "anat" folder, containing the MRI, surfaces and atlases) and '''Studies''' (the "data" folder, including the recordings, channel files and all the analyses). Each Study corresponds to a sub-folder (eg. protocol/data/subject01/run01/), and is attached to only one subject.

Subjects and Studies are referenced in the protocol with a unique index, most of the time kept in variables named '''iSubject''' and '''iStudy'''. The files available in them are also referenced with indices, with variables such as iAnatomy, iSurface, iData, iHeadModel, iResults or iTimefreq. You can see the indices in the database explorer by hovering your mouse over the nodes files and folders:

{{attachment:db_indices.gif||width="715",height="64"}}

Example: Getting the '''study structure''' from the variable sAvgData, defined in the script:

{{{
>> sAvgData(1)
ans =
          iStudy: 6
           iItem: 1
           ...

>> sStudy = bst_get('Study', sAvgData(1).iStudy) % Get study struct with its index
sStudy =
                 Name: 'S01_AEF_20131218_01_600Hz_notch'
             FileName: 'Subject01/S01_AEF_20131218_01_600Hz_notch/brainstormstudy.mat'
          DateOfStudy: '13-May-2016'
    BrainStormSubject: 'Subject01/brainstormsubject.mat' % Subject filename
            Condition: {'S01_AEF_20131218_01_600Hz_notch'} % Name of the folder
              Channel: [1x1 struct] % Channel file
             iChannel: [] % Not used anymore
                 Data: [1x242 struct] % List of "data" files in the folder
            HeadModel: [1x1 struct] % List of head models in the folder
           iHeadModel: 1 % Default head model (file in green)
               Result: [1x244 struct] % List of source files and links
                 Stat: [1x0 struct] % List of statistical results
                Image: [0x0 struct] % List of images
             NoiseCov: [1x2 struct] % Noise(1) and data(2) covariance files
              Dipoles: [0x0 struct] % List of dipole files in the folder
             Timefreq: [1x247 struct] % List of time-frequency files
               Matrix: [0x0 struct] % List of "matrix" files in the folder
}}}
Example: Getting the '''data structure'''.

{{{
% Get the structure representing the file from sStudy
>> sData = sStudy.Data(sAvgData(1).iItem)
sData =
    FileName: '..._01_600Hz_notch/data_deviant_average_160513_1329.mat'
     Comment: 'Avg: deviant (39 files)' % File comment
    DataType: 'recordings' % Type of data in the file
    BadTrial: 0 % If 1, the trial is marked as bad
}}}
Example: Getting the '''subject structure'''.

{{{
% Get subject structure from filename (lists the files in the subject folder)
>> sSubject = bst_get('Subject', sStudy.BrainStormSubject)
sSubject =
                 Name: 'Subject01' % Subject name, same as folder name
             Comments: '' % Not used much
             FileName: 'Subject01/brainstormsubject.mat'
    DateOfAcquisition: '' % Not used anymore
              Anatomy: [1x1 struct] % List of MRI volumes
              Surface: [1x9 struct] % List of surfaces
             iAnatomy: 1 % Index of default MRI
               iScalp: 9 % Index of default head surface
              iCortex: 4 % Index of default cortex surface
          iInnerSkull: [] % Index of default inner skull surface
          iOuterSkull: [] % Index of default outer skull surface
               iOther: [] % Not used anymore
       UseDefaultAnat: 0 % If 1: Use the default anatomy
    UseDefaultChannel: 0 % 0=one/folder, 1=one/subject, 2=one global
}}}
Example: Getting the '''study structure''' and '''data index''' from a file name.

{{{
>> DataFile = sAvgData(1).FileName
DataFile =
Subject01/..._01_600Hz_notch/data_deviant_average_160513_1329.mat

>> [sStudy, iStudy, iData] = bst_get('DataFile', DataFile)
sStudy =
                 Name: 'S01_AEF_20131218_01_600Hz_notch'
             FileName: '..._01_600Hz_notch/brainstormstudy.mat'
          DateOfStudy: '13-May-2016'
    BrainStormSubject: 'Subject01/brainstormsubject.mat'
            Condition: {'S01_AEF_20131218_01_600Hz_notch'}
              Channel: [1x1 struct]
             iChannel: []
                 Data: [1x242 struct]
            HeadModel: [1x1 struct]
           iHeadModel: 1
               Result: [1x244 struct]
                 Stat: [1x0 struct]
                Image: [0x0 struct]
             NoiseCov: [1x2 struct]
              Dipoles: [0x0 struct]
             Timefreq: [1x247 struct]
               Matrix: [0x0 struct]
iStudy =
     6
iData =
     1
}}}
Many other options are available for searching files in the database with bst_get. We cannot list them all in this page, but you can refer to the code of '''bst_get.m''' for more information.

<<HTML(<div style="border:1px solid black; background-color:#EEEEFF; width:720px; height:350px; overflow:scroll; padding:10px; font-family: Consolas,Menlo,Monaco,Lucida Console,Liberation Mono,DejaVu Sans Mono,Bitstream Vera Sans Mono,Courier New,monospace,sans-serif; font-size: 13px; white-space: pre;">)>><<EmbedContent("http://neuroimage.usc.edu/bst/viewcode.php?core=bst_get.m")>><<HTML(</div >)>>

<<BR>>To change parameters or database structures: '''bst_set.m'''.

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== File structures ==
The structures of the different types of files were described in the sections "On the hard drive" of the introduction tutorials. Here is a summary of all these sections:

* '''Continuous recordings''': File type "raw", [[http://neuroimage.usc.edu/brainstorm/Tutorials/EventMarkers#On_the_hard_drive|Event markers]].
* '''Imported recordings''': File type "data", [[http://neuroimage.usc.edu/brainstorm/Tutorials/Epoching#On_the_hard_drive|Import epochs]] and [[http://neuroimage.usc.edu/brainstorm/Tutorials/Averaging#On_the_hard_drive|Average response]].
* '''Power spectrum''': File type "timefreq", [[http://neuroimage.usc.edu/brainstorm/Tutorials/ArtifactsFilter#On_the_hard_drive|Power spectrum and frequency filters]].
* '''Channel files''': File type "channel", [[http://neuroimage.usc.edu/brainstorm/Tutorials/ChannelFile#On_the_hard_drive|Channel file / MEG-MRI coregistration]].
* '''SSP/ICA projectors''': Saved in the channel files, [[http://neuroimage.usc.edu/brainstorm/Tutorials/ArtifactsSsp#On_the_hard_drive|Artifact cleaning with SSP]].
* '''Head models''': File type "headmodel", [[http://neuroimage.usc.edu/brainstorm/Tutorials/HeadModel#On_the_hard_drive|Head model]].
* '''Noise covariance''': File types "noisecov" and "ndatacov", [[http://neuroimage.usc.edu/brainstorm/Tutorials/NoiseCovariance#On_the_hard_drive|Noise and data covariance matrices.]]
* '''Source files''': File types "results" and "link", [[http://neuroimage.usc.edu/brainstorm/Tutorials/SourceEstimation#On_the_hard_drive|Source estimation]].
* '''Time-frequency''': File type "timefreq", [[http://neuroimage.usc.edu/brainstorm/Tutorials/TimeFrequency#On_the_hard_drive|Time-frequency]].
* '''Statistics''': File types "pdata", "presults", "ptimefreq" and "pmatrix", [[http://neuroimage.usc.edu/brainstorm/Tutorials/Statistics#On_the_hard_drive|Statistics]].
* '''MRI volumes''': File type "subjectimage", [[http://neuroimage.usc.edu/brainstorm/Tutorials/ExploreAnatomy#On_the_hard_drive:_MRI|Display the anatomy]].
* '''Surfaces''': File type "tess", [[http://neuroimage.usc.edu/brainstorm/Tutorials/ExploreAnatomy#On_the_hard_drive:_Surface|Display the anatomy]].
* '''Scouts and atlases''': Saved in the surface files, [[http://neuroimage.usc.edu/brainstorm/Tutorials/Scouts#On_the_hard_drive|Scouts]].

== Custom processing ==
In many situations, you will find useful to read the files available in the database, and maybe modify them. The easiest approaches do not require any scripting, we will start by reviewing them quickly.

=== Process: Run Matlab command ===
If you want to modify the values saved in a file (eg. the field "F" from a "data" file), the easiest way is probably to use the process1 '''File > Run Matlab command'''. It is also available from Process2 in the category "Other".

It loads the files in input and run them through a piece of Matlab code that you can edit freely. It can extend a lot the flexibility of the Brainstorm pipeline manager, providing an easy access to any Matlab function or script.

. {{http://neuroimage.usc.edu/brainstorm/Tutorials/TutUserProcess?action=AttachFile&do=get&target=runMatlab.gif|runMatlab.gif|class="attachment"}}

The corresponding script looks like this:

{{{
sFiles = bst_process('CallProcess', 'process_matlab_eval', sFiles, [], ...
    'matlab', 'Data = Data.^2;', ...
    'sensortypes', 'MEG', ...
    'overwrite', 0);
}}}
=== Export/Import with the database explorer ===
Right-click on the Deviant average in the database explorer > '''File > Export to Matlab''' > "DataMat".

. {{attachment:export_matlab.gif||width="355",height="118"}}

{{{
Data exported as "DataMat"
>> DataMat
DataMat =
     ChannelFlag: [340x1 double]
    ColormapType: []
         Comment: 'Avg: deviant (39 files)'
        DataType: 'recordings'
          Device: 'CTF'
    DisplayUnits: []
               F: [340x361 double]
         History: {45x3 cell}
             Std: []
            Time: [1x361 double]
            nAvg: 39
          Events: [1x1 struct]
}}}
DataMat is the exact content of the corresponding .mat file, as loaded with Matlab's load() function. Edit some of the fields of this structure from the Matlab command window:

{{{
>> DataMat.Comment = 'Test square';
>> DataMat.F = DataMat.F .^ 2;
}}}
Now right-click on the '''folder''' containing the original file > '''File > Import from Matlab''' > DataMat:

{{attachment:import_matlab.gif||width="708",height="74"}}

If instead, you right-click on the original file and select the menu File > Import from Matlab, it overwrites the selected file instead of creating a new one with the selected structure.

== Reference: File manipulation ==
Useful functions for manipulating file names and paths (read the code of the functions for help):

* '''file_fullpath''': Converts a relative file path to an absolute path.
* '''file_short''': Converts an absolute file path to a short path, relative to the current protocol folder.
* '''file_gettype''': Returns the type of a file.

Reading files from a script (all the functions take relative paths in input):

* '''in_bst_data'''(DataFile): Read an imported epoch.
* '''in_bst_timefreq'''(TimefreqFile): Read a power spectrum, time-frequency or connectivity file.
* '''in_bst_headmodel'''(HeadmodelFile, ApplyOrient): Read a head model file and apply orientations.
* '''in_bst_results'''(ResultsFile, LoadFull): Load a source file and optionally reconstruct the full source time series on the fly (ImagingKernel * recordings).
* '''in_bst_matrix'''(MatrixFile): Read a file with the type "matrix".
* '''in_bst'''(FileName, TimeWindow): Read any Brainstorm data file with the possibility to load only a specific part of the file. "TimeWindow" is a range of time values in seconds: [tStart, tStop].
* '''bst_process'''(''''LoadInputFile'''', FileName, Target, TimeWindow): The most high-level function for reading data files. "Target" is a string with the list of signal names or types to load.
* '''bst_memory('GetConnectMatrix'''', TimefreqMat): Rebuild a full connectivity matrix.
* '''in_fopen'''(DataFile, FileFormat, ImportOptions): Low-level function for opening continuous files.
* '''in_fread'''(sFile, ChannelMat, iEpoch, SamplesBounds, iChannels, ImportOptions): Low-level function for reading blocks from continuous files. Requires a call to in_fopen first to get the sFile structure.

Saving files:

* '''bst_save'''(FileName, FileMat, Version, isAppend): Save a file but does not register it in the database.
  * FileName: Absolute path to a .mat file, use in combination with file_fullpath for relative paths.
  * FileMat: Valid Brainstorm structure, corresponding to the file type.
  * Version: Defines which version of the Matlab .mat format is used to store the data: <<BR>>- 'v6': Fastest option, bigger files, no compression, no files >2Gb<<BR>>- 'v7': Slower option, compressed, no files >2Gb<<BR>>- 'v7.3': Much slower than the others, compressed, but only way to save files > 2Gb.
  * isAppend: If set to 1, updates only the fields defined in FileMat, keep the others untouched.
* '''file_unique''': Produces a unique file name by adding a number tag to it.
* '''bst_process('GetNewFilename'''', OutputFolder, BaseFilename): Generate a new unique file name based on the beginning of the file name (eg. BaseFilename='data_average_test_').

Registering new files in the database:

* '''db_add'''(iStudy/iSubject, FileMat): Add a new file in an anatomy folder or a functional data folder. This function saves the file and then reloads the folder. FileMat must be a structure, not a filename. You should not save the file manually before calling this function.
* '''db_add_data'''(iStudy, FileName, FileMat): Register in the database a structure FileMat that has already been saved in file FileName. You should call bst_save manually before calling this function.
* '''db_add_data'''(iStudy, FileName, FileMat, iItem): Overwrites the existing file #iItem.

Reload folders (if you saved or deleted files without registering correctly the modification in the database):

* '''db_reload_studies'''(iStudies): Reload only the select data folders (aka "studies").
* '''db_reload_conditions'''(iSubjects): Reload all the data folders for a subject.
* '''db_reload_subjects'''(iSubjects): Reload the anatomy of the selected subjects.
* '''db_reload_database'''('current'): Reload the entire protocol (anatomy and functional data).

Other useful database functions:

* '''db_add_condition''': Create a new folder in a subject.
* '''db_add_subject''': Create a new subject.
* '''db_delete_studies''': Delete a list of folders.
* '''db_delete_subjects''': Delete a list of subjects.
* '''db_group_conditions''': Merge two folders from the same subject.
* '''db_rename_condition''': Rename a folder.
* '''db_rename_subject''': Rename a subject.
* '''db_set_channel''': Set the channel file for a folder.
* '''db_set_noisecov''': Set the noise/data covariance for a folder, or copy to other folders/subjects.
* '''db_set_template''': Copy an anatomy template to a subject or use it as the default anatomy.

Export a file from the database to other file formats (read the comments in the functions for help):

* export_channel
* export_data
* export_events
* export_result
* export_timefreq
* export_matrix
* export_mri
* export_surfaces
* export_protocol: Export a subject or an entire protocol as a .zip file.

Convert Brainstorm structures to FieldTrip structures:

* out_fieldtrip_channel
* out_fieldtrip_data
* out_fieldtrip_timefreq
* out_fieldtrip_headmodel
* out_fieldtrip_results
* out_fieldtrip_matrix

== Reference: Display functions ==
Create new visualization figures:

* '''view_channels''': Display sensors in a 3D figure.
* '''view_helmet''': Display the inner surface of the MEG helmet in a 3D figure.
* '''view_timeseries''': Display a data file as time series.
* '''view_timeseries_matrix''': Display a custom matrix as time series.
* '''view_topography''': Display a data file as a spatial topography.
* '''view_erpimage''': Display multiple data files as an image, signal by signal.
* '''view_timefreq''': Open a time-frequency file (various display modes available).
* '''view_spectrum''': Display a power spectrum (PSD or time-frequency files).
* '''view_connect''': Open a connectivity matrix (various display modes available).
* '''view_matrix''': Open a "matrix" file (various display modes available).
* '''view_contactsheet''': Create a contact sheet in time or across a volume from an existing figure.
* '''view_noisecov''': Display a noise or data covariance file.
* '''view_dipoles''': Open a dipoles file (various display modes available).
* '''view_pac''': Open PAC results (various display modes available).
* '''view_mri''': View a MRI file in the MRI viewer (with or without a functional overlay from a source file).
* '''view_mri_3d''': View a MRI file in a 3D figure (with or without a functional overlay from a source file).
* '''view_surface''': View a surface.
* '''view_surface_data''': View a surface file with a source file as its texture.
* '''view_surface_matrix''': View a custom surface (user defines vertices, faces, color, transparency).
* '''view_image_reg''': Display a 3D or 4D matrix as an image with time and/or frequency dimensions.
* '''view_struct''': Display a structure as with the popup menu "File > View file contents".
* '''script_view_sources''': Shortcut script to display source files.
* bst_memory(''''UnloadAll'''', 'Forced'): Close all the existing figures.

Configure time-series figures:

* panel_time(''''SetCurrentTime'''', t): Set current time.
* panel_record(''''SetTimeLength'''', duration): Set the length of the current display page, in seconds.
* panel_record(''''SetStartTime'''', t): Set the start of the current page, in seconds.
* panel_record(''''SetDisplayMode'''', hFig, DisplayMode): 'column' or 'butterfly'.
* panel_filter(''''SetFilters'''', isLowPass, LowPass, isHighPass, HighPass, isSinRem, SinRem, isMirror)

* panel_montage(''''SetCurrentMontage'''', hFig, MontageName): Change the montage of channels.

* bst_figures(''''SetSelectedRows'''', SelectedChannels): Set selected channels (cell array of strings).

* figure_timeseries(''''SetTimeSelectionManual'''', hFig, TimeWindow): Select a time segment.

Configure 3D figures:

* figure_3d(''''SetStandardView'''', hFig, 'left'): Change camera view (top,bottom,left,right,front,back).
* figure_3d(''''ViewSensors'''', hFig, isMarkers, isLabels): Enable the view of sensor markers and labels.
* panel_surface(''''SetShowSulci'''', hFig, iTess, 1): Show/hide the sulci (darker color for deeper areas).
* panel_surface(''''SetSurfaceColor'''', hFig, iTess, [1 0 0]): Set the surface color.
* panel_surface(''''SetSurfaceSmooth'''', hFig, iTess, Smooth, 0): Set the amount of smoothing (0-1).
* panel_surface(''''SetSurfaceTransparency'''', hFig, iTess, Transp): Set the surface transparency (0-1).
* panel_surface(''''SetDataThreshold'''', hFig, iTess, Thresh): Set the amplitude threshold.
* panel_surface(''''SetSizeThreshold'''', hFig, iTess, MinSize): Set size threshold (min size slider).
* figure_mri(''''SetLocation'''', CsName, hFig, [], xyz): CsName=voxel/mri/scs/mni, xyz=[x,y,z]

Configure time-frequency figures:

* panel_freq(''''SetCurrentFreq'''', iFreq, 1): Set the current frequency index (from the Freqs vector)

* panel_freq(''''SetCurrentFreq'''', Freq, 0): Set the current frequency (in Hz).
* sOptions = panel_display(''''GetDisplayOptions''''): Get display options selected in the Display tab.
* panel_display(''''SetDisplayOptions'''', sOptions): Change the options selected in the Display tab.
* sOptions.'''HideEdgeEffects''': Controls the checkbox "Hide edge effects" (0 or 1).
* sOptions.'''HighResolution''': Controls the checkbox "Smooth display" (0 or 1).
* sOptions.'''RowName''': Controls the signal that is currently displayed (for 'SingleSensor' display mode).
* sOptions.'''Function''': Controls the display function (magnitude, power, log, phase).

Configure colormaps:

* bst_colormaps(''''SetColormapName'''', ColormapType, ColormapName): 'jet', 'parula', 'cmap_rbw', ...
* bst_colormaps(''''SetMaxMode'''', ColormapType, MaxMode): Colorbar range ('global', 'local', 'custom').
* bst_colormaps(''''SetMaxCustom'''', ColormapType, [], Min, Max): Set a custom colorbar range.
* bst_colormaps(''''SetColormapAbsolute'''', ColormapType, isAbsolute): Show positive or relative values
* bst_colormaps(''''SetDisplayColorbar'''', ColormapType, isDisplay): Show colorbar in the figures.
* bst_colormaps(''''RestoreDefaults'''', ColormapType): Restore the default configuration for a colormap.
* ColormapType: anatomy, meg, eeg, sources, stat1, stat2, time, timefreq, connect1, connectn, image

Configure statistical thresholding:

* StatThreshOptions = bst_get(''''StatThreshOptions''''): Get display options selected in the Stat tab.
* bst_set(''''StatThreshOptions'''', StatThreshOptions): Change the options selected in the Stat tab.
* StatThreshOptions.'''pThreshold''': Current p-Value threshold.
* StatThreshOptions.'''Correction: '''Correction for multiple comparisons ('none', 'fdr', 'bonferroni')
* StatThreshOptions.'''Control''': List of dimensions to correct for multiple comparisons (default = [1 2 3])

Export the contents of a figure to a file:

* '''out_figure_image''': Screen capture of any Brainstorm figure.
* '''out_figure_movie''': Save a movie from one or multiple Brainstorm figures.
* '''out_figure_timefreq''': Extract some of the data displayed in a time-frequency figure.
* '''out_figure_timeseries''': Extract some of the data displayed in a time series figure.

== Example: Creating a new file ==
This section illustrates how to add new files to the database. We will create a sinusoidal signal and save it in a "matrix" file, in a new folder of the subject "Test".

{{{
% Time: 1 second with a sampling frequency of 1000Hz
t = 0:0.001:1;
% Generate two sinsuoidal signals (20Hz,30Hz)
F = [sin(20*2*pi*t); 0.5*sin(30*2*pi*t)];

% Initialize an empty "matrix" structure
sMat = db_template('matrixmat');
% Fill the required fields of the structure
sMat.Value = F;
sMat.Comment = 'Test sinusoids';
sMat.Description = {'Signal #1: 20Hz'; 'Signal #2: 30Hz'};
sMat.Time = t;

% Create a new folder "Script" in subject "Test"
iStudy = db_add_condition('Test', 'Script');
% Get the corresponding study structure
sStudy = bst_get('Study', iStudy);
}}}
There are many options to add a new file to the database, with various levels of requirements. You can call the db_add function (reloads the destination folder, therefore slow if you save many files), save the file in the corresponding folder and reload the protocol (slow as well), or register the file in the database manually (more complicated but faster).

'''Option #1: db_add'''

{{{
OutputFile = db_add(iStudy, sMat);
}}}
'''Option #2: bst_save / '''db_reload_studies

{{{
% Get the full path to the new folder
% (same folder as the brainstormstudy.mat file for this study)
OutputFolder = bst_fileparts(file_fullpath(sStudy.FileName));
% Get a new unique filename (including a timestamp)
MatrixFile = bst_process('GetNewFilename', OutputFolder, 'matrix_test');
% Save file
bst_save(MatrixFile, sMat, 'v6');
% Reload the folder in which the new file was saved
db_reload_studies(iStudy);
}}}
'''Option #3: bst_save / '''db_add_data

{{{
% Another way to generate a unique filename (without a timestamp)
MatrixFile = file_unique(bst_fullfile(OutputFolder, 'matrix_test.mat'));
% Save file
bst_save(MatrixFile, sMat, 'v6');
% Reference saved file in the database
db_add_data(iStudy, MatrixFile, sMat);
% Update the database explorer display
panel_protocols('UpdateNode', 'Study', iStudy);
}}}
. {{attachment:newfile.gif||width="521",height="166"}}

== Example: Editing events ==
A step that commonly requires manual changes is the definition of the event markers. For example, we have to combine external triggers or behavioral information with the existing events. This example illustrates how to load the events, modify them and save them back.

For the continuous recordings, the events are saved in the .mat file corresponding to the "Link to raw file". These structures contain only meta-data and information created with Brainstorm, the EEG/MEG recordings are available in a separate binary file. First, we need to load this link.

{{{
% Right-click on a "Link to raw file" in the database explorer
% > File > Copy file path to clipboard
RawFile = '/.../@rawS01.../data_0raw_S01_..._01_600Hz_notch.mat'

% Load the "sFile" structure, contained in the .F structure
% of the link file (data_0raw...mat)
sRaw = in_bst_data(RawFile, 'F');

>> sRaw.F.events
ans =
1x7 struct array with fields:
    label
    color
    epochs
    samples
    times
    reactTimes
    select
}}}
For example, let's say we want to add 30ms to all the events in the category "button" in order to compensate for some hardware delay, and create a new event category with the modified timing. We need first to identify what is the '''index of the category "button"''', in this array of 7 event structures.

{{{
% Find the index of the event category "button"
iEvtButton = find(strcmpi({sRaw.F.events.label}, 'button'));

>> iEvtButton
iEvtButton =
     3
}}}
In the code above, note this special Matlab syntax that allows the '''concatenation''' of the values of one field across multiple structures, in an array of structures:

{{{
>> {sRaw.F.events.label}
ans =
    'standard' 'deviant' 'button' 'cardiac'
    'blink' 'bad_1-7Hz' 'bad_40-240Hz'
}}}
If you want to search instead all the events containing a specific tag, for example "bad", you can use the '''cellfun''' function (applies the same function sequentially to all the elements in a cell array and concatenates the results) in combination with the '''strfind''' function (search for a substring). The final call to the '''find''' function returns at which indices the list of tags found in the event label is not empty.

{{{
>> iEvtBad = find( ~cellfun( @(c)isempty(strfind(c,'bad')), ...
                             {sRaw.F.events.label}))
iEvtBad =
     6 7
}}}
The code below copies the existing event category "button", renames it and add a 30ms offset. Note that the '''times''' and '''samples''' field must always match. If you modify one, you must modify the others as well (times = samples/sfreq). If you add or remove events, you must adjust the size of the '''epochs''' field (always 1 for most file formats).

{{{
% Copy the event category "button" to a new category
iEvtNew = length(sRaw.F.events) + 1;
sRaw.F.events(iEvtNew) = sRaw.F.events(iEvtButton);
% Rename the new event to "button_offset"
sRaw.F.events(iEvtNew).label = 'button_offset';

% How many samples in 30ms (0.030s * 600Hz = 18 samples)
offsetSample = round(0.030 .* sRaw.F.prop.sfreq);
% Apply offset to the events in the "button_offset" category
sRaw.F.events(iEvtNew).samples = ...
    sRaw.F.events(iEvtNew).samples + offsetSample;
% Re-compute the corresponding times
sRaw.F.events(iEvtNew).times = ...
    sRaw.F.events(iEvtNew).samples ./ sRaw.F.prop.sfreq;
% Re-generate an epochs field with only ones
% (optional here, as we didn't change the number of evt)
sRaw.F.events(iEvtNew).epochs = ...
    ones(1, size(sRaw.F.events(iEvtNew).times, 2));
% Change the event color to yellow (red=1, green=1, blue=0)
sRaw.F.events(iEvtNew).color = [1 1 0];

>> sRaw.F.events(iEvtNew)
ans =
         label: 'button_offset'
         color: [1 1 0]
        epochs: [1x40 double]
       samples: [1x40 double]
         times: [1x40 double]
    reactTimes: []
        select: 1
}}}
The last step is to '''save the modifications''' back to the "Link to raw file". Here the call to '''file_fullpath''' is optional because the variable RawFile already contains the absolute path to the file.

{{{
% Update the sRaw structure to the RawFile file (the last parameter appends to the existing struct)
bst_save(file_fullpath(RawFile), sRaw, 'v6', 1);
}}}
Open the recordings to make sure your transformation worked the way you expected.

. {{attachment:edit_events.gif||width="461",height="146"}}

== Find examples in the code ==
The easier way to understand how to use a function is to search the code with the "'''Find files'''" interface in Matlab. Go to the brainstorm3 folder, click on "Find files" (or Ctrl+Shift+F), enter the name of a function in "Find files containing text", Include subfolders, Match case. It will return all the lines that include the string you entered across all the files in the Brainstorm distribution. Just double-click on a line to jump to the code in the Matlab editor.

{{attachment:find_files.gif||width="638",height="307"}}

You can use the same interface to '''find what function is called''' when you click on a button or menu in the interface. Search for the label or the tooltip of the interface element in the same way. The example below shows how to track what happens when you click on the headmodel popup menu "Check spheres".

{{attachment:find_files2.gif||width="726",height="95"}}

If you have trouble understanding how to set some input parameters, you can use the '''debugger''' to explore a real use case. Place a breakpoint at the begging of your function of interest (watch [[https://www.youtube.com/watch?v=PdNY9n8lV1Y|this tutorial]] if you don't know how to do this), for example in view_timeseries.m. Then click on the corresponding menus in the Brainstorm interface (eg. double-click on a data file). When the execution reaches the line you selected, it stops and gives you back the commands. You can explore the values in all the variables, modify them, and execute the code step by step (many options available in the Editor tab of Matlab).

{{attachment:debugger.gif||width="509",height="268"}}

== Additional quality control ==
You can add in the reports all the information that may help you control the quality of the analysis, or figures you want to include in publications or clinical reports. The process "File > Save snapshot" lets you save some predefined views, but you can also custom screen captures. The example below shows how to add a "[[http://neuroimage.usc.edu/brainstorm/Tutorials/Epoching#Raster_plot|raster plot]]" for all the deviant trials from Run#01 in the report.

{{{
% Get all the deviant trials in Run#01 (the list includes the deviant average)
sDeviant = bst_process('CallProcess', 'process_select_files_data', [], [], ...
    'subjectname', 'Subject01', ...
    'condition', 'S01_AEF_20131218_01_600Hz_notch', ...
    'tag', 'deviant');

% Open raster plot
hFig = view_erpimage({sDeviant.FileName}, 'erpimage', 'MEG');
% Select the channel MRT34
sOptions = panel_display('GetDisplayOptions');
sOptions.RowName = 'MRT34';
panel_display('SetDisplayOptions', sOptions);

% Screen capture of this figure
% bst_report('Snapshot', hFig, FileName, Comment, WindowPosition);
bst_report('Snapshot', hFig, [], 'ERP image: MRT34', [300 100 600 400]);
% Close figure
close(hFig);
}}}
You can also add messages in the reports (information, warning or errors).

{{{
% Function call: bst_report(MsgType, sProcess, sInputs, Message)
bst_report('Info', [], sDeviant, 'This is an information message.');
bst_report('Warning', [], sDeviant, 'This is a warning.');
bst_report('Error', [], sDeviant, 'This is an error.');

% Open the report viewer to show the current report (not saved yet)
bst_report('Open', 'Current');
}}}
Report generated with the code above:

. {{attachment:report2.gif||width="510",height="349"}}

== Loop over subjects ==
Creating loops is not supported yet by the script generator, but relatively easy to do from a script without knowing too much about Matlab programming. The example below shows how to create a loop over subjects to import their anatomy. The dataset used here is from the tutorial [[Tutorials/VisualSingle|MEG visual: single subject]].

With the Process1 box empty, select the process "Import > Import anatomy > '''Import anatomy folder'''" and generate a script. Simplify if using the guidelines presented in the previous sections:

{{{
% Input files
SubjectNames = {'sub001'};
RawFiles = {...
    '/.../Tutorials/sample_group/freesurfer/sub001'};

% Process: Import anatomy folder
bst_process('CallProcess', 'process_import_anatomy', [], [], ...
    'subjectname', SubjectNames{1}, ...
    'mrifile', {RawFiles{1}, 'FreeSurfer'}, ...
    'nvertices', 15000);
}}}
Add the other subject names and corresponding FreeSurfer folders in the script header:

{{{
SubjectNames = {'sub001', 'sub002', 'sub003', 'sub004'};
RawFiles = {...
    '/.../Tutorials/sample_group/freesurfer/sub001', ...
    '/.../Tutorials/sample_group/freesurfer/sub002', ...
    '/.../Tutorials/sample_group/freesurfer/sub003', ...
    '/.../Tutorials/sample_group/freesurfer/sub004'};
}}}
Add a [[http://www.mathworks.com/help/matlab/ref/for.html|for loop]] around all the steps to repeat on each subject ("for" before, and "end" after the code), and replace the indices "1" with the loop variable:

{{{
% Loop on subjects
for iSubject = 1:length(SubjectNames)
    % Process: Import anatomy folder
    bst_process('CallProcess', 'process_import_anatomy', [], [], ...
        'subjectname', SubjectNames{iSubject}, ...
        'mrifile', {RawFiles{iSubject}, 'FreeSurfer'}, ...
        'nvertices', 15000);
end
}}}
== Loop over acquisition runs ==
If you have multiple subjects for which the anatomy is already imported, and multiple runs to process for each subject, you can add two nested for loops to link all the runs to the database in the same script. The dataset used here is from the tutorial [[Tutorials/VisualSingle|MEG visual: single subject]].

With the Process1 box empty, select the process "Import > Import recordings > '''Create link to raw file'''" and generate a script. Simplify if using the guidelines presented in the previous sections:

{{{
% Input files
SubjectNames = {'sub001'};
RawFiles = {...
    '/.../sample_group/ds117/sub001/MEG/run_01_sss.fif'};

% Process: Create link to raw file
sFileRaw = bst_process('CallProcess', 'process_import_data_raw', [], [], ...
    'subjectname', SubjectNames{1}, ...
    'datafile', {RawFiles{1}, 'FIF'}, ...
    'channelreplace', 0, ...
    'channelalign', 0, ...
    'evtmode', 'value');
}}}
Add the other subject names and all the runs for all the subjects (array of cell arrays) in the script header:

{{{
SubjectNames = {'sub001', 'sub002'};
RawFiles = {...
    {'/.../sample_group/ds117/sub001/MEG/run_01_sss.fif', ...
     '/.../sample_group/ds117/sub001/MEG/run_02_sss.fif', ...
     '/.../sample_group/ds117/sub001/MEG/run_03_sss.fif'}, ...
    {'/.../sample_group/ds117/sub002/MEG/run_01_sss.fif', ...
     '/.../sample_group/ds117/sub002/MEG/run_02_sss.fif', ...
     '/.../sample_group/ds117/sub002/MEG/run_03_sss.fif'}};
}}}
Add two for loops around the code to repeat on all the runs:

{{{
% Loop on subjects
for iSubject = 1:length(SubjectNames)
  % Loop on runs for each subject
  for iRun = 1:length(RawFiles{iSubject})
    % Process: Create link to raw file
    sFileRaw = bst_process('CallProcess', 'process_import_data_raw', [], [], ...
        'subjectname', SubjectNames{iSubject}, ...
        'datafile', {RawFiles{iSubjects}{iRun}, 'FIF'}, ...
        'channelreplace', 0, ...
        'channelalign', 0, ...
        'evtmode', 'value');
  end
end
}}}
== How to process an entire study ==
This section proposes a standard workflow for processing a full group study with Brainstorm. It contains the same steps of analysis as the introduction tutorials, but separating what can be done automatically from what should be done manually. This workflow can be adapted to most ERP studies (stimulus-based).

* '''Prototype''': Start by processing one or two subjects completely '''interactively''' (exactly like in the introduction tutorials). Use the few pilot subjects that you have for your study to prototype the analysis pipeline and check manually all the intermediate stages. Take notes of what you're doing along the way, so that you can later write a script that reproduces the same operations.
* '''Anatomical fiducials''': Set NAS/LPA/RPA and compute the MNI transformation for each subject.
  * '''Segmentation''': Run FreeSurfer/BrainSuite to get surfaces and atlases for all the subjects.
  * '''File > Batch MRI fiducials''': This menu prompts for the selection of the fiducials for all the subjects and saves a file __fiducials.m__ in each segmentation folder. You will not have to redo this even if you have to start over your analysis from the beginning.
  * '''Script''': Write a loop that calls the process "Import anatomy folder" for all the subjects.
  * '''Alternatives''': Create and import the subjects one by one and set the fiducials at the import time. Or use the default anatomy for all the subjects (or use [[Tutorials/TutWarping|warped templates]]).

* '''Script #1''': Pre-processing: Loop on the subjects and the acquisition runs.
  * '''Create link to raw files''': Link the subject and noise recordings to the database.
  * '''Event markers''': Read and group triggers from digital and analog channel, fix stimulation delays
  * '''Evaluation''': Power spectrum density of the recordings to evaluate their quality.
  * '''Pre-processing''': Notch filter, sinusoid removal, band-pass filter.
  * '''Evaluation''': Power spectrum density of the recordings to make sure the filters worked well.
  * '''Cleanup''': Delete the links to the original files (the filtered ones are copied in the database).
  * '''Detect artifacts''': Detect heartbeats, Detect eye blinks, Remove simultaneous.
  * '''Compute SSP''': Heartbeats, Blinks (this selects the first component of each decomposition)
  * '''Compute ICA''': If you have some artifacts you'd like to remove with ICA (no default selection).
  * '''Screenshots''': Check the MRI/sensors registration, PSD before and after corrections, SSP.
  * '''Export the report''': One report per subject, or one report for all the subjects, saved in HTML.
* '''Manual inspection #1''':
  * '''Check the reports''': Information messages (number of events, errors and warnings) and screen captures (registration problems, obvious noisy channels, incorrect SSP topographies).
  * '''Mark bad channels''': Open the recordings, select the channels and mark them as bad. Or use the process "Set bad channels" to mark the same bad channels in multiple files.
  * '''Fix the SSP/ICA''': For the suspicious runs: Open the file, adjust the list of blink and cardiac events, remove and recompute the SSP decompositions, manually select the components.
  * '''Detect other artifacts''': Run the process on all the runs of all the subjects at once (select all the files in Process1 and run the process, or generate the equivalent script).
  * '''Mark bad segments''': Review the artifacts detected in 1-7Hz and 40-240Hz, keep only the ones you really want to remove, then mark the event categories as bad. Review quickly the rest of the file and check that there are no other important artifacts.
  * '''Additional SSP''': If you find one type of artifact that repeats (typically saccades and SQUID jumps), you can create additional SSP projectors, either with the process "SSP: Generic" or directly from a topography figure (right-click on the figure > Snapshot> Use as SSP projector).
* '''Script #2''': Subject-level analysis: Epoching, averaging, sources, time-frequency.
  * '''Importing''': Process "Import MEG/EEG: Events" and "Pre-process > Remove DC offset".
  * '''Averaging''': Average trials by run, average runs by subject (registration problem in MEG).
  * '''Noise covariance''': Compute from empty room or resting recordings, copy to other folders.
  * '''Head model''': Compute for each run, or compute once and copy if the runs are co-registered.
  * '''Sources''': Compute for each run, average across runs and subjects in source space for MEG.
  * '''Time-frequency''': Computation with Hilbert transform or Morlet wavelets, then normalize.
  * '''Screenshots''': Check the quality of all the averages (time series, topographies, sources).
  * '''Export the report''': One report per subject, or one report for all the subjects, saved in HTML.
* '''Manual inspection #2''':
  * '''Check the reports''': Check the number of epochs imported and averaged in each condition, check the screen capture of the averages (all the primary responses should be clearly visible).
  * '''Regions of interest''': If not using predefined regions from an atlas, define the scouts on the anatomy of each subject (or on the template and then project them to the subjects).
* '''Script #3''': Group analysis, ROI-based analysis, etc.
  * '''Averaging''': Group averages for the sensor data, the sources and the time-frequency maps.
  * '''Statistics''': Contrast between conditions or groups of subjects.
  * '''Regions of interest''': Any operation that involve scouts.

== Final scripts ==
The following script from the Brainstorm distribution reproduces the introduction tutorials ("Get started"): '''brainstorm3/toolbox/script/tutorial_introduction.m''' - Report: [[http://neuroimage.usc.edu/bst/examples/report_TutorialIntroduction.html|report_TutorialIntroduction.html]]

<<HTML(<div style="border:1px solid black; background-color:#EEEEFF; width:720px; height:400px; overflow:scroll; padding:10px; font-family: Consolas,Menlo,Monaco,Lucida Console,Liberation Mono,DejaVu Sans Mono,Bitstream Vera Sans Mono,Courier New,monospace,sans-serif; font-size: 13px; white-space: pre;">)>><<EmbedContent("http://neuroimage.usc.edu/bst/viewcode.php?f=tutorial_introduction.m")>><<HTML(</div >)>>

<<BR>>For an example of a script illustrating how to create loops, look at the tutorial [[Tutorials/VisualSingle|MEG visual: single subject]]. '''brainstorm3/toolbox/script/tutorial_visual_single.m''' - Report: [[http://neuroimage.usc.edu/bst/examples/report_TutorialVisual_sub001.html|report_TutorialVisual_sub001.html]]

<<HTML(<div style="border:1px solid black; background-color:#EEEEFF; width:720px; height:400px; overflow:scroll; padding:10px; font-family: Consolas,Menlo,Monaco,Lucida Console,Liberation Mono,DejaVu Sans Mono,Bitstream Vera Sans Mono,Courier New,monospace,sans-serif; font-size: 13px; white-space: pre;">)>><<EmbedContent("http://neuroimage.usc.edu/bst/viewcode.php?f=tutorial_visual_single.m")>><<HTML(</div >)>>

== Running scripts on a cluster ==
Like mentioned above Brainstorm can be started in different ways. To use Brainstorm on a distant server the starting command "'''brainstorm server'''" needs to be used.

Before using Brainstorm on a distant server a few adjustments need to be done.

At first Matlab (including the Signal Processing Toolbox --- depending on the used functions) needs to be installed on the server and a Brainstorm version needs to be located on the server. For the Brainstorm database, the folder "brainstorm_db" needs to be created. Regarding the file structure on the server, the path for the brainstorm folders could look like this:

'''/home/user/brainstorm3'''

'''/home/user/brainstorm_db/anat'''

'''/home/user/brainstorm_db/data'''

In the "brainstorm_db" folder all the files you want to process need to be included. To not miss any files, the easiest solution would be to upload the whole "brainstorm_db" folder from your computer to the server. On the local computer Brainstorm might create missing files, e.g. "protocol.m", on its own. On the server it might not be able to do so and will crash.

To run a script using Brainstorm on a distant server also the script needs to be prepared. The following lines should be included:

{{{
% Set up the Brainstorm files
pathStr = '/home/user/brainstorm3/';
addpath(genpath(pathStr));
BrainstormDbDir = '/home/user/brainstorm_db';
% Start Brainstorm
if ~brainstorm('status')
    brainstorm server
end
bst_set('BrainstormDbDir',BrainstormDbDir)
% Select the correct protocol
ProtocolName = 'Study'; % Enter the name of your protocol
sProtocol.Comment = ProtocolName;
sProtocol.SUBJECTS = [home 'anat'];
sProtocol.STUDIES = [home 'data'];
db_edit_protocol('load',sProtocol);
% Get the protocol index
iProtocol = bst_get('Protocol', ProtocolName);
if isempty(iProtocol)
    error(['Unknown protocol: ' ProtocolName]);
end
% Select the current procotol
gui_brainstorm('SetCurrentProtocol', iProtocol);
}}}
Afterwards, you might add your analysis script. For example, you may create a script using the Brainstorm pipeline and add these lines to the top of your script and run it on the server.

To run a script using Brainstorm on a server you should check that there is a free matlab license on the server and RAM/Quota is big enough for the data you will create while processing. Also the Matlab version might differ from the version installed on your local computer. The lines above were tested using Matlab 2015b on a server.

A Brainstorm script can be executed either directly (it needs to start Brainstorm itself), or started using the syntax '''brainstorm <script.m> <parameters>''' (starts Brainstorm in server mode, executes the script and quit Brainstorm).

Brainstorm scripts can also be executed from the '''compiled version of Brainstorm''', therefore not requiring a Matlab license, only the installation of the free MCR library (see the [[Installation]] page). Add the full path to the script to execute and the script parameters to the start script:<<BR>> '''brainstorm3.bat <script.m>''' or '''brainstorm3.command <script.m>'''.

== Finding interface callback functions ==
If you are looking for the function called by a menu or a button in the interface:

* In Matlab, go to the "brainstorm3" folder
* Click on the button "Find file" in the ribbon "Editor" of Matlab interface (Ctrl+Shift+F)
* Select the option "Include subfolders"
* Search for the text of the menu or button you are looking for (eg. 'Set as default'); you can do a case-sensitive or a case-insensitive search (option "Match case")
* It gives you the list of all the places where this text appears in the Brainstorm code. In the previous example, in tree_callbacks.m, you’d find a call to function SetDefaultSurf.
* Double-click on the corresponding line to jump to the code
* Right-click on "SetDefaultSurf" > Open "SetDefaultSurf"
* The editor should jump to the code of function SetDefaultSurf(), and there you’d find your call to "db_surface_default"
* Right-click on it > Open "db_surface_default" to open the function and read the header that should explain its usage (this example is not very detailed, sorry)
* Sometimes it helps to look at other examples of calls to this function: Use the window "Find files" again to search for text "db_surface_default"<<BR>>

== Additional documentation ==
* Tutorial: [[Tutorials/TutUserProcess|How to write your own process]]
* Tutorial: [[Java|Java in Brainstorm]]

<<EmbedContent("http://neuroimage.usc.edu/bst/get_prevnext.php?prev=Tutorials/Workflows")>> lang="en"> class="line867"> 28: Scripting class="line867">Authors: Francois Tadel, Elizabeth Bock, Matthias Sure, Sylvain Baillet
The previous tutorials explained how to use Brainstorm in an interactive way to process one subject with two acquisition runs. In the context of a typical neuroimaging study, you may have tens or hundreds of subjects to process in the same way, it is unrealistic to do everything manually. Some parts of the analysis can be processed in batches with no direct supervision, others require more attention. This tutorial introduces tools and tricks that will help you assemble an efficient analysis pipeline.
Requirements: You need a license for the Matlab environment in order to use these tools and execute custom scripts. If you are running the compiled version of Brainstorm with the MCR library, the only custom code you can run is through the menu "File > Matlab console" and the process "Run Matlab command".
Contents
a new script
by line: Header
by line: Body
by line: Footer
the calls
in Matlab
conventions
the script
the script again
Brainstorm
requests
structures
processing
ulation">Reference: File manipulation
nctions">Reference: Display functions
ew_file">Example: Creating a new file
Editing events
examples in the code
ntrol">Additional quality control
over subjects
over acquisition runs
ire_study">How to process an entire study
scripts
cluster">Running scripts on a cluster
lback_functions">Finding interface callback functions
ion">Additional documentation

a new script class="line862">The easiest way to get started with a new Brainstorm script is to use the script generator, already introduced in the tutorial Select files and run processes. Select some files in the Process1 or Process2 tabs, select a list of processes, and use the menu Generate .m script. The example below should work with the protocol "TutorialIntroduction" created during the introduction tutorials.
In the Process1 tab, leave the selection box empty and click on [Run]. Instead of selecting the files from the Brainstorm interface, we will select them directly from the database using a script.
Select process File > Select files: Recordings (do not execute immediately)
Condition=[Empty], File comment=Avg: deviant (the space is important).
class="attachment" height="334" src="/brainstorm/Tutorials/Scripting?action=AttachFile&do=get&target=start1.gif" title="start1.gif" width="400" />
This process selects all the recordings with a comment including the string "Avg: deviant", from all the folders in Subject01 (except for "Intra-subject" and "Common files"). We expect to get two files: the averages of the deviant condition for both runs.
Add process Pre-process > Band-pass filter: Lower cutoff=0Hz, Upper cutoff=30Hz, 60dB.
> Save snapshot: Recordings time series, Sensors=MEG.
class="attachment" height="353" src="/brainstorm/Tutorials/Scripting?action=AttachFile&do=get&target=start2.gif" title="start2.gif" width="536" />
This will apply a low-pass filter at 30Hz and save a screen capture of the signals in the report.
Do not run the pipeline, select the menu Generate .m script instead. It saves a new .m file and opens it in the Matlab editor. Close the pipeline editor window and look at the script.
class="attachment" height="272" src="/brainstorm/Tutorials/Scripting?action=AttachFile&do=get&target=start3.gif" title="start3.gif" width="673" />
The script you just generated can be the starting point to your own custom script. The following sections explain line by line how they work and how to edit them.
by line: Header class="line867">
% Script generated by Brainstorm (19-Jul-2016)
All the lines starting with a "%" are comments, they are never executed.
% Input files -1">sFiles = []; -1">SubjectNames = {... 'Subject01'};
These lines define the script inputs:
sFiles: The list of files in input. Currently empty because we did not select anything in the Process1 list. If we had selected files, it would contain a cell array of strings with relative file paths.
SubjectNames: List of subject names that are used in the script. Most of the times, the generated scripts contain only one entry, but it is written as a cell array to make it easier to extend to multiple subjects with a loop (described further in this tutorial).
% Start a new report -2">bst_report('Start', sFiles);
Starts a new report of activity: Clears all the previous logs and gets ready to record new messages. The report will collect all the messages that are generated during the execution of the script by the various processes. You can explicitly add screen captures and additional messages to the current report with the function bst_report. This report will remain open until the function bst_report('Start') is called again. To display the current report, use the menu File > Report viewer.
The syntax function_name('SubFunction', arguments) is used a lot in Brainstorm: it calls a subfunction available inside a .m file. This line above calls the function Start() in the file brainstorm3/toolbox/process/bst_report.m. This is made possible with the use of the short script "macro_method". Many of the Brainstorm .m files are actually libraries of functions, rather than simple "scripts" or "functions".
by line: Body class="line867">
% Process: Select data files in: Subject01/*/Avg: deviant -3">sFiles = bst_process('CallProcess', 'process_select_files_data', sFiles, [], ... 'subjectname', SubjectNames{1}, ... 'condition', '', ... 'tag', 'Avg: deviant', ... 'includebad', 0, ... 'includeintra', 0, ... 'includecommon', 0); -1"> Process: Low-pass:30Hz 1-1">sFiles = bst_process('CallProcess', 'process_bandpass', sFiles, [], ... 'sensortypes', 'MEG', ... 'highpass', 0, ... 'lowpass', 30, ... 'attenuation', 'strict', ... % 60dB 'mirror', 0, ... 'useold', 0, ... 'overwrite', 0); 9-1"> Process: Snapshot: Recordings time series 1-1">sFiles = bst_process('CallProcess', 'process_snapshot', sFiles, [], ... 'target', 5, ... % Recordings time series 'modality', 1, ... % MEG (All) 'orient', 4, ... % bottom 'time', 0.11, ... 'contact_time', [0, 0.1], ... 'contact_nimage', 12, ... 'threshold', 20, ... 'Comment', 'Run');
You will find one block per process you selected in the pipeline editor. They all have the same syntax:
cess('CallProcess', process_name, input_files_A, input_files_B, options_list);
process_name: String indicating the function corresponding to the process to execute. To know from the pipeline editor what is the path to the process function: hover your mouse over the selected process, as illustrated in this tutorial.
input_files_A: List of input files in Process1, or FilesA in Process2. It can be a cell array of file names (full path, or relative path from the protocol folder), or an array of structures describing the files in the database (returned by a previous call to bst_process).
input_files_B: Empty for Process1, or FilesB in Process2. Cell array of strings, or array of struct.
options_list: Pairs of (option_name, option_values), one pair for each option of the process.
output_files: Array of structures describing the files in output of the process. If the process created new files, this variable points at them. If the process didn't create new files or was modifying exiting files, this variable points at the input files.
by line: Footer class="line867">
% Save and display report -4">ReportFile = bst_report('Save', sFiles);
Closes the current report and saves it in the user report folder ($HOME/.brainstorm/reports). These reports are in .mat format and contain all the information necessary to re-run the execution exactly in the same way, but they are not easy to read.
The parameter "sFiles" is optional, it indicates what are the files that are considered as the final results of the script. You can remove it without breaking your script: ReportFile = bst_report('Save');
bst_report('Open', ReportFile);
Opens the report viewer to display what happened during the execution. This is equivalent to using the menu File > Report viewer. You can comment this line (ie. add a "%" at the beginning of the line) if you don't want to show the report at the end of the execution.
% bst_report('Export', ReportFile, ExportDir);
This function exports the report in readable format, as an HTML file that includes all the screen captures embedded in it. It is disabled by default. If you want to use this feature: remove the "%" at the beginning of the line, and define the variable ExportDir.
ExportDir must be a string that defines where to save the HTML report. It can be either the absolute path to a HTML file (eg. 'C:\Users\myuser\Documents\report_example.html') or just a folder (eg. 'C:\Users\myuser\Documents'). If you enter only a path to a folder, a default file name including the protocol name and a date tag is generated (report_ProtocolName_YYMMDD_HHMMSS.html).
the calls class="line862">The script you generated is like any Matlab script: you can edit it, rename the variables, add tests and loops, etc. The first important thing to understand is how to edit the options and change the inputs/outputs. The script generator uses only one variable for all the file lists (sFiles) and the output process is always the input of the following process. This is usually too restrictive to write a full analysis script: we commonly need to have multiple lists of files or to run two different operations on the same file.
Let's consider the first process call, which selects the averages for the Deviant condition in both runs.
sFiles = bst_process('CallProcess', 'process_select_files_data', sFiles, [], ... 'subjectname', SubjectNames{1}, ... 'condition', '', ... 'tag', 'Avg: deviant', ... 'includebad', 0, ... 'includeintra', 0, ... 'includecommon', 0);
There is no need to set the parameter sFiles, because there is no input, you can replace it with an empty matrix []. You can therefore remove the line "sFiles = [];". We can also rename the output variable "sAvgData", to be more specific.
sAvgData = bst_process('CallProcess', 'process_select_files_data', [], [], ...
You can omit all the options that are not defined, not used, or kept to their default values:
sAvgData = bst_process('CallProcess', 'process_select_files_data', [], [], ... 'subjectname', SubjectNames{1}, ... 'tag', 'Avg: deviant');
Edit the call to the low-pass filter: Change the input to sAvgData and the output to sAvgDataLow, this way you will be able to keep track of the two files if you need to use them independently later.
sAvgDataLow = bst_process('CallProcess', 'process_bandpass', sAvgData, [], ... 'sensortypes', 'MEG', ... 'highpass', 0, ... 'lowpass', 30, ... 'attenuation', 'strict'); % 60dB
Edit the call to the snapshot process: Change the input to sAvgDataLow, and remove the output parameter (we are not expecting any output file from it).
bst_process('CallProcess', 'process_snapshot', sAvgDataLow, [], ... 'target', 5, ... % Recordings time series 'modality', 1); % MEG (All)
Replace the last lines with the following code, in order to export the report instead of opening in the report viewer (edit the file path to point at your own user folder instead).
ReportFile = bst_report('Save'); -9">bst_report('Export', ReportFile, 'C:\Users\myuser\Documents\report_test.html');
in Matlab class="line862">Select the code for the first process in the Matlab editor, right-click > Evaluate selection (or press F9).

If you haven't executed your script yet, you will get the following error in the Matlab command window:
Undefined variable "SubjectNames" or class "SubjectNames".
The variable SubjectNames is not defined yet: Execute the first lines "SubjectNames = {'Subject01'}", then try again. You should now have a new variable in your Matlab workspace, which points at the two average files. Type "sAvgData(1)" in your command window to display the first element:
>> sAvgData(1) -10">ans = iStudy: 6 iItem: 1 FileName: '..._01_600Hz_notch/data_deviant_average_160513_1329.mat' FileType: 'data' Comment: 'Avg: deviant (39 files)' Condition: 'S01_AEF_20131218_01_600Hz_notch' SubjectFile: 'Subject01/brainstormsubject.mat' SubjectName: 'Subject01' DataFile: '' ChannelFile: 'Subject01/S01_AEF_20131218_01_600Hz_notch/channel_ctf_acc1.mat' ChannelTypes: {'ADC A' 'ADC V' 'DAC' 'ECG' 'EOG' 'MEG' 'MEG REF' ...}
The field "sAvgData(1).FileName" contains the relative path to the to the Deviant average in the first run. This structure sAvgData contains also a lot of information that can be helpful in your script:
iStudy / iItem: Reference of the file in the database (described later in this tutorial).
FileType: 'raw' (continuous files), 'data' (recordings), 'results' (sources), 'timefreq' (time-frequency, spectrum and connectivity), or 'matrix' (any time series extracted from other files).
Comment: Comment field of the file (what is displayed in the database explorer).
Condition: Name of the condition/folder in which the file is located.
SubjectFile: Relative path to the subject file (brainstormsubject.mat).
SubjectName: Name of the subject (must be the same as the folder name).
DataFile: For types 'results' or 'timefreq', path of the parent file in the database explorer.
ChannelFile: Relative path to the channel file.
ChannelTypes: Cell array of channel types available for the input file.
conventions class="line874">To help you navigate in the Brainstorm code, here are some naming conventions:
Structures: Name starting with a "s" followed by a capital letter (eg. sFiles, sStudy, sSubject).
Indices: Either loop variables or array indices, name starting with a "i" (eg. iSubject, iStudy, iTime).
Counts: Number of elements in a group, name starting with a "n" (eg. nAvg, nTrials, nSubjects).
Graphic handles: Matlab graphic objects, name starting with a "h" (eg. hFig, hAxes, hLine, hText).
File names: Scripts and functions, only lower case, separation with "_" (eg. process_fft, bst_get).
Sub-functions: Inside a .m file, name starting with a capital, CamelCase (eg. CallProcess, Start).
the script class="line874">The simplified script looks like this:
% Input files -11">SubjectNames = {'Subject01'}; Start a new report -6">bst_report('Start'); -5"> Process: Select data files in: Subject01/*/Avg: deviant -4">sAvgData = bst_process('CallProcess', 'process_select_files_data', [], [], ... 'subjectname', SubjectNames{1}, ... 'tag', 'Avg: deviant'); Process: Low-pass:30Hz 1-3">sAvgDataLow = bst_process('CallProcess', 'process_bandpass', sAvgData, [], ... 'sensortypes', 'MEG', ... 'highpass', 0, ... 'lowpass', 30, ... 'attenuation', 'strict'); % 60dB Process: Snapshot: Recordings time series 7-2">bst_process('CallProcess', 'process_snapshot', sAvgDataLow, [], ... 'target', 5, ... % Recordings time series 'modality', 1); % MEG (All) 0-2"> Save and display report 2-2">ReportFile = bst_report('Save'); 3-2">bst_report('Export', ReportFile, 'C:\Users\franc\Documents\report_test.html');
You have three ways to execute it:
Select all the lines (Ctrl+A) and evaluate it in Matlab (F9).
In the Editor toolbar of the Matlab environment, click on the button [Run].
Save the file, go to this folder with Matlab (or add it to your path) and type the name of the script in the command window (without the ".m" at the end).
At the end of the execution, nothing happens, because we indicated we wanted to export the report instead of opening it. To check out the report of execution: use the menu File > Report viewer from the Brainstorm window, or open the file report_test.html that was saved somewhere on your computer.
In this page, you can review everything that happened in the script: when it was executed, how long it took, what are the processes that were executed, some additional messages (two files were selected with the first process) and the screen captures taken by process_snapshot.

the script again class="line862">If you execute the script again, it will not behave as expected anymore. The selection process we used assumes that there is only one file per folder with a comment that includes "Avg: deviant". This is not the case anymore after the execution, because the low-pass filtered files also contain the same string. The execution of the first process of the script now returns 4 files.
>> sAvgData = bst_process('CallProcess', 'process_select_files_data', [], [], ... 'subjectname', SubjectNames{1}, ... 'tag', 'Avg: deviant') -7"> -6">sAvgData = -5">1x4 struct array with fields: iStudy iItem ...
In order to exclude the low-pass filtered files from this selection, you can add another process that will refine the selection. Use the script generator again to create a template call for another process, then copy-paste it in your script.
In Process1: Select any recordings file (we will not run anything, just generate a script).
Select process File > Select files: By tag: Search="low", Search the comment, Ignore the files.
class="attachment" height="252" src="/brainstorm/Tutorials/Scripting?action=AttachFile&do=get&target=select_tag.gif" title="select_tag.gif" width="261" />
Select the menu Generate .m script (make sure you do not overwrite the script you are currently working on), then close the pipeline editor.
Copy-paste and edit the call to process_select_tag to your main script.
Now the file selection part of your script should look like this, and should return only two files:
% Process: Select data files in: Subject01/*/Avg: Deviant -13">sAvgData = bst_process('CallProcess', 'process_select_files_data', [], [], ... 'subjectname', SubjectNames{1}, ... 'tag', 'Avg: deviant'); Process: Ignore file comments with tag: low -6">sAvgData = bst_process('CallProcess', 'process_select_tag', sAvgData, [], ... 'tag', 'low', ... 'search', 2, ... % Search the file comments 'select', 2); % Ignore the files with the tag
With this last modification, your script is more robust. It can be executed multiple times without completely changing its behavior. When you are fetching files from the database using comment tags or file names, always pay attention to this aspect: the database grows and the further you go, the more specific your requests have to be.
A good practice can be to tag explicitly the output files your script generates if you need to fetch them later. You can use the process File > Add tag and File > Set comment.

Brainstorm class="line874">Brainstorm must be running in the background for these scripts to run properly. The interface doesn't have to be visible on the screen, but the database engine must be running for processing requests. At the beginning of your script, you can explicitly start or restart Brainstorm.
brainstorm: Start Brainstorm with the regular GUI.
brainstorm nogui: Start in silent mode. The Java GUI is created but hidden, the progress bar is not shown, all the processes run without user interactions, using default options instead of asking interactively. Visualization figures opened in the processing scripts are still created and made visible.
brainstorm server: Start in headless mode, for execution on a distant computation server that does not have any graphical capability or display attached to it. In this mode, none of the Java GUI elements are created, and the Matlab figures are not displayed. Whether you would be able to add screen captures to your execution reports depends mostly on the Matlab version available of your server (see section below Running scripts on a cluster).
brainstorm <script.m> <parameters>: Start Brainstorm in server mode, execute a script and quit Brainstorm. This allows executing any Matlab or Brainstorm script from the command line. This works also from the compiled version of Brainstorm, add the full path to the script to execute and the script parameters to the start script:
<script.m> or brainstorm3.command <script.m>.
If you want to start Brainstorm only if it is not already running, you can use the following code:
if ~brainstorm('status') brainstorm nogui -11">end
To select a specific protocol at the beginning of your script:
ProtocolName = 'TutorialIntroduction'; Get the protocol index -12">iProtocol = bst_get('Protocol', ProtocolName); isempty(iProtocol) error(['Unknown protocol: ' ProtocolName]); -7">end Select the current procotol -6">gui_brainstorm('SetCurrentProtocol', iProtocol);
To delete the protocol and start over:
% Delete existing protocol -16">gui_brainstorm('DeleteProtocol', ProtocolName); Create new protocol -10">gui_brainstorm('CreateProtocol', ProtocolName, 0, 0);
Additional command line options:
brainstorm stop % Quit Brainstorm -17">brainstorm update % Download and install latest Brainstorm update (see bst_update) -14">brainstorm reset % Re-initialize Brainstorm database and preferences -11">brainstorm digitize % Digitize electrodes positions and head shape using a Polhemus -9">brainstorm setpath % Add Brainstorm subdirectories to current path -8">brainstorm info % Open Brainstorm website -8">brainstorm forum % Open Brainstorm forum -7">brainstorm license % Display license
requests class="line862">The functions bst_get and bst_set allow you to query the database, access the configuration of the software and modify some display parameters. The complete reference documentation of these functions is included directly in their code (brainstorm3/toolbox/core/bst_get.m and bst_set.m).
Let's start with a few simple examples:
>> ProtocolInfo = bst_get('ProtocolInfo') % Configuration of the current protocol -18">ProtocolInfo = Comment: 'TutorialIntroduction' STUDIES: 'C:\Work\Protocols\TutorialIntroduction\data' SUBJECTS: 'C:\Work\Protocols\TutorialIntroduction\anat' iStudy: 6 UseDefaultAnat: 0 UseDefaultChannel: 0 -6"> 0-4">>> isGUI = bst_get('isGUI') % Is the Brainstorm interface displayed (0=no, 1=yes) 1-4"> 2-4">>> bst_set('FlipYAxis', 1) % New figures will have the Y axis flipped 3-4">>> bst_set('TSDisplayMode', 'butterfly') % New figures will use a "butterfly" view 4-3">>> bst_set('FieldTripDir', FieldTripDir) % Set path to the FieldTrip toolbox
To reference the files in the database, each protocol is subdivided in Subjects (the "anat" folder, containing the MRI, surfaces and atlases) and Studies (the "data" folder, including the recordings, channel files and all the analyses). Each Study corresponds to a sub-folder (eg. protocol/data/subject01/run01/), and is attached to only one subject.
Subjects and Studies are referenced in the protocol with a unique index, most of the time kept in variables named iSubject and iStudy. The files available in them are also referenced with indices, with variables such as iAnatomy, iSurface, iData, iHeadModel, iResults or iTimefreq. You can see the indices in the database explorer by hovering your mouse over the nodes files and folders:

Example: Getting the study structure from the variable sAvgData, defined in the script:
>> sAvgData(1) -19">ans = iStudy: 6 iItem: 1 ... -10"> -10">>> sStudy = bst_get('Study', sAvgData(1).iStudy) % Get study struct with its index -9">sStudy = Name: 'S01_AEF_20131218_01_600Hz_notch' FileName: 'Subject01/S01_AEF_20131218_01_600Hz_notch/brainstormstudy.mat' DateOfStudy: '13-May-2016' BrainStormSubject: 'Subject01/brainstormsubject.mat' % Subject filename Condition: {'S01_AEF_20131218_01_600Hz_notch'} % Name of the folder Channel: [1x1 struct] % Channel file iChannel: [] % Not used anymore Data: [1x242 struct] % List of "data" files in the folder HeadModel: [1x1 struct] % List of head models in the folder iHeadModel: 1 % Default head model (file in green) Result: [1x244 struct] % List of source files and links Stat: [1x0 struct] % List of statistical results Image: [0x0 struct] % List of images NoiseCov: [1x2 struct] % Noise(1) and data(2) covariance files Dipoles: [0x0 struct] % List of dipole files in the folder Timefreq: [1x247 struct] % List of time-frequency files Matrix: [0x0 struct] % List of "matrix" files in the folder
Example: Getting the data structure.
% Get the structure representing the file from sStudy -20">>> sData = sStudy.Data(sAvgData(1).iItem) -17">sData = FileName: '..._01_600Hz_notch/data_deviant_average_160513_1329.mat' Comment: 'Avg: deviant (39 files)' % File comment DataType: 'recordings' % Type of data in the file BadTrial: 0 % If 1, the trial is marked as bad
Example: Getting the subject structure.
% Get subject structure from filename (lists the files in the subject folder) -21">>> sSubject = bst_get('Subject', sStudy.BrainStormSubject) -18">sSubject = Name: 'Subject01' % Subject name, same as folder name Comments: '' % Not used much FileName: 'Subject01/brainstormsubject.mat' DateOfAcquisition: '' % Not used anymore Anatomy: [1x1 struct] % List of MRI volumes Surface: [1x9 struct] % List of surfaces iAnatomy: 1 % Index of default MRI iScalp: 9 % Index of default head surface iCortex: 4 % Index of default cortex surface iInnerSkull: [] % Index of default inner skull surface iOuterSkull: [] % Index of default outer skull surface iOther: [] % Not used anymore UseDefaultAnat: 0 % If 1: Use the default anatomy UseDefaultChannel: 0 % 0=one/folder, 1=one/subject, 2=one global
Example: Getting the study structure and data index from a file name.
>> DataFile = sAvgData(1).FileName -22">DataFile = -19">Subject01/..._01_600Hz_notch/data_deviant_average_160513_1329.mat -16"> -14">>> [sStudy, iStudy, iData] = bst_get('DataFile', DataFile) -13">sStudy = Name: 'S01_AEF_20131218_01_600Hz_notch' FileName: '..._01_600Hz_notch/brainstormstudy.mat' DateOfStudy: '13-May-2016' BrainStormSubject: 'Subject01/brainstormsubject.mat' Condition: {'S01_AEF_20131218_01_600Hz_notch'} Channel: [1x1 struct] iChannel: [] Data: [1x242 struct] HeadModel: [1x1 struct] iHeadModel: 1 Result: [1x244 struct] Stat: [1x0 struct] Image: [0x0 struct] NoiseCov: [1x2 struct] Dipoles: [0x0 struct] Timefreq: [1x247 struct] Matrix: [0x0 struct] 4-3">iStudy = 6 6-2">iData = 1
Many other options are available for searching files in the database with bst_get. We cannot list them all in this page, but you can refer to the code of bst_get.m for more information.
1 function [argout1, argout2, argout3, argout4, argout5] = bst_get( varargin ) % BST_GET: Get a Brainstorm structure. % This function is used to abstract the way that these structures are stored. % % USAGE : % ====== DIRECTORIES ================================================================== % - bst_get('UserDir') : User home directory % - bst_get('BrainstormHomeDir') : Application directory of brainstorm % - bst_get('BrainstormUserDir') : User home directory for brainstorm (<home>/.brainstorm/) % - bst_get('BrainstormTmpDir') : User brainstorm temporary directory (Default: <home>/.brainstorm/tmp/) % - bst_get('BrainstormTmpDir', isForcedDefault=0, SubDir=[]) : User DEFAULT brainstorm temporary directory (<home>/.brainstorm/tmp/SubDir) % - bst_get('BrainstormDocDir') : Doc folder folder of the Brainstorm distribution (may vary in compiled versions) % - bst_get('BrainstormDefaultsDir') : Defaults folder of the Brainstorm distribution (may vary in compiled versions) % - bst_get('UserReportsDir') : User reports directory (<home>/.brainstorm/reports/) % - bst_get('UserMexDir') : User temporary directory (<home>/.brainstorm/mex/) % - bst_get('UserProcessDir') : User custom processes directory (<home>/.brainstorm/process/) % - bst_get('UserDefaultsDir') : User defaults directory (<home>/.brainstorm/defaults/) % - bst_get('UserPluginsDir') : User plugins directory (brainstorm3/plugins/ if it exists, otherwise <home>/.brainstorm/plugins/) % - bst_get('BrainstormDbFile') : User brainstorm.mat file (<home>/.brainstorm/brainstorm.mat) % - bst_get('BrainstormDbDir') : User database directory (contains all the brainstorm protocols) % - bst_get('DirDefaultSubject') : Directory name of the default subject % - bst_get('DirDefaultStudy') : Directory name of the default study for each subject % - bst_get('DirAnalysisInter') : Directory name of the inter-subject analysis study % - bst_get('DirAnalysisIntra') : Directory name of the intra-subject analysis study (for each subject) % - bst_get('AnatomyDefaults') : Get the contents of directory bstDir/defaults/anatomy % - bst_get('MniAtlasDefaults') : Get the contents of directory bstDir/defaults/mniatlas % - bst_get('EegDefaults') : Get the contents of directory bstDir/defaults/eeg % - bst_get('LastUsedDirs') : Structure with all the last used directories (last used) % - bst_get('OsType', isMatlab=1) : Get a string that describes the operating system (if isMatlab=1 return the Matlab/JVM platform, else return the real host system) % - bst_get('FileFilters', DataType) : Get the list of import filters for a specific data type % - bst_get('PluginCustomPath') : Full custom path to all plugins % - bst_get('BrainSuiteDir') : Full path to a local installation of BrainSuite % - bst_get('SpmTpmAtlas') : Full path to the SPM atlas TPM.nii % - bst_get('PythonExe') : Path to the python executable % % ====== PROTOCOLS ==================================================================== % - bst_get('iProtocol') : Indice of current protocol % - bst_get('Protocol', ProtocolName): Return the indice of the protocol ProtocolName, or [] if it doesn't exist % - bst_get('ProtocolInfo') : Definition structure for current protocol % - bst_get('ProtocolSubjects') : Subjects list for current protocol % - bst_get('ProtocolStudies') : Studies list for current protocol % - bst_get('isProtocolLoaded') : 1 if the protocol has been loaded, 0 else % - bst_get('isProtocolModified') : 1 if the protocol has been modified, 0 else % % ====== STUDIES ====================================================================== % - bst_get('Study', StudyFileName) : Get one study in current protocol with its file name % - bst_get('Study', iStudies) : Get one or more studies % - bst_get('Study') : Get current study in current protocol % - bst_get('StudyCount') : Get number of studies in the current protocol % - bst_get('StudyWithSubject', SubjectFile) : Find studies associated with a given subject file (WITHOUT the system studies ('intra_subject', 'default_study')) % - bst_get('StudyWithSubject', ..., 'intra_subject') : Find studies ... INCLUDING 'intra_subject' study % - bst_get('StudyWithSubject', ..., 'default_study') : Find studies ... INCLUDING 'default_study' study % - bst_get('StudyWithCondition', ConditionPath) : Find studies for a given condition path % - bst_get('ChannelStudiesWithSubject', iSubjects) : Get all the studies where there should be a channel file for a list of subjects % - bst_get('AnalysisIntraStudy', iSubject) : Get the default analysis study for target subject % - bst_get('AnalysisInterStudy') : Get the default analysis study for inter-subject analysis % - bst_get('DefaultStudy', iSubject) : Get the default study for target subject (by subject indice) % - bst_get('DefaultStudy') : Get the global default study (common to all subjects) % - bst_get('DefaultStudy', SubjectFile) : Get the default study for target subject (by filename) % - bst_get('ChannelFile', ChannelFile) : Find a channel file in current protocol % - bst_get('ChannelFileForStudy', StudyFile/DataFile) : Find a channel file in current protocol % - bst_get('ChannelForStudy', iStudies) : Return current Channel struct for target study % - bst_get('ChannelModalities', ChannelFile) : Return displayable modalities for a Channel file % - bst_get('ChannelModalities', DataFile) : Return displayable modalities for a Data/Results/Timefreq... file % - bst_get('ChannelDevice', ChannelFile) : Return acquisistion device for a channel file % - bst_get('TimefreqDisplayModalities', TfFile) : Get displayable modalities for a TF file based on recordings % - bst_get('HeadModelForStudy', iStudy) : Return current HeadModel struct for target study % - bst_get('HeadModelFile', HeadModelFile) : Find a HeadModel file in current protocol % - bst_get('HeadModelFile', HeadModelFile, iStudies): Find a HeadModel file in current protocol % - bst_get('NoiseCovFile', NoiseCovFile) : Find a noise covariance file file in current protocol % - bst_get('NoiseCovFile', NoiseCovFile, iStudies) : Find a noise covariance file in current protocol % - bst_get('NoiseCovFile', DataCovFile) : Find a data covariance file file in current protocol % - bst_get('NoiseCovFile', DataCovFile, iStudies) : Find a data covariance file file in current protocol % - bst_get('DataFile', DataFile) : Find a DataFile in current protocol % - bst_get('DataFile', DataFile, iStudies) : Find a DataFile in current protocol % - bst_get('DataForDataList', iStudy, DataListName) : Find all the DataFiles grouped by a data list % - bst_get('DataForStudy', iStudy) : Find all the Data files that are dependent on the channel/headmodel of a given study % - bst_get('DataForStudies', iStudies) % - bst_get('DataForChannelFile', ChannelFile) : Find all the DataFiles that use the given ChannelFile % - bst_get('ResultsFile', ResultsFile) : Find a ResultsFile in current protocol % - bst_get('ResultsFile', ResultsFile, iStudies) : Find a ResultsFile in input studies % - bst_get('ResultsForDataFile', DataFile, iStudies): Find all results computed based on DataFile % - bst_get('StatFile', StatFile) : Find a StatFile in current protocol % - bst_get('StatFile', StatFile, iStudies) : Find a StatFile in input studies % - bst_get('StatForDataFile', DataFile, iStudies) % - bst_get('StatForDataFile', DataFile) % - bst_get('TimefreqFile', TimefreqFile) % - bst_get('TimefreqFile', TimefreqFile, iStudies) % - bst_get('TimefreqForFile', FileName, iStudies) : Find all timefreq files computed based on target file % - bst_get('TimefreqForKernel', KernelFile) % - bst_get('DipolesFile', DipolesFile) % - bst_get('DipolesFile', DipolesFile, iStudies) % - bst_get('DipolesForFile', FileName, iStudies) : Find all dipoles files computed based on target file % - bst_get('DipolesForKernel', KernelFile) % - bst_get('MatrixFile', MatrixFile) % - bst_get('MatrixFile', MatrixFile, iStudies) % - bst_get('MatrixForMatrixList', iStudy, MatrixListName) % - bst_get('AnyFile', AnyFile) % - bst_get('AnyFile', AnyFile, iStudies) % - bst_get('RelatedDataFile', FileName) % - bst_get('RelatedDataFile', FileName, iStudies) % - bst_get('GetFilenames') % % ====== SUBJECTS ====================================================================== % - bst_get('Subject', SubjectFileName, isRaw) : Find a subject in current protocol with its file name % - bst_get('Subject', SubjectName, isRaw) : Find a subject in current protocol with its name % - bst_get('Subject', iSubject) : Get a subject (normal or default if iSubject==0) % - bst_get('Subject') : Get current subject in current protocol % - bst_get('SubjectCount') : Get number of studies in the current protocol % - bst_get('NormalizedSubjectName') : Name of the subject with a normalized anatomy % - bst_get('NormalizedSubject') : Get group analysis subject for the current protocol % - bst_get('ConditionsForSubject', SubjectFile) : Find all conditions for a given subject % - bst_get('SurfaceFile', SurfaceFile) : Find a surface in current protocol % - bst_get('SurfaceFileByType', iSubject, SurfaceType) : Find surfaces with given type for subject #i (default only) % - bst_get('SurfaceFileByType', SubjectFile, SurfaceType) : Find surfaces with given type for subject SubjectFile (default only) % - bst_get('SurfaceFileByType', SurfaceName, SurfaceType) : Find surfaces with given type for subject that also has surface SurfaceName (default only) % - bst_get('SurfaceFileByType', MriName, SurfaceType) : Find surfaces with given type for subject that also has MRI MriName (default only) % - bst_get('SurfaceFileByType', ..., ..., isDefaultOnly) : If 0, return all the surfaces of the given type, instead of only the default surface % - bst_get('MriFile', MriFile) : Find a MRI in current protocol % % ====== GUI ================================================================= % - bst_get('BstControls') : Return main Brainstorm GUI structure % - bst_get('BstFrame') : Return main Brainstorm JFrame % - bst_get('isGUI') : Return 1 if the Brainstorm interface is displayed % - bst_get('GuiLevel') : Return GUI level: -1=server, 0=nogui, 1=normal, 2=autopilot % - bst_get('ScreenDef') : Get screens configuration % - bst_get('DecorationSize') : Get dimensions of the windows decorations % - bst_get('Layout') : Configuration of the main Brainstorm window % - bst_get('Layout', prop) : Get one property in the layout properties % - bst_get('PanelContainer') : Display list of registered panel containers % - bst_get('PanelContainer', ContainerName) : Get a panel container handle % - bst_get('Panel') : Display list of registered panels % - bst_get('Panel', PanelName) : Find a panel with its name % - bst_get('PanelControls', PanelName) : Get the controls of a panel % - bst_get('Clipboard') : Nodes that were copied from the interface % - bst_get('FigFont') : Standard font size displayed in the figures % - bst_get('Font') : Create a Java font, scaled for the operating system % % ====== CONFIGURATION ================================================================= % - bst_get('Version') : Brainstorm version % - bst_get('MatlabVersion') : Matlab version (version number * 100, eg. 801) % - bst_get('MatlabReleaseName') : Matlab version (release name, eg. "R2014a") % - bst_get('JavaVersion') : Java version % - bst_get('isJavacomponent') : Returns 1 if javacomponent is available (Matlab < 2019b), 0 otherwise % - bst_get('SystemMemory') : Amount of Total and Available physical memory (RAM), in MiB % - bst_get('ByteOrder') : {'l','b'} - Byte order used to read and save binary files % - bst_get('TSDisplayMode') : {'butterfly','column'} % - bst_get('ElectrodeConfig', Modality) : Structure describing the display values for SEEG/ECOG/EEG contacts % - bst_get('ElecInterpDist', Modality) : Structure describing the maximum distance for interpolating SEEG/ECOG/EEG values onto a surface % - bst_get('AutoUpdates') : {0,1} - If 1, check automatically for updates at startup % - bst_get('ForceMatCompression') : {0,1} - If 1, always save mat-files using the v7 format instead of v6 % - bst_get('IgnoreMemoryWarnings') : {0,1} - If 1, do not display memory warnings at the Brainstorm startup % - bst_get('ExpertMode') : {0,1} - If 1, show advanced options that regular user do not see % - bst_get('DisplayGFP') : {0,1} - If 1, the GFP is displayed on all the time series figures % - bst_get('DownsampleTimeSeries') : {0,1,...} - If > 0, downsample dense time series for faster display % - bst_get('DisableOpenGL') : {0,1,2} - If 1, do not use OpenGL renderer; if 2, use software OpenGL % - bst_get('InterfaceScaling') : {100,125,150,...} - Scales the Brainstorm GUI by a fixed factor % - bst_get('GraphicsSmoothing') : {0,1} - If 1, uses the graphics smoothing (Matlab >= 2014b) % - bst_get('SystemCopy') : {0,1} - If 1, uses the system calls mv/cp instead of movefile/copyfile (Linux only) % - bst_get('DefaultFormats') : Default formats for importing/exporting data, channels, ... (last used) % - bst_get('BFSProperties') : Conductivities and thicknesses for 3-shell spherical forward model % - bst_get('ImportDataOptions') : Import options for recordings % - bst_get('ImportEegRawOptions') : Importation options for RAW EEG format % - bst_get('BugReportOptions') : Bug reporter options % - bst_get('DefaultSurfaceDisplay') : Default display options for surfaces (smooth, data threshold, sulci map) % - bst_get('MagneticExtrapOptions') : Structure with the options for magnetic field extrapolation % - bst_get('DefaultFreqBands') % - bst_get('TimefreqOptions_morlet') % - bst_get('TimefreqOptions_fft') % - bst_get('TimefreqOptions_psd') % - bst_get('TimefreqOptions_hilbert') % - bst_get('OpenMEEGOptions') % - bst_get('DuneuroOptions') % - bst_get('GridOptions_headmodel') % - bst_get('GridOptions_dipfit') % - bst_get('UniformizeTimeSeriesScales') : {0,1} - If 1, the Y-axis of all the time series figures have the scale % - bst_get('FlipYAxis') : {0,1} - If 1, the recordings are displayed with the negative values UP % - bst_get('AutoScaleY') : {0,1} - If 1, the axis limits are updated when the figure is updated % - bst_get('ShowXGrid') : {0,1} - If 1, show the XGrid in the time series figures % - bst_get('ShowYGrid') : {0,1} - If 1, show the YGrid in the time series figures % - bst_get('ShowZeroLines') : {0,1} - If 1, show the Y=0 lines in the columns view % - bst_get('ShowEventsMode') : {'dot','line','none'} % - bst_get('Resolution') : [resX,resY] fixed resolutions for X and Y axes % - bst_get('FixedScaleY', Modality) : Struct with the scales to impose on the recordings for the selected modality % - bst_get('XScale', XScale) : {'log', 'linear'} % - bst_get('YScale', YScale) : {'log', 'linear'} % - bst_get('UseSigProcToolbox') : Use Matlab's Signal Processing Toolbox when available % - bst_get('RawViewerOptions', sFile) : Display options for RAW recordings, adapt for specific file % - bst_get('RawViewerOptions') : Display options for RAW recordings % - bst_get('TopoLayoutOptions') : Display options for 2DLayout display % - bst_get('StatThreshOptions') : Options for online statistical thresholding % - bst_get('ContactSheetOptions') : Display options for contact sheets % - bst_get('ProcessOptions') : Options related with the data processing % - bst_get('CustomColormaps') : Gets the list of user defined colormaps % - bst_get('MriOptions') : Configuration for MRI display % - bst_get('DigitizeOptions') : Digitizer options % - bst_get('PcaOptions') : Options for PCA dimension reduction (xyz flattening or scout function) % - bst_get('ReadOnly') : Read only interface % - bst_get('NodelistOptions') : Structure with the options for file selection in the Process1 and Process2 panels % - bst_get('ResizeFunction') : Get the appropriate resize function % - bst_get('groot') : Get the root graphic object % - bst_get('JFrame', hFig) : Get the underlying java frame for a Matlab figure % - bst_get('LastPsdDisplayFunction') : Display option of measure for spectrum (log, power, magnitude, etc.) % - bst_get('PlotlyCredentials') : Get the credentials and URL to connect to plot.ly server % - bst_get('ExportBidsOptions') : Additional metadata for BIDS export % - bst_get('Pipelines') : Saved Pipelines stored % % SEE ALSO bst_set % @============================================================================= % This function is part of the Brainstorm software: % https://neuroimage.usc.edu/brainstorm % % Copyright (c) University of Southern California & McGill University % This software is distributed under the terms of the GNU General Public License % as published by the Free Software Foundation. Further details on the GPLv3 % license can be found at http://www.gnu.org/copyleft/gpl.html. % % FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE % UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY % WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF % MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY % LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE. % % For more information type "brainstorm license" at command prompt. % =============================================================================@ % % Authors: Francois Tadel, 2008-2023 % Martin Cousineau, 2017 % Raymundo Cassani, 2021-2023 %% ==== PARSE INPUTS ==== global GlobalData; if ((nargin >= 1) && ischar(varargin{1})) contextName = varargin{1}; return % Initialize returned variable argout1 = []; argout2 = []; argout3 = []; argout4 = []; argout5 = []; % Get required context structure switch contextName %% ==== SUBFUNCTIONS ===== case 'findFileInStudies' [argout1, argout2, argout3] = findFileInStudies(varargin{2:end}); %% ==== BRAINSTORM CONFIGURATION ==== case 'Version' argout1 = GlobalData.Program.Version; case 'MatlabVersion' if ~exist('version','builtin') Version = 601; else % Get version number str_vers = version(); vers = sscanf(str_vers, '%d.%d%*s'); if isempty(vers) || any(~isnumeric(vers)) || any(isnan(vers)) vers = 0; end Version = 100 * vers(1) + vers(2); % Get release name ipar = [find(str_vers == '('), find(str_vers == ')')]; end argout1 = Version; case 'MatlabReleaseName' if ~exist('version','builtin') Release = 'Matlab6'; else % Get version number str_vers = version(); % Get release name ipar = [find(str_vers == '('), find(str_vers == ')')]; Release = str_vers(ipar(1)+1:ipar(2)-1); end argout1 = Release; case 'JavaVersion' strver = char(java.lang.System.getProperty('java.version')); iDot = find(strver == '.'); if (length(iDot) < 2) argout1 = str2num(strver); else argout1 = str2num(strver(1:iDot(2)-1)); end case 'isJavacomponent' % After Matlab 2019b, javacomponent() and JavaFrame property have been deprecated argout1 = (bst_get('MatlabVersion') <= 906); case 'SystemMemory' % [RamTotal_MiB, RamAvailable_MiB] = bst_get('SystemMemory') RamTotal_MiB = []; RamAvailable_MiB = []; tmp = regexp(bst_get('OsType'), '^[a-z]+', 'match', 'ignorecase'); if ~isempty(tmp) osFamily = tmp{1}; end if strcmpi(osFamily, 'win') && (bst_get('MatlabVersion') >= 706) try % Get memory info [usermem, systemmem] = memory(); RamTotal_MiB = round(systemmem.PhysicalMemory.Total / 1024 / 1024); RamAvailable_MiB = round(usermem.MemAvailableAllArrays / 1024 / 1024); catch % Whatever... end elseif strcmpi(osFamily, 'linux') try meminfoRes = fileread('/proc/meminfo'); ramTotalkB = regexp(meminfoRes, '(?<=MemTotal:)(.*?)(?=kB)', 'match'); ramAvailablekB = regexp(meminfoRes, '(?<=MemAvailable:)(.*?)(?=kB)', 'match'); if ~isempty(ramAvailablekB) && ~isempty(ramTotalkB) ramTotalkB = str2double(strtrim(ramTotalkB{1})); RamTotal_MiB = round(ramTotalkB /1024); ramAvailablekB = str2double(strtrim(ramAvailablekB{1})); RamAvailable_MiB = round(ramAvailablekB /1024); end catch % Whatever... end elseif strcmpi(osFamily, 'mac') try [~, mem_pressure] = system('memory_pressure'); if ~isempty(mem_pressure) ramTotalB = regexp(mem_pressure, '(?<=The system has)(.*?)(?= )', 'match'); prcFree = regexp(mem_pressure, '(?<=System-wide memory free percentage:)(.*?)(?=%)', 'match'); if ~isempty(ramTotalB) && ~isempty(prcFree) ramTotalB = str2double(ramTotalB{1}); RamTotal_MiB = round(ramTotalB / 1024 / 1024); ramAvailableB = ramTotalB * str2double(prcFree{1}) / 100; RamAvailable_MiB = round(ramAvailableB / 1024 / 1024); end end catch % Whatever... end end argout1 = RamTotal_MiB; argout2 = RamAvailable_MiB; case 'BrainstormHomeDir' argout1 = GlobalData.Program.BrainstormHomeDir; case 'BrainstormDbDir' argout1 = GlobalData.DataBase.BrainstormDbDir; case 'UserDir' try if ispc userDir = getenv('USERPROFILE'); else userDir = char(java.lang.System.getProperty('user.home')); end catch userDir = ''; end if isempty(userDir) userDir = bst_get('BrainstormHomeDir'); end argout1 = userDir; case 'BrainstormUserDir' bstUserDir = bst_fullfile(bst_get('UserDir'), '.brainstorm'); if ~isdir(bstUserDir) res = mkdir(bstUserDir); if ~res error(['Cannot create Brainstorm user directory: "' bstUserDir '".']); end end argout1 = bstUserDir; case 'BrainstormTmpDir' tmpDir = ''; isForcedDefault = ((nargin >= 2) && ~isempty(varargin{2}) && varargin{2}); % Subdirectory if (nargin >= 3) && ~isempty(varargin{3}) SubDir = varargin{3}; % % Add PID of MATLAB process to the temporary folder % try % pid = feature('getpid'); % catch % pid = []; % end % if ~isempty(pid) % SubDir = sprintf('%s_%d', SubDir, feature('getpid')); % end % Add date+time of MATLAB process to the temporary folder c = clock; SubDir = sprintf('%s_%02.0f%02.0f%02.0f_%02.0f%02.0f%02.0f', SubDir, c(1)-2000, c(2:6)); else SubDir = []; end % Default folder: userdir/tmp defDir = bst_fullfile(bst_get('BrainstormUserDir'), 'tmp'); % If temporary directory is set in the preferences if ~isForcedDefault && isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'BrainstormTmpDir') tmpDir = GlobalData.Preferences.BrainstormTmpDir; end % Else: use directory userdir/tmp if isempty(tmpDir) tmpDir = defDir; end % Create directory if it does not exist yet if ~isdir(tmpDir) res = mkdir(tmpDir); if ~res && ~strcmp(tmpDir, defDir) disp(['BST> Cannot create Brainstorm temporary directory: "' tmpDir '".']); disp(['BST> Using default directory instead: "' defDir '".']); % Create temporary folder tmpDir = defDir; if ~isdir(tmpDir) res = mkdir(tmpDir); else res = 1; end end % Error: cannot create any temporary folder if ~res error(['Cannot create Brainstorm temporary directory: "' tmpDir '".']); end end % Add sub-directory if ~isempty(SubDir) tmpDir = bst_fullfile(tmpDir, SubDir); % Create directory if it does not exist yet if ~isdir(tmpDir) res = mkdir(tmpDir); if ~res error(['Cannot create Brainstorm temporary directory: "' tmpDir '".']); end end end argout1 = tmpDir; case 'BrainstormDocDir' docDir = bst_fullfile(GlobalData.Program.BrainstormHomeDir, 'doc'); if ~exist(docDir, 'file') % Matlab compiler >= 2018b stores 'doc' under 'bst_javabuil' docDir = bst_fullfile(GlobalData.Program.BrainstormHomeDir, 'bst_javabuil', 'doc'); if ~exist(docDir, 'file') docDir = ''; disp('BST> Could not find "doc" folder.'); disp(['BST> BrainstormHomeDir = ' GlobalData.Program.BrainstormHomeDir]); end end argout1 = docDir; case 'BrainstormDefaultsDir' defaultsDir = bst_fullfile(GlobalData.Program.BrainstormHomeDir, 'defaults'); if ~exist(defaultsDir, 'file') % Matlab compiler >= 2018b stores 'defaults' under 'bst_javabuil' defaultsDir = bst_fullfile(GlobalData.Program.BrainstormHomeDir, 'bst_javabuil', 'defaults'); if ~exist(defaultsDir, 'file') defaultsDir = ''; disp('BST> Could not find "defaults" folder.'); disp(['BST> BrainstormHomeDir = ' GlobalData.Program.BrainstormHomeDir]); end end argout1 = defaultsDir; case 'UserReportsDir' reportDir = bst_fullfile(bst_get('BrainstormUserDir'), 'reports'); if ~isdir(reportDir) res = mkdir(reportDir); if ~res error(['Cannot create user reports directory: "' reportDir '".']); end end argout1 = reportDir; case 'UserMexDir' mexDir = bst_fullfile(bst_get('BrainstormUserDir'), 'mex'); if ~isdir(mexDir) res = mkdir(mexDir); if ~res error(['Cannot create Brainstorm mex-files directory: "' mexDir '".']); end end argout1 = mexDir; case 'UserProcessDir' processDir = bst_fullfile(bst_get('BrainstormUserDir'), 'process'); if ~isdir(processDir) res = mkdir(processDir); if ~res error(['Cannot create Brainstorm custom processes directory: "' processDir '".']); end end argout1 = processDir; case 'UserDefaultsDir' defDir = bst_fullfile(bst_get('BrainstormUserDir'), 'defaults'); defDirAnat = bst_fullfile(defDir, 'anatomy'); defDirEeg = bst_fullfile(defDir, 'eeg'); if ~isdir(defDir) res = mkdir(defDir); if ~res error(['Cannot create user templates directory: "' defDir '".']); end end if ~isdir(defDirAnat) res = mkdir(defDirAnat); if ~res error(['Cannot create user templates directory: "' defDirAnat '".']); end end if ~isdir(defDirEeg) res = mkdir(defDirEeg); if ~res error(['Cannot create user templates directory: "' defDirEeg '".']); end end argout1 = defDir; case 'UserPluginsDir' % If brainstorm/plugins exists, use it (case of an environment exported and reused) pluginsDir = bst_fullfile(GlobalData.Program.BrainstormHomeDir, 'plugins'); % Otherwise (standard case): <home>/.brainstorm/plugins/ if ~exist(pluginsDir, 'file') pluginsDir = bst_fullfile(bst_get('BrainstormUserDir'), 'plugins'); if ~isdir(pluginsDir) res = mkdir(pluginsDir); if ~res error(['Cannot create plugins directory: "' pluginsDir '".']); end end end argout1 = pluginsDir; case 'BrainstormDbFile' argout1 = bst_fullfile(bst_get('BrainstormUserDir'), 'brainstorm.mat'); case 'Pipelines' argout1 = GlobalData.Processes.Pipelines; case 'OsType' switch (mexext) case 'mexglx', argout1 = 'linux32'; case 'mexa64', argout1 = 'linux64'; case 'mexmaci', argout1 = 'mac32'; case 'mexmaci64', argout1 = 'mac64'; case 'mexmaca64', argout1 = 'mac64arm'; case 'mexs64', argout1 = 'sol64'; case 'mexw32', argout1 = 'win32'; case 'mexw64', argout1 = 'win64'; otherwise, error('Unsupported extension.'); end % CALL: bst_get('OsType', isMatlab=0) if (nargin >= 2) && isequal(varargin{2}, 0) if strcmpi(argout1, 'win32') && (~isempty(strfind(java.lang.System.getProperty('java.home'), '(x86)')) || ~isempty(strfind(java.lang.System.getenv('ProgramFiles(x86)'), '(x86)'))) argout1 = 'win64'; end end case 'OsName' argout1 = ''; osFamily = []; tmp = regexp(bst_get('OsType'), '^[a-z]+', 'match', 'ignorecase'); if ~isempty(tmp) osFamily = tmp{1}; end switch osFamily case 'win' [~, system_info] = system('ver'); argout1 = strtrim(system_info); case 'linux' os_release = fileread('/etc/os-release'); osName = regexp(os_release, '(?<=PRETTY_NAME=")(.*?)(?=")', 'match'); if ~isempty(osName) osName = strtrim(osName{1}); else osName = regexp(os_release, '(?<=NAME=")(.*?)(?=")', 'match'); if ~isempty(osName) osName = strtrim(osName{1}); else osName = 'Linux unknow distribution'; end end [~, kernelVer] = system('uname -r'); kernelVer = strtrim(kernelVer); argout1 = [osName, ' (' kernelVer, ')']; case 'mac' [~, sw_vers] = system('sw_vers'); osName = regexp(sw_vers, '(?<=ProductName:)(.*?)(?=\n)', 'match'); osName = strtrim(osName{1}); osVer = regexp(sw_vers, '(?<=ProductVersion:)(.*?)(?=\n)', 'match'); osVer = strtrim(osVer{1}); [~, osHw] = system('uname -m'); osHw = strtrim(osHw); argout1 = [osName, ' ' osVer, ' (', osHw, ')']; end %% ==== PROTOCOL ==== case 'iProtocol' if isempty(GlobalData.DataBase.iProtocol) argout1 = 0; else argout1 = GlobalData.DataBase.iProtocol; end case 'Protocol' if ~isempty(GlobalData.DataBase.ProtocolInfo) argout1 = find(strcmpi({GlobalData.DataBase.ProtocolInfo.Comment}, varargin{2})); else argout1 = []; end case {'ProtocolInfo', 'ProtocolSubjects', 'ProtocolStudies', 'isProtocolLoaded', 'isProtocolModified'} argout2 = GlobalData.DataBase.iProtocol; % No protocol: return empty matrix if isempty(argout2) || ~isnumeric(argout2) || argout2 == 0 return; end % Check index integrity if ((argout2 <= 0) || (argout2 > length(GlobalData.DataBase.ProtocolInfo))), warning('Brainstorm:InvalidIndex', 'Invalid index'), return, end % Get requested protocol structure argout1 = GlobalData.DataBase.(contextName)(argout2); %% ==== STUDY ==== % Usage: [sStudy, iStudy] = bst_get('Study', StudyFileName) % [sStudy, iStudy] = bst_get('Study') % [sStudy, iStudy] = bst_get('Study', iStudies) case 'Study' if isempty(GlobalData.DataBase.iProtocol) || (GlobalData.DataBase.iProtocol == 0) return; end % Get list of current protocols ProtocolInfo = GlobalData.DataBase.ProtocolInfo(GlobalData.DataBase.iProtocol); ProtocolStudies = GlobalData.DataBase.ProtocolStudies(GlobalData.DataBase.iProtocol); % Get list of current protocol studies if isempty(ProtocolStudies) || isempty(ProtocolInfo) return; end % ===== PARSE INPUTS ===== if (nargin < 2) % Call: bst_get('Study'); iStudies = ProtocolInfo.iStudy; StudyFileName = []; elseif (isnumeric(varargin{2})) iStudies = varargin{2}; StudyFileName = []; elseif (ischar(varargin{2})) iStudies = []; StudyFileName = strrep(varargin{2}, ProtocolInfo.STUDIES, ''); end % Indices iAnalysisStudy = -2; % CANNOT USE -1 => DISABLES SEARCH FUNCTIONS iDefaultStudy = -3; % Indices > 0: normal studies indiced in ProtocolStudies.Study array % ===== GET STUDY BY INDEX ===== % Call: bst_get('Study', iStudies); if ~isempty(iStudies) argout1 = repmat(ProtocolStudies.DefaultStudy, 0); % Get analysis study iTargetAnalysis = find(iStudies == iAnalysisStudy); if ~isempty(iTargetAnalysis) argout1(iTargetAnalysis) = repmat(ProtocolStudies.AnalysisStudy, size(iTargetAnalysis)); argout2(iTargetAnalysis) = repmat(iAnalysisStudy, size(iTargetAnalysis)); end % Get default study iTargetDefault = find(iStudies == iDefaultStudy); if ~isempty(iTargetDefault) argout1(iTargetDefault) = repmat(ProtocolStudies.DefaultStudy, size(iTargetDefault)); argout2(iTargetDefault) = repmat(iDefaultStudy, size(iTargetDefault)); end % Get normal studies iTargetNormal = find((iStudies >= 1) & (iStudies <= length(ProtocolStudies.Study))); if ~isempty(iTargetNormal) argout1(iTargetNormal) = ProtocolStudies.Study(iStudies(iTargetNormal)); argout2(iTargetNormal) = iStudies(iTargetNormal); end % Error if isempty(argout1) GlobalData.DataBase.ProtocolInfo(GlobalData.DataBase.iProtocol).iStudy = []; end % ===== GET STUDY BY FILENAME ===== % Call: bst_get('Study', StudyFileName); elseif ~isempty(StudyFileName) % NORMAL STUDY iStudy = find(file_compare({ProtocolStudies.Study.FileName}, StudyFileName), 1); % If a study is found : return it if ~isempty(iStudy) argout1 = ProtocolStudies.Study(iStudy); argout2 = iStudy; % DEFAULT STUDY elseif ~isempty(ProtocolStudies.DefaultStudy) && file_compare({ProtocolStudies.DefaultStudy.FileName}, StudyFileName) argout1 = ProtocolStudies.DefaultStudy; argout2 = iDefaultStudy; % ANALYSIS STUDY elseif ~isempty(ProtocolStudies.AnalysisStudy) && file_compare({ProtocolStudies.AnalysisStudy.FileName}, StudyFileName) argout1 = ProtocolStudies.AnalysisStudy; argout2 = iAnalysisStudy; end else return end %% ==== STUDY WITH SUBJECT FILE ==== % Usage : [sStudies, iStudies] = bst_get('StudyWithSubject', SubjectFile) : WITHOUT the system studies ('intra_subject', 'default_study') % [sStudies, iStudies] = bst_get(..., 'intra_subject', 'default_study') : WITH the system studies: 'intra_subject' | 'default_study' case 'StudyWithSubject' % Parse inputs if (nargin < 2) || ~ischar(varargin{2}) error('Invalid call to bst_get()'); end if (nargin > 2) IntraStudies = any(strcmpi(varargin(3:end), 'intra_subject')); DefaultStudies = any(strcmpi(varargin(3:end), 'default_study')); else IntraStudies = 0; DefaultStudies = 0; end SubjectFile = {varargin{2}}; if isempty(GlobalData.DataBase.iProtocol) || (GlobalData.DataBase.iProtocol == 0) return; end % Get list of current protocol description ProtocolInfo = GlobalData.DataBase.ProtocolInfo(GlobalData.DataBase.iProtocol); ProtocolStudies = GlobalData.DataBase.ProtocolStudies(GlobalData.DataBase.iProtocol); if isempty(ProtocolStudies) || isempty(ProtocolInfo) return; end % Get default subject sDefaultSubject = bst_get('Subject', 0); % If SubjectFile is the default subject filename if ~isempty(sDefaultSubject) && ~isempty(sDefaultSubject.FileName) && file_compare( SubjectFile{1}, sDefaultSubject.FileName) % Get all the subjects files that use default anatomy ProtocolSubjects = GlobalData.DataBase.ProtocolSubjects(GlobalData.DataBase.iProtocol); iSubjectUseDefaultAnat = find([ProtocolSubjects.Subject.UseDefaultAnat]); if isempty(iSubjectUseDefaultAnat) return end SubjectFile = {ProtocolSubjects.Subject(iSubjectUseDefaultAnat).FileName}; % Also updates inter-subject node isInterSubject = 1; else isInterSubject = 0; end % Search all the current protocol's studies iStudies = []; for i=1:length(SubjectFile) iStudies = [iStudies, find(file_compare({ProtocolStudies.Study.BrainStormSubject}, SubjectFile{i}))]; end % Return results if ~isempty(iStudies) % Remove "analysis_intra" and "default_study" studies from list if ~IntraStudies iStudies(strcmpi({ProtocolStudies.Study(iStudies).Name}, bst_get('DirAnalysisIntra'))) = []; end if ~DefaultStudies iStudies(strcmpi({ProtocolStudies.Study(iStudies).Name}, bst_get('DirDefaultStudy'))) = []; end % Return studies argout1 = ProtocolStudies.Study(iStudies); argout2 = iStudies; else argout1 = repmat(db_template('Study'), 0); argout2 = []; end % Add inter-subject node, if needed if isInterSubject [sInterStudy, iInterStudy] = bst_get('AnalysisInterStudy'); argout1 = [argout1, sInterStudy]; argout2 = [argout2, iInterStudy]; end %% ==== STUDY WITH CONDITION PATH ==== % USAGE: [sStudies, iStudies] = bst_get('StudyWithCondition', ConditionPath) % % INPUT: ConditionPath % - 'SubjectName/conditionName' : Target condition for the specified subject % - 'SubjectName/@intra' : Intra-subject condition for the subject % - 'SubjectName/@default_study' : Default condition for the subject (where the subject's shared files are stored) % - '*/conditionName' : Target condition for all the subjects % - '@inter' : Inter-subject condition % - '@default_study' : Protocol's default condition (where the protocol's shared files are stored) case 'StudyWithCondition' % Parse inputs if (nargin ~= 2) || ~ischar(varargin{2}) error('Invalid call to bst_get()'); end ConditionPath = varargin{2}; % Get list of current protocol description ProtocolInfo = GlobalData.DataBase.ProtocolInfo(GlobalData.DataBase.iProtocol); ProtocolStudies = GlobalData.DataBase.ProtocolStudies(GlobalData.DataBase.iProtocol); if isempty(ProtocolStudies) || isempty(ProtocolInfo) return; end % ConditionPath = @inter if strcmpi(ConditionPath, '@inter') iStudy = -2; argout2 = iStudy; argout1 = bst_get('Study', iStudy); % ConditionPath = @default_study elseif strcmpi(ConditionPath, '@default_study') iStudy = -3; argout2 = iStudy; argout1 = bst_get('Study', iStudy); % ConditionPath = SubjectName/ConditionName else % Get subject and condition names condSplit = str_split(ConditionPath); if (length(condSplit) ~= 2) error('Invalid condition path.'); end SubjectName = condSplit{1}; ConditionName = condSplit{2}; % If first element is '*', search for condition in all the studies if (SubjectName(1) == '*') iStudies = 1:length(ProtocolStudies.Study); % Else : search for condition only in studies that are linked to the subject specified in the ConditionPath else % Get subject sSubject = bst_get('Subject', SubjectName, 1); if isempty(sSubject) return; end iStudies = find(file_compare({ProtocolStudies.Study.BrainStormSubject}, sSubject.FileName)); end % Nothing to search if isempty(iStudies) return end % Search all the current protocol's studies iStudies = iStudies(cellfun(@(c)isequal(ConditionName, c), [ProtocolStudies.Study(iStudies).Condition])); % Return results if ~isempty(iStudies) % Remove "analysis_intra" and "default_study" studies from list if ~strcmpi(ConditionName, '@intra') iStudies(strcmpi({ProtocolStudies.Study(iStudies).Condition}, bst_get('DirAnalysisIntra'))) = []; end if ~strcmpi(ConditionName, '@default_study') iStudies(strcmpi({ProtocolStudies.Study(iStudies).Condition}, bst_get('DirDefaultStudy'))) = []; end % Sort by subject if (length(iStudies) > 1) SubjNameList = cell(1,length(iStudies)); % For each study, get subject name for i = 1:length(iStudies) sSubject = bst_get('Subject', ProtocolStudies.Study(iStudies(i)).BrainStormSubject); SubjNameList{i} = sSubject.Name; end % Sort subjects names [sortSubjList, iSort] = sort(SubjNameList); % Apply same sorting to studies iStudies = iStudies(iSort); end % Return studies argout1 = ProtocolStudies.Study(iStudies); argout2 = iStudies; else argout1 = repmat(db_template('Study'), 0); argout2 = []; end end %% ==== CHANNEL STUDIES WITH SUBJECT ==== % Usage: iStudies = bst_get('ChannelStudiesWithSubject', iSubjects, 'NoIntra') case 'ChannelStudiesWithSubject' % Parse inputs if (nargin >= 2) && isnumeric(varargin{2}) iSubjects = varargin{2}; else error('Invalid call to bst_get()'); end if (nargin == 3) && strcmpi(varargin{3}, 'NoIntra') NoIntra = 1; else NoIntra = 0; end % Process all subjects iStudies = []; for i=1:length(iSubjects) iSubject = iSubjects(i); sSubject = bst_get('Subject', iSubject, 1); % No subject: error if isempty(sSubject) continue % If subject uses default channel file elseif (sSubject.UseDefaultChannel ~= 0) % Get default study for this subject [tmp___, iStudiesNew] = bst_get('DefaultStudy', iSubject); iStudies = [iStudies, iStudiesNew]; % Else: get all the studies belonging to this subject else if NoIntra [tmp___, iStudiesNew] = bst_get('StudyWithSubject', sSubject.FileName); else [tmp___, iStudiesNew] = bst_get('StudyWithSubject', sSubject.FileName, 'intra_subject'); end iStudies = [iStudies, iStudiesNew]; end end argout1 = iStudies; %% ==== STUDIES COUNT ==== % Usage: [nbStudies] = bst_get('StudyCount') case 'StudyCount' % Nothing if isempty(GlobalData.DataBase.iProtocol) || (GlobalData.DataBase.iProtocol == 0) argout1 = 0; return; end % Get list of current protocol studies ProtocolStudies = GlobalData.DataBase.ProtocolStudies(GlobalData.DataBase.iProtocol); argout1 = length(ProtocolStudies.Study); %% ==== SUBJECTS COUNT ==== % Usage: [nbSubjects] = bst_get('SubjectCount') case 'SubjectCount' if isempty(GlobalData.DataBase.iProtocol) || (GlobalData.DataBase.iProtocol == 0) argout1 = 0; return; end % Get list of current protocol studies ProtocolSubjects = GlobalData.DataBase.ProtocolSubjects(GlobalData.DataBase.iProtocol); argout1 = length(ProtocolSubjects.Subject); %% ==== NORMALIZED SUBJECT ==== case 'NormalizedSubject' % Get normalized subject name normSubjName = 'Group_analysis'; % Try to get normalized subject [sNormSubj, iNormSubj] = bst_get('Subject', normSubjName, 0); % If normalized subject does not exist: create it if isempty(sNormSubj) % Always use default anatomy UseDefaultAnat = 1; % If all the subjects use a global channel file: Use global default as well if ~isempty(GlobalData.DataBase.ProtocolSubjects(GlobalData.DataBase.iProtocol).Subject) && ... all([GlobalData.DataBase.ProtocolSubjects(GlobalData.DataBase.iProtocol).Subject.UseDefaultChannel] == 2) UseDefaultChannel = 2; else UseDefaultChannel = 1; end % Create subject [sNormSubj, iNormSubj] = db_add_subject(normSubjName, [], UseDefaultAnat, UseDefaultChannel); % Get full subject structure [sNormSubj, iNormSubj] = bst_get('Subject', normSubjName, 0); end argout1 = sNormSubj; argout2 = iNormSubj; %% ==== ANALYSIS STUDY (INTRA) ==== % Usage: [sAnalStudy, iAnalStudy] = bst_get('AnalysisIntraStudy', iSubject) case 'AnalysisIntraStudy' % Parse inputs if (nargin == 2) iSubject = varargin{2}; else error('Invalid call to bst_get()'); end % Get subject sSubject = bst_get('Subject', iSubject, 1); % Get studies related to subject [sSubjStudies, iSubjStudies] = bst_get('StudyWithSubject', sSubject.FileName, 'intra_subject'); % Look for the 'AnalysisIntra' study iFound = find(cellfun(@(c)ismember(bst_get('DirAnalysisIntra'), c), {sSubjStudies.Condition})); iAnalStudy = iSubjStudies(iFound); sAnalStudy = sSubjStudies(iFound); % Return found structure argout1 = sAnalStudy; argout2 = iAnalStudy; %% ==== ANALYSIS STUDY (INTER) ==== % Usage: [sAnalStudyInter, iAnalStudyInter] = bst_get('AnalysisInterStudy') case 'AnalysisInterStudy' iAnalStudyInter = -2; [argout1, argout2] = bst_get('Study', iAnalStudyInter); %% ==== DEFAULT STUDY ==== % Usage: [sDefaulStudy, iDefaultStudy] = bst_get('DefaultStudy', iSubject) % [sDefaulStudy, iDefaultStudy] = bst_get('DefaultStudy') : iSubject=0 % [sDefaulStudy, iDefaultStudy] = bst_get('DefaultStudy', SubjectFile) case 'DefaultStudy' if isempty(GlobalData.DataBase.iProtocol) || (GlobalData.DataBase.iProtocol == 0) return; end % Parse inputs if (nargin == 1) iSubject = 0; elseif (nargin == 2) && isnumeric(varargin{2}) iSubject = varargin{2}; elseif (nargin == 2) && ischar(varargin{2}) SubjectFile = varargin{2}; % Get subject attached to study [sSubject, iSubject] = bst_get('Subject', SubjectFile, 1); if isempty(sSubject) || ~sSubject.UseDefaultChannel return; end else error('Invalid call to bst_get()'); end % === DEFAULT SUBJECT === % => Return global default study if (iSubject == 0) % Get protocol's studies ProtocolStudies = GlobalData.DataBase.ProtocolStudies(GlobalData.DataBase.iProtocol); % Return Global default study argout1 = ProtocolStudies.DefaultStudy; argout2 = -3; % === NORMAL SUBJECT === else % Get subject sSubject = bst_get('Subject', iSubject, 1); % === GLOBAL DEFAULT STUDY === if sSubject.UseDefaultChannel == 2 % Get protocol's studies ProtocolStudies = GlobalData.DataBase.ProtocolStudies(GlobalData.DataBase.iProtocol); % Return Global default study argout1 = ProtocolStudies.DefaultStudy; argout2 = -3; % === SUBJECT'S DEFAULT STUDY === elseif sSubject.UseDefaultChannel == 1 % Get studies related to subject [sSubjStudies, iSubjStudies] = bst_get('StudyWithSubject', sSubject.FileName, 'default_study'); % Look for the 'DefaultStudy' study iFound = find(cellfun(@(c)ismember(bst_get('DirDefaultStudy'), c), {sSubjStudies.Condition})); iDefaultStudy = iSubjStudies(iFound); sDefaultStudy = sSubjStudies(iFound); % Return found structure argout1 = sDefaultStudy; argout2 = iDefaultStudy; end end %% ==== SUBJECT ==== % Usage : [sSubject, iSubject] = bst_get('Subject', iSubject, isRaw) % [sSubject, iSubject] = bst_get('Subject', SubjectFileName, isRaw); % [sSubject, iSubject] = bst_get('Subject', SubjectName, isRaw); % [sSubject, iSubject] = bst_get('Subject'); % If isRaw is set: force to return the real brainstormsubject description % (ignoring wether it uses protocol's default anatomy or not) case 'Subject' if isempty(GlobalData.DataBase.iProtocol) || (GlobalData.DataBase.iProtocol == 0) return; end % Get list of current protocol subjects ProtocolSubjects = GlobalData.DataBase.ProtocolSubjects(GlobalData.DataBase.iProtocol); sSubject = []; SubjectName = []; SubjectFileName = []; % ISRAW parameter if (nargin < 3) isRaw = 0; else isRaw = varargin{3}; end % Call: bst_get('subject', iSubject, isRaw); if (nargin >= 2) && isnumeric(varargin{2}) iSubject = varargin{2}; if (iSubject > length(ProtocolSubjects.Subject)) error('Invalid subject indice.'); end % If required subject is default subject (iSubject = 0) if (iSubject == 0) % Default subject available if ~isempty(ProtocolSubjects.DefaultSubject) sSubject = ProtocolSubjects.DefaultSubject; % Default subject not available else return end % Normal subject else sSubject = ProtocolSubjects.Subject(iSubject); end % Call: bst_get('subject', SubjectFileName, isRaw); % Call: bst_get('subject', SubjectName, isRaw); elseif (nargin >= 2) && isempty(varargin{2}) % If study name is empty: use DefaultSubject SubjectFileName = ProtocolSubjects.DefaultSubject.FileName; elseif (nargin >= 2) && (ischar(varargin{2})) [fName, fBase, fExt] = bst_fileparts(varargin{2}); % Argument is a Matlab .mat filename if strcmpi(fExt, '.mat') SubjectFileName = varargin{2}; % Else : assume argument is a directory else SubjectName = file_standardize(varargin{2}); end % Call: bst_get('subject'); => looking for current subject elseif (nargin < 2) % Get current subject filename in current study sStudy = bst_get('Study'); if isempty(sStudy) return end SubjectFileName = sStudy.BrainStormSubject; % If study's subject is not defined, get DefaultSubject if isempty(SubjectFileName) && ~isempty(ProtocolSubjects.DefaultSubject) SubjectFileName = ProtocolSubjects.DefaultSubject.FileName; end else error('Invalid call to bst_get()'); end % If Subject is defined by its filename/name if isempty(sSubject) % Look in Default Subject if ~isempty(ProtocolSubjects.DefaultSubject) && (file_compare(ProtocolSubjects.DefaultSubject.FileName, SubjectFileName) ... || strcmpi(ProtocolSubjects.DefaultSubject.Name, SubjectName)) sSubject = ProtocolSubjects.DefaultSubject; iSubject = 0; % If not found : find target subject file name in normal subjects elseif ~isempty(SubjectFileName) iSubject = find(file_compare({ProtocolSubjects.Subject.FileName}, SubjectFileName), 1); sSubject = ProtocolSubjects.Subject(iSubject); elseif ~isempty(SubjectName) iSubject = find(file_compare({ProtocolSubjects.Subject.Name}, SubjectName), 1); sSubject = ProtocolSubjects.Subject(iSubject); else error('Subject name not specified.'); end end % Return found subject if ~isempty(iSubject) && ~isempty(sSubject) % If subject uses default subject if sSubject.UseDefaultAnat && ~isRaw && ~isempty(ProtocolSubjects.DefaultSubject) && ~isempty(ProtocolSubjects.DefaultSubject.FileName) % Return default subject (WITH REAL SUBJECT'S NAME) argout1 = ProtocolSubjects.DefaultSubject; argout1.Name = sSubject.Name; argout1.UseDefaultAnat = sSubject.UseDefaultAnat; argout1.UseDefaultChannel = sSubject.UseDefaultChannel; argout2 = iSubject; % Else, return found subject else argout1 = sSubject; argout2 = iSubject; end end %% ==== SURFACE FILE ==== % Usage : [sSubject, iSubject, iSurface] = bst_get('SurfaceFile', SurfaceFile) case 'SurfaceFile' % No protocol in database if isempty(GlobalData) || isempty(GlobalData.DataBase) || isempty(GlobalData.DataBase.iProtocol) || (GlobalData.DataBase.iProtocol == 0) return; end % Get list of current protocol subjects ProtocolSubjects = GlobalData.DataBase.ProtocolSubjects(GlobalData.DataBase.iProtocol); if isempty(ProtocolSubjects) return end; % Parse inputs if (nargin == 2) SurfaceFile = varargin{2}; else error('Invalid call to bst_get().'); end % Remove SUBJECTS path from SurfaceFile SurfaceFile = file_short(SurfaceFile); % Look for surface file in DefaultSubject if ~isempty(ProtocolSubjects.DefaultSubject) % Find the first surface that matches the SurfaceFile iSurface = find(file_compare(SurfaceFile, {ProtocolSubjects.DefaultSubject.Surface.FileName}), 1); % If a surface was found in default subject : return it if ~isempty(iSurface) argout1 = ProtocolSubjects.DefaultSubject; argout2 = 0; argout3 = iSurface; return end end % Look for surface file in all the surfaces of all subjects for iSubj = 1:length(ProtocolSubjects.Subject) % Find the first surface that matches the SurfaceFile iSurface = find(file_compare(SurfaceFile, {ProtocolSubjects.Subject(iSubj).Surface.FileName}), 1); % If a surface was found in current subject : return it if ~isempty(iSurface) argout1 = ProtocolSubjects.Subject(iSubj); argout2 = iSubj; argout3 = iSurface; return end end %% ==== SURFACE FILE BY TYPE ==== % Usage : [sSurface, iSurface] = bst_get('SurfaceFileByType', iSubject, SurfaceType) % [sSurface, iSurface] = bst_get('SurfaceFileByType', SubjectFile, SurfaceType) % [sSurface, iSurface] = bst_get('SurfaceFileByType', SurfaceFile, SurfaceType) % [sSurface, iSurface] = bst_get('SurfaceFileByType', MriFile, SurfaceType) % [sSurface, iSurface] = bst_get('SurfaceFileByType', ..., SurfaceType, isDefaultOnly) case 'SurfaceFileByType' % By default: return only the default surfaces of the category if (nargin < 4) isDefaultOnly = 1; else isDefaultOnly = varargin{4}; end % Get subject if isempty(varargin{2}) % Get default subject sSubject = bst_get('Subject', 0); elseif ischar(varargin{2}) FileName = varargin{2}; sSubject = bst_get('AnyFile', FileName); else iSubject = varargin{2}; sSubject = bst_get('Subject', iSubject); end % Error handling if isempty(sSubject) disp('BST> Warning: Subject not found.'); return; elseif isempty(sSubject.Surface) return; end SurfaceType = varargin{3}; % === RETURN ONLY DEFAULTS === if isDefaultOnly % Look for required surface type field = ['i' SurfaceType]; if ~isfield(sSubject, field) || isempty(sSubject.(field)) return end argout1 = sSubject.Surface(sSubject.(field)); argout2 = sSubject.(field); % === RETURN ALL THE SURFACES === else % Build the list of tagged surfaces fileTag = ['_' lower(SurfaceType)]; iTargetList = find(cellfun(@(c)~isempty(strfind(c, fileTag)), {sSubject.Surface.FileName})); % Put the default cortex on top of the list iDefaults = intersect([sSubject.iCortex, sSubject.iScalp, sSubject.iInnerSkull, sSubject.iOuterSkull, sSubject.iFibers, sSubject.iFEM], iTargetList); if ~isempty(iDefaults) iTargetList = [iDefaults, setdiff(iTargetList, iDefaults)]; end % Return all cortex surfaces argout1 = sSubject.Surface(iTargetList); argout2 = iTargetList; end %% ==== MRI FILE ==== % Usage : [sSubject, iSubject, iMri] = bst_get('MriFile', MriFile) case 'MriFile' % No protocol in database if isempty(GlobalData.DataBase.iProtocol) || (GlobalData.DataBase.iProtocol == 0) return; end % Get list of current protocol subjects ProtocolSubjects = GlobalData.DataBase.ProtocolSubjects(GlobalData.DataBase.iProtocol); if isempty(ProtocolSubjects) return end % Parse inputs if (nargin == 2) MriFile = varargin{2}; else error('Invalid call to bst_get().'); end % Remove SUBJECTS path from MriFile MriFile = file_short(MriFile); % Look for MRI file in DefaultSubject if ~isempty(ProtocolSubjects.DefaultSubject) % Find the first MRI that matches the MriFile iMri = find(file_compare(MriFile, {ProtocolSubjects.DefaultSubject.Anatomy.FileName}), 1); % If a MRI was found in default subject : return it if ~isempty(iMri) argout1 = ProtocolSubjects.DefaultSubject; argout2 = 0; argout3 = iMri; return end end % Look for MRI file in all the MRIs of all subjects for iSubj = 1:length(ProtocolSubjects.Subject) % Find the first MRI that matches the MriFile iMri = find(file_compare(MriFile, {ProtocolSubjects.Subject(iSubj).Anatomy.FileName}), 1); % If a MRI was found in current subject : return it if ~isempty(iMri) argout1 = ProtocolSubjects.Subject(iSubj); argout2 = iSubj; argout3 = iMri; return end end %% ==== CHANNEL FILE ==== % Usage: [sStudy, iStudy, iChannel] = bst_get('ChannelFile', ChannelFile) case 'ChannelFile' % No protocol in database if isempty(GlobalData.DataBase.iProtocol) || (GlobalData.DataBase.iProtocol == 0) return; end ProtocolInfo = GlobalData.DataBase.ProtocolInfo(GlobalData.DataBase.iProtocol); % Parse inputs if (nargin == 2) ChannelFile = varargin{2}; ChannelFile = strrep(ChannelFile, ProtocolInfo.STUDIES, ''); else error('Invalid call to bst_get().'); end % Look for Channel file in all the surfaces of all subjects [argout1, argout2, argout3] = findFileInStudies('Channel', 'FileName', ChannelFile); %% ==== CHANNEL FILE FOR STUDY ==== % Usage: [ChannelFile, sStudy, iStudy] = bst_get('ChannelFileForStudy', StudyFile/DataFile) case 'ChannelFileForStudy' % Parse inputs if (nargin == 2) StudyFile = varargin{2}; else error('Invalid call to bst_get().'); end % Get study in database [sStudy, iStudy] = bst_get('Study', StudyFile); % If data file instead of Study file if isempty(sStudy) [sStudy, iStudy] = bst_get('AnyFile', StudyFile); end sChannel = bst_get('ChannelForStudy', iStudy); if ~isempty(sChannel) argout1 = sChannel.FileName; argout2 = sStudy; argout3 = iStudy; else argout1 = []; end %% ==== CHANNEL STRUCT FOR STUDY ==== % Usage: [sChannel, iChanStudy] = bst_get('ChannelForStudy', iStudies) case 'ChannelForStudy' % Parse inputs if (nargin == 2) iStudies = varargin{2}; else error('Invalid call to bst_get().'); end iChanStudies = []; sListChannel = []; for i = 1:length(iStudies) % Get study iStudy = iStudies(i); sStudy = bst_get('Study', iStudy); if isempty(sStudy) continue; end iChanStudy = iStudy; % === Analysis-Inter node === iAnalysisInter = -2; iGlobalDefaultStudy = -3; if (iStudy == iAnalysisInter) % If no channel file is defined in 'Analysis-intra' node: look in if isempty(sStudy.Channel) % Get global default study sStudy = bst_get('Study', iGlobalDefaultStudy); iChanStudy = iGlobalDefaultStudy; end % === All other nodes === else % Get subject attached to study [sSubject, iSubject] = bst_get('Subject', sStudy.BrainStormSubject, 1); if isempty(sSubject) return; end % Subject uses default channel/headmodel if (sSubject.UseDefaultChannel ~= 0) [sStudy, iChanStudy] = bst_get('DefaultStudy', iSubject); if isempty(sStudy) return end end end iChanStudies = [iChanStudies, iChanStudy]; sListChannel = [sListChannel, sStudy.Channel]; end % Return Channel structure argout1 = sListChannel; argout2 = iChanStudies; %% ==== CHANNEL MODALITIES ===== % Usage: [Modalities, DispMod, DefMod] = bst_get('ChannelModalities', ChannelFile) % [Modalities, DispMod, DefMod] = bst_get('ChannelModalities', DataFile/ResultsFile/TimefreqFile...) case 'ChannelModalities' % Get input file [sStudy, iStudy, iItem, DataType, sItem] = bst_get('AnyFile', varargin{2}); % If channel file if strcmpi(DataType, 'channel') sChannel = sItem; else sChannel = bst_get('ChannelForStudy', iStudy); end % Return modalities if ~isempty(sChannel) % Get all modalities if ~isempty(sChannel.DisplayableSensorTypes) % Return the displayable sensors on top of the list argout1 = cat(2, sChannel.DisplayableSensorTypes, setdiff(sChannel.Modalities, sChannel.DisplayableSensorTypes)); else argout1 = sChannel.Modalities; end % Get only sensors that have spatial representation argout2 = sChannel.DisplayableSensorTypes; % Default candidates if ~isempty(argout2) defList = argout2; else defList = argout1; end if isempty(defList) return; end % Remove EDF and BDF from the default list defList = setdiff(defList, {'EDF','BDF','KDF'}); % Get default modality if ismember('SEEG', defList) argout3 = 'SEEG'; elseif ismember('ECOG', defList) argout3 = 'ECOG'; elseif any(ismember({'MEG','MEG GRAD','MEG MAG'}, defList)) argout3 = 'MEG'; elseif ismember('EEG', defList) argout3 = 'EEG'; elseif ismember('NIRS', defList) argout3 = 'NIRS'; else argout3 = defList{1}; end % Place the default on top of the lists if ismember(argout3, argout1) argout1(strcmpi(argout1, argout3)) = []; argout1 = cat(2, argout3, argout1); end if ismember(argout3, argout2) argout2(strcmpi(argout2, argout3)) = []; argout2 = cat(2, argout3, argout2); end else argout1 = []; end %% ==== TIMEFREQ DISPLAY MODALITIES ==== % Usage: DisplayMod = bst_get('TimefreqDisplayModalities', TimefreqFile) case 'TimefreqDisplayModalities' TimefreqFile = varargin{2}; % Load sensor names from file TimefreqMat = in_bst_timefreq(TimefreqFile, 0, 'RowNames'); % Get channel file ChannelFile = bst_get('ChannelFileForStudy', TimefreqFile); if isempty(ChannelFile) return; end % Load channel file ChannelMat = load(file_fullpath(ChannelFile), 'Channel'); % Get channels that are present in the file [tmp__,I,J] = intersect({ChannelMat.Channel.Name}, TimefreqMat.RowNames); FileMod = unique({ChannelMat.Channel(I).Type}); % Check if only one type of gradiometer is selected if isequal(FileMod, {'MEG GRAD'}) && all(cellfun(@(c)(c(end)=='2'), {ChannelMat.Channel(I).Name})) argout1 = {'MEG GRAD2'}; elseif isequal(FileMod, {'MEG GRAD'}) && all(cellfun(@(c)(c(end)=='3'), {ChannelMat.Channel(I).Name})) argout1 = {'MEG GRAD3'}; % Keep only the modalities that can be displayed (as topography) else argout1 = intersect(FileMod, {'MEG','MEG GRAD','MEG MAG','EEG','ECOG','SEEG','NIRS'}); end %% ==== CHANNEL DEVICE ==== % Usage: Device = bst_get('ChannelDevice', ChannelFile) case 'ChannelDevice' ChannelFile = varargin{2}; if ~isempty(strfind(ChannelFile, 'vectorview306')) Device = 'Vectorview306'; elseif ~isempty(strfind(ChannelFile, 'ctf_acc1')) Device = 'CTF'; elseif ~isempty(strfind(ChannelFile, '4d_acc1')) Device = '4D'; elseif ~isempty(strfind(ChannelFile, 'babysquid')) Device = 'BabySQUID'; elseif ~isempty(strfind(ChannelFile, 'babymeg')) Device = 'BabyMEG'; elseif ~isempty(strfind(ChannelFile, 'kit')) Device = 'KIT'; elseif ~isempty(strfind(ChannelFile, 'ricoh')) Device = 'RICOH'; elseif ~isempty(strfind(ChannelFile, 'kriss')) Device = 'KRISS'; elseif ~isempty(strfind(ChannelFile, 'nirsbrs')) Device = 'NIRS-BRS'; else Device = ''; end argout1 = Device; %% ==== HEADMODEL STRUCT FOR STUDY ==== % Usage: [sHeadModel] = bst_get('HeadModelForStudy', iStudy) case 'HeadModelForStudy' % Parse inputs if (nargin == 2) iStudy = varargin{2}; else error('Invalid call to bst_get().'); end % Get study sStudy = bst_get('Study', iStudy); % === Analysis-Inter node === iAnalysisInter = -2; iGlobalDefaultStudy = -3; if (iStudy == iAnalysisInter) % If no channel file is defined in 'Analysis-intra' node: look in if isempty(sStudy.iHeadModel) % Get global default study sStudy = bst_get('Study', iGlobalDefaultStudy); end % === All other nodes === else % Get subject attached to study [sSubject, iSubject] = bst_get('Subject', sStudy.BrainStormSubject, 1); if isempty(sSubject) return; end % Subject uses default channel/headmodel if (sSubject.UseDefaultChannel ~= 0) sStudy = bst_get('DefaultStudy', iSubject); if isempty(sStudy) return end end end % Return HeadModel structure if ~isempty(sStudy.iHeadModel) argout1 = sStudy.HeadModel(sStudy.iHeadModel(1)); else argout1 = []; end %% ==== HEADMODEL FILE ==== % Usage: [sStudy, iStudy, iHeadModel] = bst_get('HeadModelFile', HeadModelFile, iStudies) % [sStudy, iStudy, iHeadModel] = bst_get('HeadModelFile', HeadModelFile) case 'HeadModelFile' % No protocol in database if isempty(GlobalData.DataBase.iProtocol) || (GlobalData.DataBase.iProtocol == 0) return; end % Input #2: HeadModelFile ProtocolInfo = GlobalData.DataBase.ProtocolInfo(GlobalData.DataBase.iProtocol); HeadModelFile = varargin{2}; HeadModelFile = strrep(HeadModelFile, ProtocolInfo.STUDIES, ''); % Input #3: iStudies if (nargin < 3) iStudies = []; else iStudies = varargin{3}; end % Look for surface file in all the surfaces of all subjects [argout1, argout2, argout3] = findFileInStudies('HeadModel', 'FileName', HeadModelFile, iStudies); %% ==== NOISECOV FILE ==== % Usage: [sStudy, iStudy, iNoiseCov] = bst_get('NoiseCovFile', NoiseCovFile, iStudies) % [sStudy, iStudy, iNoiseCov] = bst_get('NoiseCovFile', NoiseCovFile) % Usage: [sStudy, iStudy, iNoiseCov] = bst_get('DataCovFile', NoiseCovFile, iStudies) % [sStudy, iStudy, iNoiseCov] = bst_get('DataCovFile', NoiseCovFile) case {'NoiseCovFile', 'DataCovFile'} % No protocol in database if isempty(GlobalData.DataBase.iProtocol) || (GlobalData.DataBase.iProtocol == 0) return; end % Input #2: NoiseCovFile ProtocolInfo = GlobalData.DataBase.ProtocolInfo(GlobalData.DataBase.iProtocol); NoiseCovFile = varargin{2}; NoiseCovFile = strrep(NoiseCovFile, ProtocolInfo.STUDIES, ''); % Input #3: iStudies if (nargin < 3) iStudies = []; else iStudies = varargin{3}; end % Look for surface file in all the surfaces of all subjects [argout1, argout2, argout3] = findFileInStudies('NoiseCov', 'FileName', NoiseCovFile, iStudies); %% ==== DATA FILE ==== % Usage: [sStudy, iStudy, iData] = bst_get('DataFile', DataFile, iStudies) % [sStudy, iStudy, iData] = bst_get('DataFile', DataFile) case 'DataFile' % No protocol in database if isempty(GlobalData.DataBase.iProtocol) || (GlobalData.DataBase.iProtocol == 0) return; end % Input #2: DataFile ProtocolInfo = GlobalData.DataBase.ProtocolInfo(GlobalData.DataBase.iProtocol); DataFile = varargin{2}; DataFile = strrep(DataFile, ProtocolInfo.STUDIES, ''); % Input #3: iStudies if (nargin < 3) iStudies = []; else iStudies = varargin{3}; end % Look for file in all the studies [argout1, argout2, argout3] = findFileInStudies('Data', 'FileName', DataFile, iStudies); %% ==== DATA FOR DATA LIST ==== % Usage: [iFoundData] = bst_get('DataForDataList', iStudy, DataListName) case 'DataForDataList' iStudy = varargin{2}; DataListName = varargin{3}; % Get study structure sStudy = bst_get('Study', iStudy); % Get all the data files held by this datalist listComments = cellfun(@(c)deblank(str_remove_parenth(c)), {sStudy.Data.Comment}, 'UniformOutput', 0); iFoundData = find(strcmp(listComments, DataListName)); % Return found data files argout1 = iFoundData; %% ==== MATRIX FOR MATRIX LIST ==== % Usage: [iFoundMatrix] = bst_get('MatrixForMatrixList', iStudy, MatrixListName) case 'MatrixForMatrixList' iStudy = varargin{2}; MatrixListName = varargin{3}; % Get study structure sStudy = bst_get('Study', iStudy); % Get all the matrix files held by this datalist listComments = cellfun(@(c)deblank(str_remove_parenth(c)), {sStudy.Matrix.Comment}, 'UniformOutput', 0); iFoundMatrix = find(strcmp(listComments, MatrixListName)); % Return found matrix files argout1 = iFoundMatrix; %% ==== DATA FOR STUDY (INCLUDING SHARED STUDIES) ==== % Usage: [iStudies, iDatas] = bst_get('DataForStudy', iStudy) case 'DataForStudy' % Get target study iStudy = varargin{2}; sStudy = bst_get('Study', iStudy); isDefaultStudy = strcmpi(sStudy.Name, bst_get('DirDefaultStudy')); isGlobalDefault = (iStudy == -3); % If study is the global default study sStudies = []; iStudies = []; if isGlobalDefault % Get all the subjects of the protocol nbSubjects = bst_get('SubjectCount'); for iSubject = 1:nbSubjects sSubject = bst_get('Subject', iSubject, 1); if sSubject.UseDefaultChannel [tmp_sStudies, tmp_iStudies] = bst_get('StudyWithSubject', sSubject.FileName); sStudies = [sStudies, tmp_sStudies]; iStudies = [iStudies, tmp_iStudies]; end end % Else, if study is a subject's default study (ie. channel file is shared by all studies of one subject) elseif isDefaultStudy % Get all the subject's studies [sStudies, iStudies] = bst_get('StudyWithSubject', sStudy.BrainStormSubject, 'intra_subject', 'default_study'); else % Normal: one channel per condition sStudies = sStudy; iStudies = iStudy; end % Get all the DataFiles for all these studies for i = 1:length(sStudies) nData = length(sStudies(i).Data); argout1 = [argout1, repmat(iStudies(i), [1,nData])]; argout2 = [argout2, 1:nData]; end %% ==== DATA FOR STUDIES (INCLUDING SHARED STUDIES) ==== % Usage: [iStudies, iDatas] = bst_get('DataForStudies', iStudies) case 'DataForStudies' iStudies = varargin{2}; for i = 1:length(iStudies) [tmp_iStudies, tmp_iDatas] = bst_get('DataForStudy', iStudies(i)); argout1 = [argout1, tmp_iStudies]; argout2 = [argout2, tmp_iDatas]; end %% ==== DATA FILE FOR CHANNEL FILE ==== % Usage: DataFiles = bst_get('DataForChannelFile', ChannelFile) case 'DataForChannelFile' ChannelFile = varargin{2}; DataFiles = {}; % Get study for the given channel file [sStudy, iStudy] = bst_get('ChannelFile', ChannelFile); if isempty(sStudy) return; end % Get dependent data files [iStudies, iDatas] = bst_get('DataForStudy', iStudy); % Get all the Data filenames for i = 1:length(iStudies) sStudy = bst_get('Study', iStudies(i)); DataFiles = cat(2, DataFiles, {sStudy.Data(iDatas(i)).FileName}); end argout1 = DataFiles; %% ==== RESULTS FILE ==== % Usage: [sStudy, iStudy, iResult] = bst_get('ResultsFile', ResultsFile, iStudies) % [sStudy, iStudy, iResult] = bst_get('ResultsFile', ResultsFile) case 'ResultsFile' % No protocol in database if isempty(GlobalData.DataBase.iProtocol) || (GlobalData.DataBase.iProtocol == 0) return; end % Input #2: ResultsFile ProtocolInfo = GlobalData.DataBase.ProtocolInfo(GlobalData.DataBase.iProtocol); ResultsFile = varargin{2}; ResultsFile = strrep(ResultsFile, ProtocolInfo.STUDIES, ''); % Input #3: iStudies if (nargin < 3) iStudies = []; else iStudies = varargin{3}; end % Look for surface file in all the surfaces of all subjects [argout1, argout2, argout3] = findFileInStudies('Result', 'FileName', ResultsFile, iStudies); %% ==== RESULTS FOR DATA FILE ==== % Usage: [sStudy, iStudy, iResults] = bst_get('ResultsForDataFile', DataFile) : search the whole protocol % Usage: [sStudy, iStudy, iResults] = bst_get('ResultsForDataFile', DataFile, iStudies) : search only the specified studies case 'ResultsForDataFile' % No protocol in database if isempty(GlobalData.DataBase.iProtocol) || (GlobalData.DataBase.iProtocol == 0) return; end ProtocolInfo = GlobalData.DataBase.ProtocolInfo(GlobalData.DataBase.iProtocol); % Input #2: DataFile DataFile = varargin{2}; DataFile = strrep(DataFile, ProtocolInfo.STUDIES, ''); % Determine in which studies to search for ResultsFile if (nargin >= 3) % Studies specified in argument iStudy = varargin{3}; else % Get study in which DataFile is located [sStudy, iStudy] = bst_get('DataFile', DataFile); if isempty(iStudy) return; end end % Search selected studies [argout1, argout2, argout3] = findFileInStudies('Result', 'DataFile', DataFile, iStudy); %% ==== STAT FILE ==== % Usage: [sStudy, iStudy, iData] = bst_get('StatFile', StatFile, iStudies) % [sStudy, iStudy, iData] = bst_get('StatFile', StatFile) case 'StatFile' % No protocol in database if isempty(GlobalData.DataBase.iProtocol) || (GlobalData.DataBase.iProtocol == 0) return; end % Input #2: SataFile ProtocolInfo = GlobalData.DataBase.ProtocolInfo(GlobalData.DataBase.iProtocol); StatFile = varargin{2}; StatFile = strrep(StatFile, ProtocolInfo.STUDIES, ''); % Input #3: iStudies if (nargin < 3) iStudies = []; else iStudies = varargin{3}; end % Look for surface file in all the surfaces of all subjects [argout1, argout2, argout3] = findFileInStudies('Stat', 'FileName', StatFile, iStudies); %% ==== STAT FOR DATA FILE ==== % Usage: [sStudy, iStudy, iResults] = bst_get('StatForDataFile', DataFile) : search the whole protocol % Usage: [sStudy, iStudy, iResults] = bst_get('StatForDataFile', DataFile, iStudies) : search only the specified studies case 'StatForDataFile' % No protocol in database if isempty(GlobalData.DataBase.iProtocol) || (GlobalData.DataBase.iProtocol == 0) return; end ProtocolInfo = GlobalData.DataBase.ProtocolInfo(GlobalData.DataBase.iProtocol); % Parse inputs if (nargin >= 2) DataFile = varargin{2}; DataFile = strrep(DataFile, ProtocolInfo.STUDIES, ''); else error('Invalid call to bst_get().'); end % Determine in which studies to search for ResultsFile if (nargin >= 3) % Studies specified in argument iStudies = varargin{3}; else % Get study in which DataFile is located [sStudies, iStudies] = bst_get('DataFile', DataFile); if isempty(iStudies) return; end end % Search selected studies [argout1, argout2, argout3] = findFileInStudies('Stat', 'DataFile', DataFile, iStudies); %% ==== TIMEFREQ FILE ==== % Usage: [sStudy, iStudy, iTimefreq] = bst_get('TimefreqFile', TimefreqFile, iStudies) % [sStudy, iStudy, iTimefreq] = bst_get('TimefreqFile', TimefreqFile) case 'TimefreqFile' % No protocol in database if isempty(GlobalData.DataBase.iProtocol) || (GlobalData.DataBase.iProtocol == 0) return; end % Input #2: TimefreqFile ProtocolInfo = GlobalData.DataBase.ProtocolInfo(GlobalData.DataBase.iProtocol); TimefreqFile = varargin{2}; TimefreqFile = strrep(TimefreqFile, ProtocolInfo.STUDIES, ''); % Remove optional RefRowName iPipe = find(TimefreqFile == '|', 1); if ~isempty(iPipe) TimefreqFile = TimefreqFile(1:iPipe-1); end % Input #3: iStudies if (nargin < 3) iStudies = []; else iStudies = varargin{3}; end % Look for surface file in all the surfaces of all subjects [argout1, argout2, argout3] = findFileInStudies('Timefreq', 'FileName', TimefreqFile, iStudies); %% ==== TIMEFREQ FOR FILE ==== % Usage: [sStudy, iStudy, iTimefreq] = bst_get('TimefreqForFile', FileName, iStudies) : search only the specified studies % [sStudy, iStudy, iTimefreq] = bst_get('TimefreqForFile', FileName) : search the whole protocol case 'TimefreqForFile' % No protocol in database if isempty(GlobalData.DataBase.iProtocol) || (GlobalData.DataBase.iProtocol == 0) return; end ProtocolInfo = GlobalData.DataBase.ProtocolInfo(GlobalData.DataBase.iProtocol); % Parse inputs if (nargin >= 2) FileName = varargin{2}; FileName = strrep(FileName, ProtocolInfo.STUDIES, ''); else error('Invalid call to bst_get().'); end % Get study in which file is located if (nargin >= 3) iStudies = varargin{3}; [sStudy, iStudy, iFile, DataType] = bst_get('AnyFile', FileName, iStudies); else [sStudy, iStudy, iFile, DataType] = bst_get('AnyFile', FileName); end % If file was not found if isempty(iStudy) return; end % Search direct dependent files [tmp, tmp, iTf] = findFileInStudies('Timefreq', 'DataFile', FileName, iStudy); % Data files: get all the depending results, and then all the timefreq for those results if strcmpi(DataType, 'data') [tmp, tmp, iResults] = bst_get('ResultsForDataFile', FileName, iStudy); for i = 1:length(iResults); % Search selected studies [tmp, tmp, iTfRes] = findFileInStudies('Timefreq', 'DataFile', sStudy.Result(iResults(i)).FileName, iStudy); if ~isempty(iTfRes) iTf = [iTf iTfRes]; end end end % Return results if ~isempty(iTf) argout1 = sStudy; argout2 = iStudy; argout3 = iTf; end %% ==== DIPOLES FOR FILE ==== % Usage: [sStudy, iStudy, iDipoles] = bst_get('DipolesForFile', FileName, iStudies) : search only the specified studies % [sStudy, iStudy, iDipoles] = bst_get('DipolesForFile', FileName) : search the whole protocol case 'DipolesForFile' % No protocol in database if isempty(GlobalData.DataBase.iProtocol) || (GlobalData.DataBase.iProtocol == 0) return; end ProtocolInfo = GlobalData.DataBase.ProtocolInfo(GlobalData.DataBase.iProtocol); % Parse inputs if (nargin >= 2) FileName = varargin{2}; FileName = strrep(FileName, ProtocolInfo.STUDIES, ''); else error('Invalid call to bst_get().'); end % Get study in which file is located if (nargin >= 3) iStudies = varargin{3}; [sStudy, iStudy, iFile, DataType] = bst_get('AnyFile', FileName, iStudies); else [sStudy, iStudy, iFile, DataType] = bst_get('AnyFile', FileName); end % If file was not found if isempty(iStudy) return; end % Search direct dependent files [tmp, tmp, iDip] = findFileInStudies('Dipoles', 'DataFile', FileName, iStudy); % Data files: get all the depending results, and then all the timefreq for those results if strcmpi(DataType, 'data') [tmp, tmp, iResults] = bst_get('ResultsForDataFile', FileName, iStudy); for i = 1:length(iResults); % Search selected studies [tmp, tmp, iDipRes] = findFileInStudies('Dipoles', 'DataFile', sStudy.Result(iResults(i)).FileName, iStudy); if ~isempty(iDipRes) iDip = [iDip, iDipRes]; end end end % Return results if ~isempty(iDip) argout1 = sStudy; argout2 = iStudy; argout3 = iDip; end %% ==== TIMEFREQ FOR KERNEL ==== % Find all the timefreq files dependent from links due to a given kernel % Usage: [sStudy, iStudy, iTimefreq] = bst_get('TimefreqForKernel', KernelFile) case 'TimefreqForKernel' sFoundStudy = []; iFoundStudy = []; iFoundTimefreq = []; % No protocol in database if isempty(GlobalData.DataBase.iProtocol) || (GlobalData.DataBase.iProtocol == 0) return; end % Get study in which file is located KernelFile = varargin{2}; [sStudy, iStudy, iFile, DataType] = bst_get('ResultsFile', KernelFile); if isempty(iStudy) return; end % Get all the data files relative with this kernel [iDepStudies, iDepDatas] = bst_get('DataForStudy', iStudy); % Keep only once each study iDepStudies = unique(iDepStudies); % Process all the dependent studies for iSt = 1:length(iDepStudies) % Get the study structure sDepStudy = bst_get('Study', iDepStudies(iSt)); % Process each timefreq file separately for iTf = 1:length(sDepStudy.Timefreq) DataFile = sDepStudy.Timefreq(iTf).DataFile; % Keep only the files that are linked to LINKS if isempty(DataFile) || (length(DataFile) < 5) || ~isequal(DataFile(1:5), 'link|') continue; end % Split link splitFile = str_split(DataFile, '|'); % If the kernel is found: add it to the found list if file_compare(splitFile{2}, KernelFile) sFoundStudy = [sFoundStudy sDepStudy]; iFoundStudy = [iFoundStudy, iDepStudies(iSt)]; iFoundTimefreq = [iFoundTimefreq, iTf]; end end end % Return findings argout1 = sFoundStudy; argout2 = iFoundStudy; argout3 = iFoundTimefreq; %% ==== DIPOLES FOR KERNEL ==== % Find all the dipoles files dependent from links due to a given kernel % Usage: [sStudy, iStudy, iDipoles] = bst_get('TimefreqForKernel', KernelFile) case 'DipolesForKernel' sFoundStudy = []; iFoundStudy = []; iFoundDipoles = []; % No protocol in database if isempty(GlobalData.DataBase.iProtocol) || (GlobalData.DataBase.iProtocol == 0) return; end % Get study in which file is located KernelFile = varargin{2}; [sStudy, iStudy, iFile, DataType] = bst_get('ResultsFile', KernelFile); if isempty(iStudy) return; end % Get all the data files relative with this kernel [iDepStudies, iDepDatas] = bst_get('DataForStudy', iStudy); % Keep only once each study iDepStudies = unique(iDepStudies); % Process all the dependent studies for iSt = 1:length(iDepStudies) % Get the study structure sDepStudy = bst_get('Study', iDepStudies(iSt)); % Process each timefreq file separately for iDip = 1:length(sDepStudy.Dipoles) DataFile = sDepStudy.Dipoles(iDip).DataFile; % Keep only the files that are linked to LINKS if isempty(DataFile) || (length(DataFile) < 5) || ~isequal(DataFile(1:5), 'link|') continue; end % Split link splitFile = str_split(DataFile, '|'); % If the kernel is found: add it to the found list if file_compare(splitFile{2}, KernelFile) sFoundStudy = [sFoundStudy sDepStudy]; iFoundStudy = [iFoundStudy, iDepStudies(iSt)]; iFoundDipoles = [iFoundDipoles, iDip]; end end end % Return findings argout1 = sFoundStudy; argout2 = iFoundStudy; argout3 = iFoundDipoles; %% ==== DIPOLES FILE ==== % Usage: [sStudy, iStudy, iDipole] = bst_get('DipolesFile', DipolesFile, iStudies) % [sStudy, iStudy, iDipole] = bst_get('DipolesFile', DipolesFile) case 'DipolesFile' % No protocol in database if isempty(GlobalData.DataBase.iProtocol) || (GlobalData.DataBase.iProtocol == 0) return; end % Input #2: DipolesFile ProtocolInfo = GlobalData.DataBase.ProtocolInfo(GlobalData.DataBase.iProtocol); DipolesFile = varargin{2}; DipolesFile = strrep(DipolesFile, ProtocolInfo.STUDIES, ''); % Input #3: iStudies if (nargin < 3) iStudies = []; else iStudies = varargin{3}; end % Look for surface file in all the surfaces of all subjects [argout1, argout2, argout3] = findFileInStudies('Dipoles', 'FileName', DipolesFile, iStudies); %% ==== MATRIX FILE ==== % Usage: [sStudy, iStudy, iDipole] = bst_get('MatrixFile', MatrixFile, iStudies) % [sStudy, iStudy, iDipole] = bst_get('MatrixFile', MatrixFile) case 'MatrixFile' % No protocol in database if isempty(GlobalData.DataBase.iProtocol) || (GlobalData.DataBase.iProtocol == 0) return; end % Input #2: MatrixFile ProtocolInfo = GlobalData.DataBase.ProtocolInfo(GlobalData.DataBase.iProtocol); MatrixFile = varargin{2}; MatrixFile = strrep(MatrixFile, ProtocolInfo.STUDIES, ''); % Input #3: iStudies if (nargin < 3) iStudies = []; else iStudies = varargin{3}; end % Look for surface file in all the surfaces of all subjects [argout1, argout2, argout3] = findFileInStudies('Matrix', 'FileName', MatrixFile, iStudies); %% ==== IMAGE FILE ==== % Usage: [sStudy, iStudy, iDipole] = bst_get('ImageFile', ImageFile, iStudies) % [sStudy, iStudy, iDipole] = bst_get('ImageFile', ImageFile) case 'ImageFile' % No protocol in database if isempty(GlobalData.DataBase.iProtocol) || (GlobalData.DataBase.iProtocol == 0) return; end % Input #2: ImageFile ProtocolInfo = GlobalData.DataBase.ProtocolInfo(GlobalData.DataBase.iProtocol); ImageFile = varargin{2}; ImageFile = strrep(ImageFile, ProtocolInfo.STUDIES, ''); % Input #3: iStudies if (nargin < 3) iStudies = []; else iStudies = varargin{3}; end % Look for surface file in all the surfaces of all subjects [argout1, argout2, argout3] = findFileInStudies('Image', 'FileName', ImageFile, iStudies); %% ==== ANY FILE ==== % Usage: [sStudy, iStudy, iFile, DataType, sItem] = bst_get('AnyFile', FileName, iStudies) % [sStudy, iStudy, iFile, DataType, sItem] = bst_get('AnyFile', FileName) case 'AnyFile' % Input #2: FileName FileName = varargin{2}; if isempty(FileName) return end % Input #3: iStudies if (nargin < 3) iStudies = []; else iStudies = varargin{3}; end % Get data format fileType = file_gettype(FileName); if isempty(fileType) error('File type is not recognized.'); end sItem = []; % Get information related with this file switch (fileType) % ===== FUNCTIONAL ===== case 'channel' [sStudy, iStudy] = bst_get('ChannelFile', FileName); iItem = 1; if (nargout >= 5) && ~isempty(sStudy) sItem = sStudy.Channel; end case 'headmodel' [sStudy, iStudy, iItem] = bst_get('HeadModelFile', FileName); if (nargout >= 5) && ~isempty(sStudy) sItem = sStudy.HeadModel(iItem); end case 'noisecov' [sStudy, iStudy, iItem] = bst_get('NoiseCovFile', FileName); if (nargout >= 5) && ~isempty(sStudy) sItem = sStudy.NoiseCov(iItem); end case 'ndatacov' [sStudy, iStudy, iItem] = bst_get('DataCovFile', FileName); if (nargout >= 5) && ~isempty(sStudy) sItem = sStudy.NoiseCov(iItem); end case {'data', 'spike'} [sStudy, iStudy, iItem] = bst_get('DataFile', FileName, iStudies); if (nargout >= 5) && ~isempty(sStudy) sItem = sStudy.Data(iItem); end case {'results', 'link'} [sStudy, iStudy, iItem] = bst_get('ResultsFile', FileName, iStudies); if (nargout >= 5) && ~isempty(sStudy) sItem = sStudy.Result(iItem); end case {'presults', 'pdata','ptimefreq','pmatrix'} [sStudy, iStudy, iItem] = bst_get('StatFile', FileName, iStudies); if (nargout >= 5) && ~isempty(sStudy) sItem = sStudy.Stat(iItem); end case 'dipoles' [sStudy, iStudy, iItem] = bst_get('DipolesFile', FileName, iStudies); if (nargout >= 5) && ~isempty(sStudy) sItem = sStudy.Dipoles(iItem); end case 'timefreq' % Remove optional RefRowName iPipe = find(FileName == '|', 1); if ~isempty(iPipe) FileName = FileName(1:iPipe-1); end [sStudy, iStudy, iItem] = bst_get('TimefreqFile', FileName, iStudies); if (nargout >= 5) && ~isempty(sStudy) sItem = sStudy.Timefreq(iItem); end case 'matrix' [sStudy, iStudy, iItem] = bst_get('MatrixFile', FileName, iStudies); if (nargout >= 5) && ~isempty(sStudy) sItem = sStudy.Matrix(iItem); end case 'brainstormstudy' [sStudy, iStudy] = bst_get('Study', FileName); iItem = 0; if (nargout >= 5) && ~isempty(sStudy) sItem = sStudy; end case {'image', 'video', 'videolink'} [sStudy, iStudy, iItem] = bst_get('ImageFile', FileName, iStudies); if (nargout >= 5) && ~isempty(sStudy) sItem = sStudy.Image(iItem); end % ===== ANATOMY ===== case {'cortex','scalp','innerskull','outerskull','tess','fibers','fem'} [sStudy, iStudy, iItem] = bst_get('SurfaceFile', FileName); if (nargout >= 5) && ~isempty(sStudy) sItem = sStudy.Surface(iItem); end case 'subjectimage' [sStudy, iStudy, iItem] = bst_get('MriFile', FileName); if (nargout >= 5) && ~isempty(sStudy) sItem = sStudy.Anatomy(iItem); end case 'brainstormsubject' [sStudy, iStudy] = bst_get('Subject', FileName); iItem = 0; if (nargout >= 5) && ~isempty(sStudy) sItem = sStudy; end otherwise error('File type is not recognized.'); end argout1 = sStudy; argout2 = iStudy; argout3 = iItem; argout4 = fileType; if (nargout >= 5) argout5 = sItem; end %% ==== GET RELATED DATA FILE ==== % Usage: DataFile = bst_get('RelatedDataFile', FileName, iStudies) % DataFile = bst_get('RelatedDataFile', FileName) case 'RelatedDataFile' % Input #2: FileName FileName = varargin{2}; % Input #3: iStudies if (nargin < 3) iStudies = []; else iStudies = varargin{3}; end % Get file in database [sStudy, iStudy, iFile, fileType] = bst_get('AnyFile', FileName, iStudies); % If this data file does not belong to any study if isempty(sStudy) return; end % Get associated data file switch (fileType) case 'data' RelatedDataFile = sStudy.Data(iFile).FileName; case {'pdata','presults','ptimefreq','pmatrix'} RelatedDataFile = sStudy.Stat(iFile).DataFile; case {'results', 'link'} RelatedDataFile = sStudy.Result(iFile).DataFile; case 'dipoles' RelatedDataFile = sStudy.Dipoles(iFile).DataFile; case 'timefreq' RelatedDataFile = sStudy.Timefreq(iFile).DataFile; otherwise RelatedDataFile = ''; end % If related file is results: get related data file if ~isempty(RelatedDataFile) relFileType = file_gettype(RelatedDataFile); if ismember(relFileType, {'link','results'}) RelatedDataFile = bst_get('RelatedDataFile', RelatedDataFile, iStudy); end end % Return file argout1 = RelatedDataFile; %% ==== ALL CONDITIONS FOR ONE SUBJECT ==== % Usage: [Conditions] = bst_get('ConditionsForSubject', SubjectFile) case 'ConditionsForSubject' % Parse inputs if (nargin == 2) SubjectFile = varargin{2}; else error('Invalid call to bst_get().'); end % Get list of studies associated with subject sStudies = bst_get('StudyWithSubject', SubjectFile); % Get Conditions for each study Conditions = {}; for i = 1:length(sStudies) % Test if the condition of this study was not added previously isNewCondition = 1; for iCond = 1:length(Conditions) % If new condition is found % (and excludes DirAnalysisIntra and DirDefaultSubject from list) if isempty(sStudies(i).Condition) || ... isequal(sStudies(i).Condition, Conditions(iCond)) || ... strcmpi(sStudies(i).Condition{1}, bst_get('DirAnalysisIntra')) || ... strcmpi(sStudies(i).Condition{1}, bst_get('DirDefaultSubject')) isNewCondition = 0; break; end end % If Condition is not added yet : add it to the list if isNewCondition && ~isempty(sStudies(i).Condition) Conditions{end+1} = sStudies(i).Condition{1}; end end % Return conditions list argout1 = Conditions; %% ==== ANATOMY DEFAULTS ==== % Returns the list of all the anatomy defaults (distributed with the software + user defined) case 'AnatomyDefaults' % Parse inputs if (nargin == 2) AnatName = varargin{2}; else AnatName = []; end % Get templates from the brainstorm3 folder progDir = bst_fullfile(bst_get('BrainstormDefaultsDir'), 'anatomy'); progFiles = dir(progDir); % Get templates from the user folder userDir = bst_fullfile(bst_get('UserDefaultsDir'), 'anatomy'); userFiles = dir(userDir); % Combine the two lists AllProgNames = cat(2, {progFiles.name}, cellfun(@(c)cat(2,c,'.zip'), {progFiles.name}, 'UniformOutput', 0)); AllFiles = cat(2, cellfun(@(c)bst_fullfile(progDir,c), setdiff({progFiles.name}, {'.','..'}), 'UniformOutput', 0), ... cellfun(@(c)bst_fullfile(userDir,c), setdiff({userFiles.name}, AllProgNames), 'UniformOutput', 0)); % Initialize list of defaults sTemplates = repmat(struct('FilePath',[],'Name',[]), 0); % Find all the valid defaults (.zip files or subdirectory with a brainstormsubject.mat in it) for i = 1:length(AllFiles) % Decompose file name [fPath, fBase, fExt] = bst_fileparts(AllFiles{i}); % Entry is a directory W/ a name that does not start with a '.' if isempty(fBase) || strcmpi(fBase(1),'.') || (~isempty(fExt) && ~strcmpi(fExt, '.zip')) continue; end % If it's a folder: check for a brainstormsubject file if isdir(AllFiles{i}) bstFiles = dir(bst_fullfile(AllFiles{i}, 'brainstormsubject*.mat')); if (length(bstFiles) == 1) sTemplates(end+1).FilePath = AllFiles{i}; sTemplates(end).Name = fBase; end % If it's a zip file elseif isequal(fExt, '.zip') sTemplates(end+1).FilePath = AllFiles{i}; sTemplates(end).Name = fBase; end end % Get defaults from internet if ~ismember('icbm152', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=ICBM152_2023b'; sTemplates(end).Name = 'ICBM152'; end if ~ismember('icbm152_2022', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=ICBM152_2022'; sTemplates(end).Name = 'ICBM152_2022'; end if ~ismember('icbm152_2023b', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=ICBM152_2023b'; sTemplates(end).Name = 'ICBM152_2023b'; end if ~ismember('icbm152_2019', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=ICBM152_2019'; sTemplates(end).Name = 'ICBM152_2019'; end if ~ismember('icbm152_brainsuite_2016', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=ICBM152_BrainSuite_2016'; sTemplates(end).Name = 'ICBM152_BrainSuite_2016'; end if ~ismember('colin27_2016', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=Colin27_2016'; sTemplates(end).Name = 'Colin27_2016'; end if ~ismember('colin27_4nirs_2024', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=Colin27_4NIRS_2024'; sTemplates(end).Name = 'Colin27_4NIRS_2024'; end if ~ismember('colin27_brainsuite_2016', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=Colin27_BrainSuite_2016'; sTemplates(end).Name = 'Colin27_BrainSuite_2016'; end if ~ismember('bci-dni_brainsuite_2020', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=BCI-DNI_BrainSuite_2020'; sTemplates(end).Name = 'BCI-DNI_BrainSuite_2020'; end if ~ismember('uscbrain_brainsuite_2020', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=USCBrain_BrainSuite_2020'; sTemplates(end).Name = 'USCBrain_BrainSuite_2020'; end if ~ismember('fsaverage_2020', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=FSAverage_2020'; sTemplates(end).Name = 'FsAverage_2020'; end if ~ismember('kabdebon_7w', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=Kabdebon_7w'; sTemplates(end).Name = 'Kabdebon_7w'; end if ~ismember('oreilly_0.5m_2021', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=Oreilly_0.5m_2021'; sTemplates(end).Name = 'Oreilly_0.5m_2021'; end if ~ismember('oreilly_1m_2021', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=Oreilly_1m_2021'; sTemplates(end).Name = 'Oreilly_1m_2021'; end if ~ismember('oreilly_2m_2021', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=Oreilly_2m_2021'; sTemplates(end).Name = 'Oreilly_2m_2021'; end if ~ismember(lower({sTemplates.Name}), 'oreilly_3m_2021') sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=Oreilly_3m_2021'; sTemplates(end).Name = 'Oreilly_3m_2021'; end if ~ismember('oreilly_4.5m_2021', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=Oreilly_4.5m_2021'; sTemplates(end).Name = 'Oreilly_4.5m_2021'; end if ~ismember('oreilly_6m_2021', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=Oreilly_6m_2021'; sTemplates(end).Name = 'Oreilly_6m_2021'; end if ~ismember('oreilly_7.5m_2021', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=Oreilly_7.5m_2021'; sTemplates(end).Name = 'Oreilly_7.5m_2021'; end if ~ismember('oreilly_9m_2021', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=Oreilly_9m_2021'; sTemplates(end).Name = 'Oreilly_9m_2021'; end if ~ismember('oreilly_10.5m_2021', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=Oreilly_10.5m_2021'; sTemplates(end).Name = 'Oreilly_10.5m_2021'; end if ~ismember('oreilly_12m_2021', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=Oreilly_12m_2021'; sTemplates(end).Name = 'Oreilly_12m_2021'; end if ~ismember('oreilly_15m_2021', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=Oreilly_15m_2021'; sTemplates(end).Name = 'Oreilly_15m_2021'; end if ~ismember('oreilly_18m_2021', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=Oreilly_18m_2021'; sTemplates(end).Name = 'Oreilly_18m_2021'; end if ~ismember('oreilly_24m_2021', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=Oreilly_24m_2021'; sTemplates(end).Name = 'Oreilly_24m_2021'; end % If a specific template was requested if ~isempty(AnatName) iAnat = find(strcmpi({sTemplates.Name}, AnatName)); sTemplates = sTemplates(iAnat); end % Sort in alphabetical order if ~isempty(sTemplates) [tmp__, I] = sort_nat({sTemplates(2:end).Name}); sTemplates = sTemplates([1, I+1]); end % Return defaults list argout1 = sTemplates; %% ==== MNI ATLASES ==== % Returns the list of all the available MNI atlases case 'MniAtlasDefaults' % Get templates from the brainstorm3 folder mniDir = bst_fullfile(bst_get('UserDefaultsDir'), 'mniatlas'); mniFiles = dir(bst_fullfile(mniDir, '*.nii.gz')); mniFiles = cellfun(@(c)bst_fullfile(mniDir,c), {mniFiles.name}, 'UniformOutput', 0); % Initialize list of defaults sTemplates = repmat(struct('FilePath',[],'Name',[],'Info',[]), 0); % Find all the valid defaults (.zip files or subdirectory with a brainstormsubject.mat in it) for i = 1:length(mniFiles) % Decompose file name [fPath, fBase, fExt] = bst_fileparts(mniFiles{i}); % Keep only files with .nii and .nii.gz extensions if ~isempty(fBase) && (fBase(1) ~= '.') && ~isempty(fExt) && strcmpi(fExt, '.gz') sTemplates(end+1).FilePath = mniFiles{i}; sTemplates(end).Name = strrep(fBase, '.nii', ''); sTemplates(end).Info = ''; end end % Sort in alphabetical order if ~isempty(sTemplates) [tmp__, I] = sort_nat(lower({sTemplates.Name})); sTemplates = sTemplates(I); end % Get defaults from internet if ~ismember('aal1', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=mni_AAL1'; sTemplates(end).Name = 'AAL1'; sTemplates(end).Info = 'https://www.gin.cnrs.fr/en/tools/aal/'; end if ~ismember('aal2', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=mni_AAL2'; sTemplates(end).Name = 'AAL2'; sTemplates(end).Info = 'https://www.gin.cnrs.fr/en/tools/aal/'; end if ~ismember('aal3', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=mni_AAL3'; sTemplates(end).Name = 'AAL3'; sTemplates(end).Info = 'https://www.gin.cnrs.fr/en/tools/aal/'; end if ~ismember('aicha', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=mni_AICHA'; sTemplates(end).Name = 'AICHA'; sTemplates(end).Info = 'https://www.gin.cnrs.fr/en/tools/aicha'; end if ~ismember('brainnetome', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=mni_Brainnetome'; sTemplates(end).Name = 'Brainnetome'; sTemplates(end).Info = 'http://atlas.brainnetome.org/'; end if ~ismember('brainnetome_leaddbs', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=mni_Brainnetome_leaddbs'; sTemplates(end).Name = 'Brainnetome_leaddbs'; sTemplates(end).Info = 'http://atlas.brainnetome.org/'; end if ~ismember('brodmann', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=mni_Brodmann'; sTemplates(end).Name = 'Brodmann'; sTemplates(end).Info = 'https://people.cas.sc.edu/rorden/mricro/lesion.html#brod'; end if ~ismember('hammers83', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=mni_Hammers'; sTemplates(end).Name = 'Hammers'; sTemplates(end).Info = 'http://brain-development.org/brain-atlases/adult-brain-atlases/'; end if ~ismember('neuromorphometrics', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=mni_Neuromorphometrics'; sTemplates(end).Name = 'Neuromorphometrics'; sTemplates(end).Info = 'https://search.kg.ebrains.eu/instances/Dataset/ef48c5e9-6b3c-4d5a-a9a9-e678fe10bdf6'; end if ~ismember('julich-brain-v25', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=mni_Julich-Brain-v25'; sTemplates(end).Name = 'Julich-Brain-v25'; sTemplates(end).Info = 'https://search.kg.ebrains.eu/instances/Dataset/ef48c5e9-6b3c-4d5a-a9a9-e678fe10bdf6'; end if ~ismember('schaefer2018_100_7net', lower({sTemplates.Name})) sTemplates(end+1).FilePath = 'http://neuroimage.usc.edu/bst/getupdate.php?t=mni_Schaefer2018'; sTemplates(end).Name = 'Schaefer2018'; sTemplates(end).Info = 'https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/brain_parcellation/Schaefer2018_LocalGlobal'; end % Return defaults list argout1 = sTemplates; %% ==== EEG DEFAULTS ==== % Returns an array of struct(fullpath, name) of all the Brainstorm eeg nets defaults % Usage: EegDefaults = bst_get('EegDefaults') % EegDefaults = bst_get('EegDefaults', TemplateName=[], SetupName=[]) case 'EegDefaults' % Parse inputs if (nargin >= 3) SetupName = varargin{3}; else SetupName = []; end if (nargin >= 2) TemplateName = varargin{2}; else TemplateName = []; end % Get templates from the brainstorm3 folder progDir = bst_fullfile(bst_get('BrainstormDefaultsDir'), 'eeg'); progFiles = dir(bst_fullfile(progDir, '*')); % Get templates from the user folder userDir = bst_fullfile(bst_get('UserDefaultsDir'), 'eeg'); userFiles = dir(bst_fullfile(userDir, '*')); % Combine the two lists dirList = cat(2, cellfun(@(c)bst_fullfile(progDir,c), {progFiles.name}, 'UniformOutput', 0), ... cellfun(@(c)bst_fullfile(userDir,c), setdiff({userFiles.name}, {progFiles.name}), 'UniformOutput', 0)); % Initialize list of folders fullDefaultsList = repmat(struct('contents','', 'name',''), 0); % For each template directory for iDir = 1:length(dirList) % Decompose file name [fPath, fBase, fExt] = bst_fileparts(dirList{iDir}); % Entry is a not a folder, or starts with a "." if ~isdir(dirList{iDir}) || isempty(fBase) || strcmpi(fBase(1),'.') continue; end % Skip if it is not the requested template if ~isempty(TemplateName) && ~strcmpi(fBase, TemplateName) continue; end % Get files list fileList = dir(bst_fullfile(dirList{iDir}, 'channel*.mat')); defaultsList = repmat(struct('fullpath','', 'name',''), 0); % Find all the valid defaults (channel files) for iFile = 1:length(fileList) [tmp__, baseName] = bst_fileparts(fileList(iFile).name); baseName = strrep(baseName, 'channel_', ''); baseName = strrep(baseName, '_channel', ''); baseName = strrep(baseName, '_', ' '); % Skip if it is not the requested template if ~isempty(SetupName) && ~strcmpi(baseName, SetupName) continue; end % Add to list of templates iNewDefault = length(defaultsList) + 1; defaultsList(iNewDefault).fullpath = bst_fullfile(dirList{iDir}, fileList(iFile).name); defaultsList(iNewDefault).name = baseName; end % Add files list to defaults list if ~isempty(defaultsList) fullDefaultsList(end + 1) = struct('contents', defaultsList, ... 'name', fBase); end end % Return defaults list argout1 = fullDefaultsList; %% ==== GET FILENAMES ==== case 'GetFilenames' iStudies = varargin{2}; iItems = varargin{3}; DataType = varargin{4}; FileNames = cell(1, length(iStudies)); argout1 = {}; for i = 1:length(iStudies) % Get study definition sStudy = bst_get('Study', iStudies(i)); if isempty(sStudy) continue; end % Recordings or sources switch (DataType) case 'data' if (iItems(i) > length(sStudy.Data)) return; end FileNames{i} = sStudy.Data(iItems(i)).FileName; case 'results' if (iItems(i) > length(sStudy.Result)) return; end FileNames{i} = sStudy.Result(iItems(i)).FileName; case 'timefreq' if (iItems(i) > length(sStudy.Timefreq)) return; end FileNames{i} = sStudy.Timefreq(iItems(i)).FileName; case 'matrix' if (iItems(i) > length(sStudy.Matrix)) return; end FileNames{i} = sStudy.Matrix(iItems(i)).FileName; case {'pdata','presults','ptimfreq'} if (iItems(i) > length(sStudy.Stat)) return; end FileNames{i} = sStudy.Stat(iItems(i)).FileName; end end argout1 = FileNames; %% ==== GUI ==== case 'BstFrame' if isempty(GlobalData) || isempty(GlobalData.Program.GUI) || isempty(GlobalData.Program.GUI.mainWindow) argout1 = []; else argout1 = GlobalData.Program.GUI.mainWindow.jBstFrame; end case 'BstControls' if isempty(GlobalData) || isempty(GlobalData.Program) || isempty(GlobalData.Program.GUI) || isempty(GlobalData.Program.GUI.mainWindow) argout1 = []; else argout1 = GlobalData.Program.GUI.mainWindow; end case 'isGUI' if isempty(GlobalData) || isempty(GlobalData.Program) || ~isfield(GlobalData.Program, 'GuiLevel') argout1 = []; else argout1 = (GlobalData.Program.GuiLevel >= 1); end case 'GuiLevel' if isempty(GlobalData) || isempty(GlobalData.Program) || ~isfield(GlobalData.Program, 'GuiLevel') argout1 = []; else argout1 = GlobalData.Program.GuiLevel; end case 'ScreenDef' if isempty(GlobalData) || isempty(GlobalData.Program) || ~isfield(GlobalData.Program, 'ScreenDef') argout1 = []; else argout1 = GlobalData.Program.ScreenDef; end case 'DecorationSize' if isempty(GlobalData) || isempty(GlobalData.Program) || ~isfield(GlobalData.Program, 'DecorationSize') argout1 = []; else argout1 = GlobalData.Program.DecorationSize; end case 'Layout' % Default or current layout structure if ~isfield(GlobalData, 'Preferences') || ~isfield(GlobalData.Preferences, 'Layout') || ~((nargin == 1) || isfield(GlobalData.Preferences.Layout, varargin{2})) || ~isfield(GlobalData.Preferences.Layout, 'MainWindowPos') GlobalData.Preferences.Layout = db_template('Layout'); end % Structure or property call if (nargin == 2) && ischar(varargin{2}) && isfield(GlobalData.Preferences.Layout, varargin{2}) argout1 = GlobalData.Preferences.Layout.(varargin{2}); elseif (nargin == 1) argout1 = GlobalData.Preferences.Layout; else error('Invalid call to bst_get.'); end case 'ByteOrder' if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'ByteOrder') argout1 = GlobalData.Preferences.ByteOrder; else argout1 = 'l'; end case 'UniformizeTimeSeriesScales' if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'UniformizeTimeSeriesScales') argout1 = GlobalData.Preferences.UniformizeTimeSeriesScales; else argout1 = 1; end case 'FlipYAxis' if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'FlipYAxis') argout1 = GlobalData.Preferences.FlipYAxis; else argout1 = 0; end case 'AutoScaleY' if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'AutoScaleY') argout1 = GlobalData.Preferences.AutoScaleY; else argout1 = 1; end case 'ShowXGrid' if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'ShowXGrid') argout1 = GlobalData.Preferences.ShowXGrid; else argout1 = 0; end case 'ShowYGrid' if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'ShowYGrid') argout1 = GlobalData.Preferences.ShowYGrid; else argout1 = 0; end case 'ShowZeroLines' if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'ShowZeroLines') argout1 = GlobalData.Preferences.ShowZeroLines; else argout1 = 1; end case 'Resolution' if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'Resolution') argout1 = GlobalData.Preferences.Resolution; else argout1 = [0 0]; end case 'FixedScaleY' if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'FixedScaleY') && isfield(GlobalData.Preferences.FixedScaleY, varargin{2}) && ~isempty(GlobalData.Preferences.FixedScaleY.(varargin{2})) argout1 = GlobalData.Preferences.FixedScaleY.(varargin{2}); else argout1 = []; end case 'XScale' if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'XScale') argout1 = GlobalData.Preferences.XScale; else argout1 = 'linear'; end case 'YScale' if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'YScale') argout1 = GlobalData.Preferences.YScale; else argout1 = 'linear'; end case 'ShowEventsMode' if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'ShowEventsMode') argout1 = GlobalData.Preferences.ShowEventsMode; else argout1 = 'dot'; end case 'AutoUpdates' if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'AutoUpdates') argout1 = GlobalData.Preferences.AutoUpdates; else argout1 = 1; end case 'ForceMatCompression' if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'ForceMatCompression') argout1 = GlobalData.Preferences.ForceMatCompression; else argout1 = 0; end case 'IgnoreMemoryWarnings' if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'IgnoreMemoryWarnings') argout1 = GlobalData.Preferences.IgnoreMemoryWarnings; else argout1 = 0; end case 'SystemCopy' if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'SystemCopy') argout1 = GlobalData.Preferences.SystemCopy; else argout1 = 0; end case 'ExpertMode' if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'ExpertMode') argout1 = GlobalData.Preferences.ExpertMode; else argout1 = 0; end case 'DisplayGFP' if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'DisplayGFP') argout1 = GlobalData.Preferences.DisplayGFP; else argout1 = 1; end case 'DownsampleTimeSeries' if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'DownsampleTimeSeries') if (GlobalData.Preferences.DownsampleTimeSeries == 1) GlobalData.Preferences.DownsampleTimeSeries = 5; end argout1 = GlobalData.Preferences.DownsampleTimeSeries; else argout1 = 5; end case 'GraphicsSmoothing' if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'GraphicsSmoothing') argout1 = GlobalData.Preferences.GraphicsSmoothing; else argout1 = 5; end case 'DisableOpenGL' if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'DisableOpenGL') argout1 = GlobalData.Preferences.DisableOpenGL; else argout1 = 0; end case 'InterfaceScaling' if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'InterfaceScaling') argout1 = GlobalData.Preferences.InterfaceScaling; else % Get screen resolution if isfield(GlobalData, 'Program') && isfield(GlobalData.Program, 'ScreenDef') && isfield(GlobalData.Program.ScreenDef, 'javaPos') && ~isempty(GlobalData.Program.ScreenDef(1).javaPos) AvailableRes = [100 125 150 200 250 300 400]; iRes = bst_closest(GlobalData.Program.ScreenDef(1).javaPos.width * 100 / 1920, AvailableRes); argout1 = AvailableRes(iRes); else argout1 = 100; end end case 'TSDisplayMode' if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'TSDisplayMode') argout1 = GlobalData.Preferences.TSDisplayMode; else argout1 = 'butterfly'; end case 'PluginCustomPath' if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'PluginCustomPath') && ~isempty(GlobalData.Preferences.PluginCustomPath) argout1 = GlobalData.Preferences.PluginCustomPath; else argout1 = []; end case 'BrainSuiteDir' if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'BrainSuiteDir') && ~isempty(GlobalData.Preferences.BrainSuiteDir) if isdir(GlobalData.Preferences.BrainSuiteDir) && file_exist(bst_fullfile(GlobalData.Preferences.BrainSuiteDir, 'bdp')) argout1 = GlobalData.Preferences.BrainSuiteDir; else argout1 = []; end else argout1 = []; end case 'SpmTpmAtlas' preferSpm = 0; % CALL: bst_get('SpmTpmAtlas', 'SPM') if (nargin >= 2) && strcmpi(varargin{2}, 'SPM') preferSpm = 1; end % Get template file tpmUser = bst_fullfile(bst_get('BrainstormUserDir'), 'defaults', 'spm', 'TPM.nii'); if file_exist(tpmUser) && ~preferSpm argout1 = tpmUser; disp(['BST> SPM12 template found: ' tpmUser]); return; end % If it does not exist: check in brainstorm3 folder tpmDistrib = bst_fullfile(bst_get('BrainstormHomeDir'), 'defaults', 'spm', 'TPM.nii'); if file_exist(tpmDistrib) && ~preferSpm argout1 = tpmDistrib; disp(['BST> SPM12 template found: ' tpmDistrib]); return; end % If it does not exist: check in spm12 folder PlugSpm = bst_plugin('GetInstalled', 'spm12'); if ~isempty(PlugSpm) tpmSpm = bst_fullfile(PlugSpm.Path, PlugSpm.SubFolder, 'tpm', 'TPM.nii'); if file_exist(tpmSpm) argout1 = tpmSpm; disp(['BST> SPM12 template found: ' tpmSpm]); return; elseif preferSpm argout1 = bst_get('SpmTpmAtlas'); return end else tpmSpm = ''; end % Not found... disp('SPM12 template not found in any of the following folders:'); disp([' - ' tpmUser]); disp([' - ' tpmDistrib]); if ~isempty(tpmSpm) disp([' - ' tpmSpm]); end argout1 = []; case 'PythonExe' % Get saved value if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'PythonExe') && ~isempty(GlobalData.Preferences.PythonExe) if file_exist(GlobalData.Preferences.PythonExe) argout1 = GlobalData.Preferences.PythonExe; else disp(['BST> Error: Python executable not found: ' GlobalData.Preferences.PythonExe]); argout1 = []; end else argout1 = []; end % If not defined in Brainstorm, but set in Matlab if isempty(argout1) [pyVer, PythonExe] = bst_python_ver(); if ~isempty(PythonExe) && file_exist(PythonExe) disp(['BST> Found Python executable: ' PythonExe]); argout1 = PythonExe; bst_set('PythonExe', PythonExe); end end case 'ElectrodeConfig' % Get modality Modality = varargin{2}; if isequal(Modality, 'ECOG+SEEG') Modality = 'ECOG_SEEG'; elseif isempty(Modality) || ~ismember(Modality, {'EEG','ECOG','SEEG'}) error(['Invalid modality: ' Modality]); end % Value was saved previously if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'ElectrodeConfig') && isfield(GlobalData.Preferences.ElectrodeConfig, Modality) && isfield(GlobalData.Preferences.ElectrodeConfig.(Modality), 'ContactDiameter') argout1 = GlobalData.Preferences.ElectrodeConfig.(Modality); % Get default value else switch (Modality) case 'EEG' ElectrodeConfig.Type = 'eeg'; ElectrodeConfig.ContactDiameter = 0.010; ElectrodeConfig.ContactLength = 0.002; ElectrodeConfig.ElecDiameter = []; ElectrodeConfig.ElecLength = []; case 'ECOG' ElectrodeConfig.Type = 'ecog'; ElectrodeConfig.ContactDiameter = 0.004; ElectrodeConfig.ContactLength = 0.001; ElectrodeConfig.ElecDiameter = 0.0005; ElectrodeConfig.ElecLength = []; case {'SEEG','ECOG_SEEG'} ElectrodeConfig.Type = 'seeg'; ElectrodeConfig.ContactDiameter = 0.0008; ElectrodeConfig.ContactLength = 0.002; ElectrodeConfig.ElecDiameter = 0.0007; ElectrodeConfig.ElecLength = 0.070; end argout1 = ElectrodeConfig; end case 'ElecInterpDist' % Get modality Modality = varargin{2}; if isequal(Modality, 'ECOG+SEEG') Modality = 'ECOG_SEEG'; elseif isempty(Modality) || ~ismember(Modality, {'EEG','ECOG','SEEG','MEG'}) error(['Invalid modality: ' Modality]); end % Value was saved previously if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'ElecInterpDist') && isfield(GlobalData.Preferences.ElecInterpDist, Modality) argout1 = GlobalData.Preferences.ElecInterpDist.(Modality); % Get default value else switch (Modality) case 'EEG', argout1 = .3; case 'ECOG', argout1 = .015; case 'SEEG', argout1 = .015; case 'ECOG_SEEG', argout1 = .015; case 'MEG', argout1 = .5; end end case 'UseSigProcToolbox' % In a parfor loop: GlobalData is empty => Check only if the toolbox is installed (ignore user preferences) if isempty(GlobalData) || ~isfield(GlobalData, 'Program') || ~isfield(GlobalData.Program, 'HasSigProcToolbox') argout1 = exist('kaiserord', 'file'); else % Save the result of the check for the SigProc tb if isempty(GlobalData.Program.HasSigProcToolbox) % Check if Signal Processing Toolbox is installed GlobalData.Program.HasSigProcToolbox = (exist('kaiserord', 'file') == 2); end % Return user preferences if ~GlobalData.Program.HasSigProcToolbox argout1 = 0; elseif isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'UseSigProcToolbox') argout1 = GlobalData.Preferences.UseSigProcToolbox; else argout1 = 1; end end case 'CustomColormaps' if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'CustomColormaps') && ~isempty(GlobalData.Preferences.CustomColormaps) argout1 = GlobalData.Preferences.CustomColormaps; else argout1 = repmat(struct('Name', '', 'CMap', []), 0); end case 'BFSProperties' if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'BFSProperties') && ~isempty(GlobalData.Preferences.BFSProperties) argout1 = GlobalData.Preferences.BFSProperties; else argout1 = [.33 .0042 .33 .88 .93]; end case 'ShowHiddenFiles' if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'ShowHiddenFiles') argout1 = GlobalData.Preferences.ShowHiddenFiles; else argout1 = 0; end case 'LastUsedDirs' defPref = struct(... 'ImportData', '', ... 'ImportChannel', '', ... 'ImportAnat', '', ... 'ImportMontage', '', ... 'ExportChannel', '', ... 'ExportData', '', ... 'ExportAnat', '', ... 'ExportProtocol', '', ... 'ExportImage', '', ... 'ExportScript', '', ... 'ExportMontage', ''); argout1 = FillMissingFields(contextName, defPref); % Check that all folders are valid fields = fieldnames(argout1); for i = 1:length(fields) if ~ischar(argout1.(fields{i})) || ~file_exist(argout1.(fields{i})) argout1.(fields{i}) = ''; end end case 'DefaultFormats' defPref = struct(... 'AnatIn', 'FreeSurfer', ... 'ChannelIn', '', ... 'ChannelOut', '', ... 'DataIn', 'CTF', ... 'DataOut', '', ... 'DipolesIn', '', ... 'DipolesOut', '', ... 'ImageOut', '', ... 'EventsIn', '', ... 'EventsOut', '', ... 'MriIn', '', ... 'MriOut', 'Nifti1', ... 'NoiseCovIn', '', ... 'NoiseCovOut', '', ... 'ResultsIn', '', ... 'ResultsOut', '', ... 'SpmOut', '', ... 'SspIn', '', ... 'SspOut', '', ... 'SurfaceIn', '', ... 'SurfaceOut', '', ... 'LabelIn', '', ... 'LabelOut', '', ... 'TimefreqIn', '', ... 'TimefreqOut', '', ... 'MatrixIn', '', ... 'MatrixOut', '', ... 'MontageIn', '', ... 'MontageOut', '', ... 'FibersIn', ''); argout1 = FillMissingFields(contextName, defPref); case 'ImportDataOptions' defPref = db_template('ImportOptions'); argout1 = FillMissingFields(contextName, defPref); case 'RawViewerOptions' defPref = struct(... 'PageDuration', 3, ... 'RemoveBaseline', 'all', ... 'UseCtfComp', 1, ... 'Shortcuts', []); defPref.Shortcuts = {... '1', 'event1', 'simple', []; ... % Key, event name, event type (simple,extended,page), epoch time '2', 'event2', 'simple', []; ... '3', 'event3', 'simple', []; ... '4', 'event4', 'simple', []; ... '5', 'event5', 'simple', []; ... '6', 'event6', 'simple', []; ... '7', 'event7', 'simple', []; ... '8', 'event8', 'simple', []; ... '9', 'event9', 'simple', []}; argout1 = FillMissingFields(contextName, defPref); % If invalid PageDuration: reset to default if (argout1.PageDuration <= 0.1) argout1.PageDuration = defPref.PageDuration; end % If old shortcuts: reset to defaults if any(size(argout1.Shortcuts) ~= size(defPref.Shortcuts)) disp('BST> Warning: Reset keyboard shortcuts to include new options.'); argout1.Shortcuts = defPref.Shortcuts; bst_set('RawViewerOptions', argout1); end case 'MontageOptions' defPref = struct('Shortcuts', []); defPref.Shortcuts = { %'a', []; ... Note: A is reserved for All channels 'b', []; ... 'c', []; ... 'd', []; ... 'e', []; ... 'f', []; ... 'g', []; ... 'h', []; ... 'i', []; ... 'j', []; ... 'k', []; ... 'l', []; ... 'm', []; ... 'n', []; ... 'o', []; ... 'p', []; ... 'q', []; ... 'r', []; ... 's', []; ... 't', []; ... 'u', []; ... 'v', []; ... 'w', []; ... 'x', []; ... 'y', []; ... 'z', []; ... }; argout1 = FillMissingFields(contextName, defPref); case 'TopoLayoutOptions' defPref = struct(... 'TimeWindow', [], ... 'FreqWindow', [], ... 'WhiteBackground', 0, ... 'ShowRefLines', 1, ... 'ShowLegend', 1, ... 'FlipYAxis', 0, ... 'ContourLines', 10); argout1 = FillMissingFields(contextName, defPref); case 'StatThreshOptions' defPref = struct(... 'pThreshold', .05, ... 'durThreshold', 0, ... 'Correction', 'fdr', ... 'Control', [1 2 3]); argout1 = FillMissingFields(contextName, defPref); % Make sure that Control is not a string (previous brainstorm version) if ischar(argout1.Control) argout1.Control = defPref.Control; end % Make sure that 'no' is used instead of 'none' (previous brainstorm version) if strcmpi(argout1.Correction, 'none') argout1.Correction = 'no'; end case 'ContactSheetOptions' defPref = struct(... 'nImages', 20, ... 'TimeRange', [], ... 'SkipVolume', 0.2); argout1 = FillMissingFields(contextName, defPref); case 'ProcessOptions' defPref = struct(... 'SavedParam', struct(), ... 'MaxBlockSize', 100 * 1024 * 1024 / 8, ... % 100MiB == 13,107,200 doubles 'LastMaxBlockSize', 100 * 1024 * 1024 / 8); % 100MiB == 13,107,200 doubles argout1 = FillMissingFields(contextName, defPref); case 'ImportEegRawOptions' defPref = struct(... 'isCanceled', 0, ... 'BaselineDuration', 0, ... 'SamplingRate', 1000, ... 'MatrixOrientation', 'channelXtime', ... % {'channelXtime', 'timeXchannel'} 'VoltageUnits', 'V', ... % {'\muV', 'mV', 'V'} 'SkipLines', 0, ... 'nAvg', 1, ... 'isChannelName', 0); % 1 if the first entry contains the channel name argout1 = FillMissingFields(contextName, defPref); case 'BugReportOptions' defPref = struct(... 'isEnabled', 0, ... 'SmtpServer', 'mailhost.chups.jussieu.fr', ... 'UserEmail', ''); argout1 = FillMissingFields(contextName, defPref); case 'DefaultSurfaceDisplay' defPref = struct(... 'SurfShowSulci', 1, ... 'SurfSmoothValue', 0, ... 'DataThreshold', 0.5, ... 'SizeThreshold', 1, ... 'DataAlpha', 0); argout1 = FillMissingFields(contextName, defPref); case 'MagneticExtrapOptions' defPref = struct(... 'ForceWhitening', 0, ... 'EpsilonValue', 0.0001); argout1 = FillMissingFields(contextName, defPref); case 'DefaultFreqBands' argout1 = {... 'delta', '2, 4', 'mean'; ... 'theta', '5, 7', 'mean'; ... 'alpha', '8, 12', 'mean'; ... 'beta', '15, 29', 'mean'; ... 'gamma1', '30, 59', 'mean'; ... 'gamma2', '60, 90', 'mean'}; case 'TimefreqOptions_morlet' defPref.isTimeBands = 0; defPref.isFreqBands = 0; defPref.isFreqLog = 0; defPref.TimeBands = {}; defPref.Freqs = '1:1:60'; defPref.FreqsLog = '1:40:150'; defPref.FreqBands = bst_get('DefaultFreqBands'); defPref.Measure = 'power'; defPref.SaveKernel = 0; defPref.Output = 'all'; defPref.RemoveEvoked = 0; defPref.ClusterFuncTime = 'after'; defPref.MorletFc = 1; defPref.MorletFwhmTc = 3; argout1 = FillMissingFields(contextName, defPref); if isempty(argout1.Freqs) argout1.Freqs = defPref.Freqs; end if ~isempty(argout1.FreqBands) && ((size(argout1.FreqBands,2) ~= 3) || ~all(cellfun(@ischar, argout1.FreqBands(:))) || any(cellfun(@(c)isempty(strtrim(c)), argout1.FreqBands(:)))) argout1.FreqBands = defPref.FreqBands; end case 'TimefreqOptions_hilbert' defPref.isTimeBands = 0; defPref.isFreqBands = 1; defPref.isFreqLog = 0; defPref.TimeBands = {}; defPref.Freqs = []; defPref.FreqsLog = []; defPref.FreqBands = bst_get('DefaultFreqBands'); defPref.Measure = 'power'; defPref.SaveKernel = 0; defPref.Output = 'all'; defPref.RemoveEvoked = 0; defPref.ClusterFuncTime = 'after'; argout1 = FillMissingFields(contextName, defPref); if isempty(argout1.Freqs) argout1.Freqs = defPref.Freqs; end if ~isempty(argout1.FreqBands) && (size(argout1.FreqBands,2) == 3) && ~ischar(argout1.FreqBands{1,2}) argout1.FreqBands = defPref.FreqBands; end case 'TimefreqOptions_plv' % not used defPref.isTimeBands = 0; defPref.isFreqBands = 1; defPref.isFreqLog = 0; defPref.TimeBands = {}; defPref.Freqs = []; defPref.FreqsLog = []; defPref.FreqBands = bst_get('DefaultFreqBands'); defPref.Measure = 'other'; defPref.SaveKernel = 0; defPref.Output = 'all'; defPref.ClusterFuncTime = 'after'; argout1 = FillMissingFields(contextName, defPref); if isempty(argout1.Freqs) argout1.Freqs = defPref.Freqs; end if ~isempty(argout1.FreqBands) && ~ischar(argout1.FreqBands{1,2}) argout1.FreqBands = defPref.FreqBands; end case 'TimefreqOptions_fft' defPref.isTimeBands = 0; defPref.isFreqBands = 0; defPref.isFreqLog = 0; defPref.TimeBands = {}; defPref.Freqs = []; defPref.FreqsLog = []; defPref.FreqBands = bst_get('DefaultFreqBands'); defPref.Measure = 'power'; defPref.Output = 'all'; defPref.ClusterFuncTime = 'after'; argout1 = FillMissingFields(contextName, defPref); if isempty(argout1.Freqs) argout1.Freqs = defPref.Freqs; end if ~isempty(argout1.FreqBands) && ~ischar(argout1.FreqBands{1,2}) argout1.FreqBands = defPref.FreqBands; end case 'TimefreqOptions_psd' defPref.isTimeBands = 0; defPref.isFreqBands = 0; defPref.isFreqLog = 0; defPref.TimeBands = {}; defPref.Freqs = []; defPref.FreqsLog = []; defPref.FreqBands = bst_get('DefaultFreqBands'); defPref.Measure = 'power'; defPref.Output = 'all'; defPref.ClusterFuncTime = 'after'; argout1 = FillMissingFields(contextName, defPref); if isempty(argout1.Freqs) argout1.Freqs = defPref.Freqs; end if ~isempty(argout1.FreqBands) && ~ischar(argout1.FreqBands{1,2}) argout1.FreqBands = defPref.FreqBands; end case 'TimefreqOptions_stft' defPref.isTimeBands = 0; defPref.isFreqBands = 0; defPref.isFreqLog = 0; defPref.TimeBands = {}; defPref.Freqs = []; defPref.FreqsLog = []; defPref.FreqBands = bst_get('DefaultFreqBands'); defPref.Measure = 'power'; defPref.Output = 'all'; defPref.ClusterFuncTime = 'after'; defPref.StftWinLen = 1; defPref.StftWinOvr = 0; defPref.StftFrqMax = 0; argout1 = FillMissingFields(contextName, defPref); if isempty(argout1.Freqs) argout1.Freqs = defPref.Freqs; end if ~isempty(argout1.FreqBands) && ~ischar(argout1.FreqBands{1,2}) argout1.FreqBands = defPref.FreqBands; end case 'ExportBidsOptions' defPref.ProjName = []; defPref.ProjID = []; defPref.ProjDesc = []; defPref.Categories = []; defPref.JsonDataset = ['{' 10 ' "License": "PD"' 10 '}']; defPref.JsonMeg = ['{' 10 ' "TaskDescription": "My task"' 10 '}']; argout1 = FillMissingFields(contextName, defPref); case 'OpenMEEGOptions' defPref.BemFiles = {}; defPref.BemNames = {'Scalp', 'Skull', 'Brain'}; defPref.BemCond = [1, 0.0125, 1]; defPref.BemSelect = [1 1 1]; defPref.isAdjoint = 0; defPref.isAdaptative = 1; defPref.isSplit = 0; defPref.SplitLength = 4000; argout1 = FillMissingFields(contextName, defPref); case 'DuneuroOptions' defPref = duneuro_defaults(); argout1 = FillMissingFields(contextName, defPref); case 'GridOptions_dipfit' defPref = struct(... 'Method', 'isotropic', ... 'nLayers', 17, ... 'Reduction', 3, ... 'nVerticesInit', 4000, ... 'Resolution', 0.020, ... 'FileName', ''); argout1 = FillMissingFields(contextName, defPref); case 'GridOptions_headmodel' defPref = struct(... 'Method', 'isotropic', ... 'nLayers', 17, ... 'Reduction', 3, ... 'nVerticesInit', 4000, ... 'Resolution', 0.005, ... 'FileName', ''); argout1 = FillMissingFields(contextName, defPref); case 'MriOptions' defPref = struct(... 'isRadioOrient', 0, ... 'isMipAnatomy', 0, ... 'isMipFunctional', 0, ... 'OverlaySmooth', 0, ... 'InterpDownsample', 3, ... 'DistanceThresh', 6, ... 'UpsampleImage', 0, ... 'DefaultAtlas', []); argout1 = FillMissingFields(contextName, defPref); case 'DigitizeOptions' defPref = struct(... 'PatientId', 'S001', ... 'ComPort', 'COM1', ... 'ComRate', 9600, ... 'ComByteCount', 94, ... % 47 bytes * 2 receivers 'UnitType', 'fastrak', ... 'ConfigCommands', [], ... % setup-specific device configuration commands, e.g. hemisphere of operation 'nFidSets', 2, ... 'Fids', {{'NAS', 'LPA', 'RPA'}}, ... % 3 anat points (required) and any other, e.g. MEG coils, in desired digitization order 'DistThresh', 0.005, ... % 5 mm distance threshold between repeated measures of fid positions 'isBeep', 1, ... 'isMEG', 1, ... 'isSimulate', 0, ... 'Montages', [... struct('Name', 'No EEG', ... 'Labels', [], ... 'ChannelFile', []), ... struct('Name', 'Default', ... 'Labels', [], ... 'ChannelFile', [])], ... 'iMontage', 1, ... 'Version', '2024'); % Version of the Digitize panel: 'legacy' or '2024' argout1 = FillMissingFields(contextName, defPref); case 'PcaOptions' defPref.Method = 'pca'; % deprecated legacy per-file with sign inconsistencies, but kept as default for reproducibility defPref.Baseline = [-.1, 0]; % not used for 'pca': full window instead defPref.DataTimeWindow = [0, 1]; % not used for 'pca': full window instead defPref.RemoveDcOffset = 'file'; argout1 = FillMissingFields(contextName, defPref); case 'ConnectGraphOptions' % Get interface scaling factor InterfaceScaling = bst_get('InterfaceScaling'); % Get default values defPref = struct(... 'LobeFullLabel', 1, ... 'TextDisplayMode', [1 2], ... 'LabelSize', 7 .* InterfaceScaling ./ 100, ... 'NodeSize', 5 .* InterfaceScaling ./ 100, ... 'LinkSize', 1.5 .* InterfaceScaling ./ 100, ... 'BgColor', [0 0 0], ... 'HierarchyNodeIsVisible', 1); % If we have an additional argument, get the default values if nargin > 1 argout1 = defPref; % Otherwise, get the saved values else savedValues = FillMissingFields(contextName, defPref); % if any of the fields are [], replace by default value % do it here to avoid touching the common FillMissingFields % function, as other tools may actually want to set [] as desired property fields = fieldnames(savedValues); for i=1:numel(fields) if(isempty(savedValues.(fields{i}))) savedValues.(fields{i}) = defPref.(fields{i}); end end argout1 = savedValues; end case 'NodelistOptions' defPref = struct(... 'String', '', ... % What to search for 'Target', 'Comment', ... % What field to search for: {'FileName', 'Comment'} 'Action', 'Select'); % What to do with the filtered files: {'Select', 'Exclude'} argout1 = FillMissingFields(contextName, defPref); case 'ReadOnly' if isfield(GlobalData.DataBase, 'isReadOnly') argout1 = GlobalData.DataBase.isReadOnly; else argout1 = 0; end case 'LastPsdDisplayFunction' if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'LastPsdDisplayFunction') argout1 = GlobalData.Preferences.LastPsdDisplayFunction; else argout1 = []; end case 'PlotlyCredentials' % Get saved username and API key try creds = loadplotlycredentials(); argout1 = creds.username; argout2 = creds.api_key; catch argout1 = ''; argout2 = ''; end % Get saved domain try config = loadplotlyconfig(); argout3 = config.plotly_domain; catch argout3 = ''; end case 'KlustersExecutable' if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, 'KlustersExecutable') argout1 = GlobalData.Preferences.KlustersExecutable; else argout1 = []; end %% ===== FILE FILTERS ===== case 'FileFilters' switch lower(varargin{2}) case 'mri' argout1 = {... {'.img'}, 'MRI: Analyze (*.img/*.hdr)', 'Analyze'; ... {'.ima'}, 'MRI: BrainVISA GIS (*.ima/*.dim)', 'GIS'; ... {'.ima'}, 'MRI: BrainVISA GIS (*.ima/*.dim)', 'GIS'; ... {'.mri'}, 'MRI: CTF (*.mri)', 'CTF'; ... {'.mat'}, 'MRI: FieldTrip (*.mat)', 'FT-MRI'; ... {'.mgh','.mgz'}, 'MRI: MGH (*.mgh,*.mgz)', 'MGH'; ... {'.mnc', '.mni'}, 'MRI: MNI (*.mnc,*.mni)', 'MINC'; ... {'.nii','.gz'}, 'MRI: NIfTI-1 (*.nii;*.nii.gz)', 'Nifti1'; ... {'_subjectimage'}, 'MRI: Brainstorm (*subjectimage*.mat)', 'BST'; ... {'*'}, 'MRI: DICOM (SPM converter)', 'DICOM-SPM'; ... {'.mri', '.fif', '.img', '.ima', '.nii', '.mgh', '.mgz', '.mnc', '.mni', '.gz', '_subjectimage'}, 'All MRI files (subject space)', 'ALL'; ... {'.mri', '.fif', '.img', '.ima', '.nii', '.mgh', '.mgz', '.mnc', '.mni', '.gz', '_subjectimage'}, 'All MRI files (MNI space)', 'ALL-MNI'; ... {'.mri', '.fif', '.img', '.ima', '.nii', '.mgh', '.mgz', '.mnc', '.mni', '.gz', '_subjectimage'}, 'Volume atlas (subject space)', 'ALL-ATLAS'; ... {'.mri', '.fif', '.img', '.ima', '.nii', '.mgh', '.mgz', '.mnc', '.mni', '.gz', '_subjectimage'}, 'Volume atlas (MNI space)', 'ALL-MNI-ATLAS'; ... }; case 'mriout' argout1 = {... {'.img'}, 'MRI: Analyze (*.img/*.hdr)', 'Analyze'; ... {'.ima'}, 'MRI: BrainVISA GIS (*.ima/*.dim)', 'GIS'; ... {'.mri'}, 'MRI: CTF (*.mri)', 'CTF'; ... {'.mat'}, 'MRI: FieldTrip (*.mat)', 'FT-MRI'; ... {'.nii'}, 'MRI: NIfTI-1 (*.nii)', 'Nifti1'... }; case 'anatin' argout1 = {... {'.folder'}, 'FreeSurfer', 'FreeSurfer-fast'; ... {'.folder'}, 'FreeSurfer + Volume atlases', 'FreeSurfer'; ... {'.folder'}, 'FreeSurfer + Volume atlases + Thickness', 'FreeSurfer+Thick'; ... {'.folder'}, 'BrainSuite', 'BrainSuite-fast'; ... {'.folder'}, 'BrainSuite + Volume atlases', 'BrainSuite'; ... {'.folder'}, 'BrainVISA', 'BrainVISA'; ... {'.folder'}, 'CAT12', 'CAT12'; ... {'.folder'}, 'CAT12 + Thickness', 'CAT12+Thick'; ... {'.folder'}, 'CIVET', 'CIVET'; ... {'.folder'}, 'CIVET + Thickness', 'CIVET+Thick'; ... {'.folder'}, 'HCP MEG/anatomy (pipeline v3)', 'HCPv3'; ... {'.folder'}, 'SimNIBS', 'SimNIBS'; ... }; case 'source4d' argout1 = {... {'.folder'}, 'NIfTI-1 (*.nii)', 'Nifti1';... {'.folder'}, 'Analyze (*.img/*.hdr)', 'Analyze'; ... {'.folder'}, 'Matlab 4D matrix (*voltime*.mat)', 'BST'; ... }; case 'surface' argout1 = {... {'.mesh'}, 'BrainVISA (*.mesh)', 'MESH'; ... {'_tess', '_head', '_scalp', '_brain', '_cortex', '_innerskull', '_outerskull'}, 'Brainstorm (*.mat)', 'BST'; ... {'.dfs'}, 'BrainSuite (*.dfs)', 'DFS'; ... {'.dsgl'}, 'BrainSuite old (*.dsgl)', 'DSGL'; ... {'.bd0','.bd1','.bd2','.bd3','.bd4','.bd5','.bd6','.bd7','.bd8','.bd9', ... '.s00','.s01','.s02','.s03','.s04','.s05','.s06','.s07','.s08','.s09'}, ... 'Curry BEM (*.db*;*.s0*)', 'CURRY-BEM'; {'.vtk'}, 'FSL: VTK (*.vtk)', 'VTK'; ... {'*'}, 'FreeSurfer (*.*)', 'FS'; {'.off'}, 'Geomview OFF (*.off)', 'OFF'; ... {'.gii'}, 'GIfTI / MRI coordinates (*.gii)', 'GII'; ... {'.gii'}, 'GIfTI / MNI coordinates (*.gii)', 'GII-MNI'; ... {'.gii'}, 'GIfTI / World coordinates (*.gii)', 'GII-WORLD'; ... {'.fif'}, 'MNE (*.fif)', 'FIF'; ... {'.obj'}, 'MNI OBJ (*.obj)', 'MNIOBJ'; ... {'.obj'}, 'Wavefront OBJ (*.obj)', 'WFTOBJ'; ... {'.msh'}, 'SimNIBS3/headreco Gmsh4 (*.msh)', 'SIMNIBS3'; ... {'.msh'}, 'SimNIBS4/charm Gmsh4 (*.msh)', 'SIMNIBS4'; ... {'.tri'}, 'TRI (*.tri)', 'TRI'; ... {'.mri', '.fif', '.img', '.ima', '.nii', '.mgh', '.mgz', '.mnc', '.mni', '.gz', '_subjectimage'}, 'Volume mask or atlas (subject space)', 'MRI-MASK'; ... {'.mri', '.fif', '.img', '.ima', '.nii', '.mgh', '.mgz', '.mnc', '.mni', '.gz'}, 'Volume mask or atlas (MNI space)', 'MRI-MASK-MNI'; ... {'.nwbaux'}, 'Neurodata Without Borders (*.nwbaux)', 'NWB'; ... {'*'}, 'All surface files (*.*)', 'ALL'; ... }; case 'surfaceout' argout1 = {... {'.mesh'}, 'BrainVISA (*.mesh)', 'MESH'; ... {'.dfs'}, 'BrainSuite (*.dfs)', 'DFS'; ... {'.fs'}, 'FreeSurfer (*.fs)', 'FS'; ... {'.obj'}, 'Wavefront OBJ (*.obj)', 'OBJ'; ... {'.off'}, 'Geomview OFF (*.off)', 'OFF'; ... {'.gii'}, 'GIfTI (*.gii)', 'GII'; ... {'.tri'}, 'TRI (*.tri)', 'TRI'; ... }; case 'data' argout1 = {... {'.*'}, 'MEG/EEG: 4D-Neuroimaging/BTi (*.*)', '4D'; ... {'.meg4','.res4'}, 'MEG/EEG: CTF (*.ds;*.meg4;*.res4)', 'CTF'; ... {'.fif'}, 'MEG/EEG: Elekta-Neuromag (*.fif)', 'FIF'; ... {'.mat'}, 'MEG/EEG: FieldTrip (*.mat)', 'FT-TIMELOCK'; ... {'.raw'}, 'MEG/EEG: ITAB (*.raw)', 'ITAB'; ... {'.kdf'}, 'MEG/EEG: KRISS MEG (*.kdf)', 'KDF'; ... {'.mrk','.sqd','.con','.raw','.ave'}, 'MEG/EEG: Ricoh (*.sqd;*.con;*.raw;*.ave;*.mrk)', 'RICOH'; ... {'.mat'}, 'MEG/EEG: SPM (*.mat/.dat)', 'SPM-DAT'; ... {'.mrk','.sqd','.con','.raw','.ave'}, 'MEG/EEG: Yokogawa/KIT (*.sqd;*.con;*.raw;*.ave;*.mrk)', 'KIT'; ... {'.meghdf5'}, 'MEG/EEG: York Instruments MEGSCAN (.meghdf5)', 'MEGSCAN-HDF5'; ... {'.bst'}, 'MEG/EEG: Brainstorm binary (*.bst)', 'BST-BIN'; ... {'.adicht'}, 'EEG: ADInstruments LabChart (*.adicht)', 'EEG-ADICHT'; ... {'.msr'}, 'EEG: ANT ASA (*.msr)', 'EEG-ANT-MSR'; ... {'.cnt','.avr'}, 'EEG: ANT EEProbe (*.cnt;*.avr)', 'EEG-ANT-CNT'; ... {'*'}, 'EEG: ASCII text (*.*)', 'EEG-ASCII'; ... {'.raw'}, 'EEG: Axion AxIS (*.raw)', 'EEG-AXION'; ... {'.dat'}, 'EEG: BCI2000 (*.dat)', 'EEG-BCI2000'; ... {'.bdf'}, 'EEG: BDF (*.bdf)', 'EEG-BDF'; ... {'.avr','.mux','.mul'}, 'EEG: BESA exports (*.avr;*.mul;*.mux)', 'EEG-BESA'; ... {'.acq'}, 'EEG: BIOPAC AcqKnowledge (*.acq)', 'EEG-BIOPAC'; ... {'.ns1','.ns2','.ns3','.ns4','.ns5','.ns6'}, 'EEG: Blackrock NeuroPort (*.nsX/*.nev)', 'EEG-BLACKROCK'; {'.eeg','.dat'}, 'EEG: BrainVision BrainAmp (*.eeg;*.dat)', 'EEG-BRAINAMP'; ... {'.txt'}, 'EEG: BrainVision Analyzer (*.txt)', 'EEG-BRAINVISION'; ... {'.sef','.ep','.eph'}, 'EEG: Cartool (*.sef;*.ep;*.eph)', 'EEG-CARTOOL'; ... {'.dat','.cdt'}, 'EEG: Curry (*.dat;*.cdt)', 'EEG-CURRY'; ... {'.smr','.son'}, 'EEG: CED Spike2 old 32bit (*.smr;*.son)', 'EEG-SMR'; ... {'.smr','.smrx'}, 'EEG: CED Spike2 new 64bit (*.smr;*.smrx)', 'EEG-SMRX'; ... {'.rda'}, 'EEG: Compumedics ProFusion Sleep (*.rda)', 'EEG-COMPUMEDICS-PFS'; ... {'.bin'}, 'EEG: Deltamed Coherence-Neurofile (*.bin)', 'EEG-DELTAMED'; ... {'.edf','.rec'}, 'EEG: EDF / EDF+ (*.rec;*.edf)', 'EEG-EDF'; ... {'.edf','.rec'}, 'EEG EDF / EDF+ FieldTrip reader (*.rec;*.edf)', 'EEG-EDF-FT'; ... {'.set'}, 'EEG: EEGLAB (*.set)', 'EEG-EEGLAB'; ... {'.raw'}, 'EEG: EGI Netstation RAW (*.raw)', 'EEG-EGI-RAW'; ... {'.mff','.bin'}, 'EEG: EGI-Philips (*.mff)', 'EEG-EGI-MFF'; ... {'.edf'}, 'EEG: EmotivPRO (*.edf)', 'EEG-EMOTIV'; ... {'.erp','.hdr'}, 'EEG: ERPCenter (*.hdr;*.erp)', 'EEG-ERPCENTER'; ... {'.erp'}, 'EEG: ERPLab (*.erp)', 'EEG-ERPLAB'; ... {'.mat','.hdf5'}, 'EEG: g.tec Matlab (*.mat,*.hdf5)', 'EEG-GTEC'; ... {'.rhd','.rhs'}, 'EEG: Intan (*.rhd,*.rhs)', 'EEG-INTAN'; ... {'.mb2'}, 'EEG: MANSCAN (*.mb2)', 'EEG-MANSCAN'; ... {'.trc'}, 'EEG: Micromed (*.trc)', 'EEG-MICROMED'; ... {'.mat'}, 'EEG: Matlab matrix (*.mat)', 'EEG-MAT'; ... {'.csv'}, 'EEG: Muse (*.csv)', 'EEG-MUSE-CSV'; ... {'.ncs'}, 'EEG: Neuralynx (*.ncs)', 'EEG-NEURALYNX'; ... {'.nwb'}, 'EEG: Neurodata Without Borders (*.nwb)','NWB'; ... {'.nedf','.easy'}, 'EEG: Neuroelectrics (*.nedf;*.easy)', 'EEG-NEUROELECTRICS'; ... {'.bin'}, 'EEG: NeurOne session folder', 'EEG-NEURONE'; ... {'.cnt','.avg','.eeg','.dat'}, 'EEG: Neuroscan (*.cnt;*.eeg;*.avg;*.dat)', 'EEG-NEUROSCAN'; ... {'.eeg','.dat'}, 'EEG: NeuroScope (*.eeg;*.dat)', 'EEG-NEUROSCOPE'; ... {'.e'}, 'EEG: Nicolet (*.e)', 'EEG-NICOLET'; ... {'.eeg'}, 'EEG: Nihon Kohden (*.eeg)', 'EEG-NK'; ... {'.dat'}, 'EEG: Open Ephys flat binary (*.dat)', 'EEG-OEBIN'; ... {'.plx','.pl2'}, 'EEG: Plexon (*.plx;*.pl2)', 'EEG-PLEXON'; ... {'.ns1','.ns2','.ns3','.ns4','.ns5','.ns6'}, 'EEG: Ripple Trellis (*.nsX/*.nev)', 'EEG-RIPPLE'; ... {'.h5'}, 'EEG: The Virtual Brain (*_TimeSeriesEEG.h5)', 'EEG-TVB'; ... {'.csv'}, 'EEG: Wearable Sensing (*.csv)', 'EEG-WS-CSV'; ... {'.xdf'}, 'EEG: XDF (*.xdf)', 'EEG-XDF'; ... {'.nirs'}, 'NIRS: Brainsight (*.nirs)', 'NIRS-BRS'; ... {'.bnirs','.jnirs','.snirf'}, 'NIRS: SNIRF (*.snirf)', 'NIRS-SNIRF'; ... {'.edf'}, 'Eye tracker: EyeLink (*.edf)', 'EYELINK'; ... {'.tsv'}, 'Eye tracker: Tobii glasses (*.tsv)', 'EYE-TOBII-TSV'; ... }; case 'raw' argout1 = {... {'.*'}, 'MEG/EEG: 4D-Neuroimaging/BTi (*.*)', '4D'; ... {'.meg4','.res4'}, 'MEG/EEG: CTF (*.ds;*.meg4;*.res4)', 'CTF'; ... {'.fif'}, 'MEG/EEG: Elekta-Neuromag (*.fif)', 'FIF'; ... {'.mat'}, 'MEG/EEG: FieldTrip (*.mat)', 'FT-TIMELOCK'; ... {'.raw'}, 'MEG/EEG: ITAB (*.raw)', 'ITAB'; ... {'.kdf'}, 'MEG/EEG: KRISS MEG (*.kdf)', 'KDF'; ... {'.mrk','.sqd','.con','.raw','.ave'}, 'MEG/EEG: Ricoh (*.sqd;*.con;*.raw;*.ave;*.mrk)', 'RICOH'; ... {'.mat'}, 'MEG/EEG: SPM (*.mat/.dat)', 'SPM-DAT'; ... {'.mrk','.sqd','.con','.raw','.ave'}, 'MEG/EEG: Yokogawa/KIT (*.sqd;*.con;*.raw;*.ave;*.mrk)', 'KIT'; ... {'.meghdf5'}, 'MEG/EEG: York Instruments MEGSCAN (.meghdf5)', 'MEGSCAN-HDF5'; ... {'.bst'}, 'MEG/EEG: Brainstorm binary (*.bst)', 'BST-BIN'; ... {'.adicht'}, 'EEG: ADInstruments LabChart (*.adicht)', 'EEG-ADICHT'; ... {'.msr'}, 'EEG: ANT ASA (*.msr)', 'EEG-ANT-MSR'; ... {'.cnt','.avr'}, 'EEG: ANT EEProbe (*.cnt;*.avr)', 'EEG-ANT-CNT'; ... {'*'}, 'EEG: ASCII text (*.*)', 'EEG-ASCII'; ... {'.raw'}, 'EEG: Axion AxIS (*.raw)', 'EEG-AXION'; ... {'.dat'}, 'EEG: BCI2000 (*.dat)', 'EEG-BCI2000'; ... {'.bdf'}, 'EEG: BDF (*.bdf)', 'EEG-BDF'; ... {'.avr','.mux','.mul'}, 'EEG: BESA exports (*.avr;*.mul;*.mux)', 'EEG-BESA'; ... {'.acq'}, 'EEG: BIOPAC AcqKnowledge (*.acq)', 'EEG-BIOPAC'; ... {'.ns1','.ns2','.ns3','.ns4','.ns5','.ns6'}, 'EEG: Blackrock NeuroPort (*.nsX/*.nev)', 'EEG-BLACKROCK'; {'.eeg','.dat'}, 'EEG: BrainVision BrainAmp (*.eeg;*.dat)', 'EEG-BRAINAMP'; ... {'.txt'}, 'EEG: BrainVision Analyzer (*.txt)', 'EEG-BRAINVISION'; ... {'.sef','.ep','.eph'}, 'EEG: Cartool (*.sef;*.ep;*.eph)', 'EEG-CARTOOL'; ... {'.smr','.son'}, 'EEG: CED Spike2 old 32bit (*.smr;*.son)', 'EEG-SMR'; ... {'.smr','.smrx'}, 'EEG: CED Spike2 new 64bit (*.smr;*.smrx)', 'EEG-SMRX'; ... {'.rda'}, 'EEG: Compumedics ProFusion Sleep (*.rda)', 'EEG-COMPUMEDICS-PFS'; ... {'.dat','.cdt'}, 'EEG: Curry (*.dat;*.cdt)', 'EEG-CURRY'; ... {'.bin'}, 'EEG: Deltamed Coherence-Neurofile (*.bin)', 'EEG-DELTAMED'; ... {'.edf','.rec'}, 'EEG: EDF / EDF+ (*.rec;*.edf)', 'EEG-EDF'; ... {'.edf','.rec'}, 'EEG EDF / EDF+ FieldTrip reader (*.rec;*.edf)', 'EEG-EDF-FT'; ... {'.set'}, 'EEG: EEGLAB (*.set)', 'EEG-EEGLAB'; ... {'.raw'}, 'EEG: EGI Netstation RAW (*.raw)', 'EEG-EGI-RAW'; ... {'.mff','.bin'}, 'EEG: EGI-Philips (*.mff)', 'EEG-EGI-MFF'; ... {'.edf'}, 'EEG: EmotivPRO (*.edf)', 'EEG-EMOTIV'; ... {'.mat','.hdf5'}, 'EEG: g.tec Matlab (*.mat,*.hdf5)', 'EEG-GTEC'; ... {'.rhd','.rhs'}, 'EEG: Intan (*.rhd,*.rhs)', 'EEG-INTAN'; ... {'.mb2'}, 'EEG: MANSCAN (*.mb2)', 'EEG-MANSCAN'; ... {'.mat'}, 'EEG: Matlab matrix (*.mat)', 'EEG-MAT'; ... {'.csv'}, 'EEG: Muse (*.csv)', 'EEG-MUSE-CSV'; ... {'.trc'}, 'EEG: Micromed (*.trc)', 'EEG-MICROMED'; ... {'.ncs'}, 'EEG: Neuralynx (*.ncs)', 'EEG-NEURALYNX'; ... {'.nwb'}, 'EEG: Neurodata Without Borders (*.nwb)','NWB'; ... {'.nedf','.easy'}, 'EEG: Neuroelectrics (*.nedf;*.easy)', 'EEG-NEUROELECTRICS'; ... {'.bin'}, 'EEG: NeurOne session folder', 'EEG-NEURONE'; ... {'.cnt','.avg','.eeg','.dat'}, 'EEG: Neuroscan (*.cnt;*.eeg;*.avg;*.dat)', 'EEG-NEUROSCAN'; ... {'.eeg','.dat'}, 'EEG: NeuroScope (*.eeg;*.dat)', 'EEG-NEUROSCOPE'; ... {'.e'}, 'EEG: Nicolet (*.e)', 'EEG-NICOLET'; ... {'.eeg'}, 'EEG: Nihon Kohden (*.eeg)', 'EEG-NK'; ... {'.dat'}, 'EEG: Open Ephys flat binary (*.dat)', 'EEG-OEBIN'; ... {'.plx','.pl2'}, 'EEG: Plexon (*.plx;.pl2)' 'EEG-PLEXON'; ... {'.ns1','.ns2','.ns3','.ns4','.ns5','.ns6'}, 'EEG: Ripple Trellis (*.nsX/*.nev)', 'EEG-RIPPLE'; ... {'.h5'}, 'EEG: The Virtual Brain (*_TimeSeriesEEG.h5)', 'EEG-TVB'; ... {'.tbk'}, 'EEG: Tucker Davis Technologies (*.tbk)', 'EEG-TDT'; ... {'.csv'}, 'EEG: Wearable Sensing (*.csv)', 'EEG-WS-CSV'; ... {'.xdf'}, 'EEG: XDF (*.xdf)', 'EEG-XDF'; ... {'.trc','.eeg','.e','.bin','.rda','.edf','.bdf'}, 'SEEG: Deltamed/Micromed/NK/Nicolet/BrainVision/EDF', 'SEEG-ALL'; ... {'.trc','.eeg','.e','.bin','.rda','.edf','.bdf'}, 'ECOG: Deltamed/Micromed/NK/Nicolet/BrainVision/EDF', 'ECOG-ALL'; ... {'.nirs'}, 'NIRS: Brainsight (*.nirs)', 'NIRS-BRS'; ... {'.bnirs','.jnirs','.snirf'}, 'NIRS: SNIRF (*.snirf)', 'NIRS-SNIRF'; ... {'.edf'}, 'Eye tracker: EyeLink (*.edf)', 'EYELINK'; ... {'.tsv'}, 'Eye tracker: Tobii glasses (*.tsv)', 'EYE-TOBII-TSV'; ... }; case 'dataout' argout1 = {... {'.bst'}, 'MEG/EEG: Brainstorm binary (*.bst)', 'BST-BIN'; ... {'.mat'}, 'MEG/EEG: FieldTrip timelock (*.mat)', 'FT-TIMELOCK'; ... {'.mat'}, 'MEG/EEG: SPM (*.mat/.dat)', 'SPM-DAT'; ... {'.eeg'}, 'EEG: BrainVision BrainAmp (*.eeg)', 'EEG-BRAINAMP'; ... {'.eph'}, 'EEG: Cartool EPH (*.eph)', 'EEG-CARTOOL-EPH'; ... {'.edf'}, 'EEG: EDF+ (*.edf)', 'EEG-EDF'; ... {'.raw'}, 'EEG: EGI NetStation RAW (*.raw)', 'EEG-EGI-RAW'; ... {'.snirf'}, 'NIRS: SNIRF (*.snirf)', 'NIRS-SNIRF'; ... {'.txt'}, 'ASCII: Space-separated, fixed column size (*.txt)', 'ASCII-SPC'; ... {'.txt'}, 'ASCII: Space-separated with header, fixed column size (*.txt)', 'ASCII-SPC-HDR'; ... {'.tsv'}, 'ASCII: Tab-separated (*.tsv)', 'ASCII-TSV'; ... {'.tsv'}, 'ASCII: Tab-separated with header (*.tsv)', 'ASCII-TSV-HDR'; ... {'.tsv'}, 'ASCII: Tab-separated with header transposed (*.tsv)', 'ASCII-TSV-HDR-TR'; ... {'.csv'}, 'ASCII: Comma-separated (*.csv)', 'ASCII-CSV'; ... {'.csv'}, 'ASCII: Comma-separated with header (*.csv)', 'ASCII-CSV-HDR'; ... {'.csv'}, 'ASCII: Comma-separated with header transposed (*.csv)', 'ASCII-CSV-HDR-TR'; ... {'.xlsx'}, 'Microsoft Excel (*.xlsx)', 'EXCEL'; ... {'.xlsx'}, 'Microsoft Excel transposed (*.xlsx)', 'EXCEL-TR'; ... {'_timeseries'}, 'Brainstorm matrix (*timeseries*.mat)', 'BST'; ... }; case 'rawout' argout1 = {... {'.bst'}, 'MEG/EEG: Brainstorm binary (*.bst)', 'BST-BIN'; ... {'.mat'}, 'MEG/EEG: SPM (*.mat/.dat)', 'SPM-DAT'; ... {'.eeg'}, 'EEG: BrainVision BrainAmp (*.eeg)', 'EEG-BRAINAMP'; ... {'.edf'}, 'EEG: EDF+ (*.edf)', 'EEG-EDF'; ... {'.raw'}, 'EEG: EGI NetStation RAW (*.raw)', 'EEG-EGI-RAW'; ... {'.snirf'}, 'NIRS: SNIRF (*.snirf)', 'NIRS-SNIRF'; ... }; case 'events' argout1 = {... {'.trg'}, 'ANT EEProbe (*.trg)', 'ANT'; ... {'.mrk'}, 'AnyWave (*.mrk)', 'ANYWAVE'; ... {'.evt'}, 'BESA (*.evt)', 'BESA'; ... {'.tsv'}, 'BIDS events: onset, duration, trial_type, channel (*.tsv)', 'BIDS'; ... {'.vmrk'}, 'BrainVision BrainAmp (*.vmrk)', 'BRAINAMP'; ... {'_events'}, 'Brainstorm (events*.mat)', 'BST'; ... {'.mrk'}, 'Cartool (*.mrk)', 'CARTOOL'; ... {'.mrk'}, 'CTF MarkerFile (*.mrk)', 'CTF'; ... {'.cef'}, 'Curry (*.cef)', 'CURRY'; ... {'.eve','.fif'}, 'Elekta-Neuromag MNE (*.eve;*.fif)', 'FIF'; ... {'.evl','.txt'}, 'Elekta-Neuromag Graph (*.evl;*.txt)', 'GRAPH'; ... {'.txt','.mat'}, 'FieldTrip trial definition (*.txt;*.mat)', 'TRL'; ... {'.trg'}, 'KRISS MEG (*.trg)', 'KDF'; ... {'.evt'}, 'Micromed (*.evt)', 'MICROMED'; ... {'.ev2'}, 'Neuroscan (*.ev2)', 'NEUROSCAN'; ... {'.txt'}, 'Nicolet export (*.txt)', 'NICOLET'; ... {'timestamps.npy'},'Open Ephys (timestamps.npy)', 'OEBIN'; ... {'.log'}, 'Presentation (*.log)', 'PRESENTATION'; ... {'.mrk','.sqd','.con','.raw','.ave'}, 'Ricoh (*.mrk;*.sqd;*.con;*.raw;*.ave)', 'RICOH'; ... {'.txt'}, 'XLTEK export (*.txt)', 'XLTEK'; ... {'.mrk','.sqd','.con','.raw','.ave'}, 'Yokogawa/KIT (*.mrk;*.sqd;*.con;*.raw;*.ave)', 'KIT'; ... {'.*'}, 'Array of times (*.mat;*.*)', 'ARRAY-TIMES'; ... {'.*'}, 'Array of samples (*.mat;*.*)', 'ARRAY-SAMPLES'; ... {'.txt','.csv'}, 'CSV text file: label, time, duration (*.txt;*.csv)', 'CSV-TIME'; ... {'.*'}, 'CTF Video Times (.txt)', 'CTFVIDEO'; ... }; case 'eventsout' argout1 = {... {'.mrk'}, 'AnyWave (*.mrk)', 'ANYWAVE'; ... {'_events'}, 'Brainstorm (events*.mat)', 'BST'; ... {'.vmrk'}, 'BrainVision BrainAmp (*.vmrk)', 'BRAINAMP'; ... {'.mrk'}, 'CTF MarkerFile (*.mrk)', 'CTF'; ... {'.eve','.fif'}, 'Elekta-Neuromag/MNE (*.eve)', 'FIF'; ... {'.evl'}, 'Elekta-Neuromag Graph (Alternative Style) (*.evl)', 'GRAPH_ALT'; ... {'.txt'}, 'Array of times (*.txt)', 'ARRAY-TIMES'; ... {'.txt'}, 'Array of samples (*.txt)', 'ARRAY-SAMPLES'; ... {'.txt','.csv'}, 'CSV text file: label, time, duration (*.txt;*.csv)', 'CSV-TIME'; ... {'.txt'}, 'CTF Video Times (*.txt)', 'CTFVIDEO'; ... {'.tsv'}, 'BIDS events: onset, duration, trial_type (*.tsv)', 'BIDS'; ... }; case 'channel' argout1 = {... {'.*'}, 'MEG/EEG: 4D-Neuroimaging/BTi (*.*)', '4D'; ... {'.meg4','.res4'}, 'MEG/EEG: CTF (*.ds;*.meg4;*.res4)', 'CTF' ; ... {'.fif'}, 'MEG/EEG: Elekta-Neuromag (*.fif)', 'FIF'; ... {'.kdf'}, 'MEG/EEG: KRISS MEG (*.kdf)', 'KDF'; ... {'.raw'}, 'MEG/EEG: ITAB (*.raw)', 'ITAB'; ... {'.mrk','.sqd','.con','.raw','.ave'}, 'MEG/EEG: Ricoh (*.sqd;*.con;*.raw;*.ave;*.mrk)', 'RICOH'; ... {'.mrk','.sqd','.con','.raw','.ave'}, 'MEG/EEG: Yokogawa/KIT (*.sqd;*.con;*.raw;*.ave;*.mrk)', 'KIT'; ... {'.meghdf5'}, 'MEG/EEG: York Instruments MEGSCAN (.meghdf5)', 'MEGSCAN-HDF5'; ... {'.bst'}, 'MEG/EEG: Brainstorm binary (*.bst)', 'BST-BIN'; ... {'_channel'}, 'MEG/EEG: Brainstorm (channel*.mat)', 'BST'; ... {'.elc'}, 'EEG: ANT ASA/Xensor (*.elc)', 'XENSOR'; ... {'.sfp','.elp','.ela','.eps'}, 'EEG: BESA (*.sfp;*.elp;*.eps/*.ela)', 'BESA'; ... {'.bvef','.bvct','.txt'}, 'EEG: BrainVision electrode file (*.bvef,*.bvct,*.txt)', 'BRAINVISION'; ... {'.tsv'}, 'EEG: BIDS electrodes.tsv, subject space mm (*.tsv)', 'BIDS-SCANRAS-MM'; ... {'.tsv'}, 'EEG: BIDS electrodes.tsv, MNI space mm (*.tsv)', 'BIDS-MNI-MM'; ... {'.tsv'}, 'EEG: BIDS electrodes.tsv, ACPC space mm (*.tsv)', 'BIDS-ACPC-MM'; ... {'.tsv'}, 'EEG: BIDS electrodes.tsv, ALS/SCS/CTF space mm (*.tsv)','BIDS-ALS-MM'; ... {'.tsv'}, 'EEG: BIDS electrodes.tsv, CapTrak space mm (*.tsv)', 'BIDS-CAPTRAK-MM'; ... {'.els','.xyz'}, 'EEG: Cartool (*.els;*.xyz)', 'CARTOOL'; ... {'.eeg'}, 'EEG: MegDraw (*.eeg)', 'MEGDRAW'; ... {'.res','.rs3','.pom'}, 'EEG: Curry, LPS (*.res;*.rs3;*.pom)', 'CURRY'; ... {'.ced','.xyz','.set'}, 'EEG: EEGLAB (*.ced;*.xyz;*.set)', 'EEGLAB'; ... {'.elc'}, 'EEG: EETrak (*.elc)', 'EETRAK'; ... {'.sfp'}, 'EEG: EGI (*.sfp)', 'EGI'; ... {'coordinates.xml'}, 'EEG: EGI-Philips (coordinates.xml)', 'MFF'; ... {'.elp'}, 'EEG: EMSE (*.elp)', 'EMSE'; ... {'.pts','.csv'}, 'EEG: IntrAnat, subject space (*.pts;*.csv)', 'INTRANAT'; ... {'.pts','.csv'}, 'EEG: IntrAnat, MNI space (*.pts;*.csv)', 'INTRANAT_MNI'; ... {'.csv'}, 'EEG: Localite (*.csv)', 'LOCALITE'; ... {'.dat','.tri','.txt','.asc'}, 'EEG: Neuroscan (*.dat;*.tri;*.txt;*.asc)', 'NEUROSCAN'; ... {'.pos','.pol','.elp','.txt'}, 'EEG: Polhemus (*.pos;*.pol;*.elp;*.txt)', 'POLHEMUS'; ... {'.csv'}, 'EEG: SimNIBS (*.csv)', 'SIMNIBS'; ... {'.h5'}, 'EEG: The Virtual Brain (*_SensorsEEG.h5)', 'TVB'; ... {'*'}, 'EEG: ASCII: Name,XYZ (*.*)', 'ASCII_NXYZ'; ... {'*'}, 'EEG: ASCII: Name,XYZ_MNI (*.*)', 'ASCII_NXYZ_MNI'; ... {'*'}, 'EEG: ASCII: Name,XYZ_World (*.*)', 'ASCII_NXYZ_WORLD'; ... {'*'}, 'EEG: ASCII: Name,XY (*.*)', 'ASCII_NXY'; ... {'*'}, 'EEG: ASCII: XYZ (*.*)', 'ASCII_XYZ'; ... {'*'}, 'EEG: ASCII: XYZ_MNI (*.*)', 'ASCII_XYZ_MNI'; ... {'*'}, 'EEG: ASCII: XYZ_World (*.*)', 'ASCII_XYZ_WORLD'; ... {'*'}, 'EEG: ASCII: XY (*.*)', 'ASCII_XY'; ... {'*'}, 'EEG: ASCII: XYZ,Name (*.*)', 'ASCII_XYZN'; ... {'*'}, 'EEG: ASCII: XYZ_MNI,Name (*.*)', 'ASCII_XYZN_MNI'; ... {'*'}, 'EEG: ASCII: XYZ_World,Name (*.*)', 'ASCII_XYZN_WORLD'; ... {'*'}, 'EEG: ASCII: Name,Theta,Phi (*.*)', 'ASCII_NTP'; ... {'*'}, 'EEG: ASCII: Theta,Phi (*.*)', 'ASCII_TP'; ... }; case 'channelout' argout1 = {... {'.pos'}, 'EEG+Headshape: Polhemus (*.pos)', 'POLHEMUS'; ... {'.eeg'}, 'Headshape: MegDraw (*.eeg)', 'MEGDRAW'; ... {'.pos'}, 'Headshape: Polhemus (*.pos)', 'POLHEMUS-HS'; ... {'.txt'}, 'Headshape: ASCII: XYZ (*.txt)', 'ASCII_XYZ-HS'; ... {'.txt'}, 'Headshape: ASCII: XYZ_World (*.txt)', 'ASCII_XYZ_WORLD-HS'; ... {'.txt'}, 'Headshape: ASCII: Name,XYZ (*.txt)', 'ASCII_NXYZ-HS'; ... {'.txt'}, 'Headshape: ASCII: Name,XYZ_World (*.txt)', 'ASCII_NXYZ_WORLD-HS'; ... {'.txt'}, 'Headshape: ASCII: XYZ,Name (*.txt)', 'ASCII_XYZN-HS'; ... {'.txt'}, 'Headshape: ASCII: XYZ_World,Name (*.txt)', 'ASCII_XYZN_WORLD-HS'; ... {'.sfp'}, 'EEG: BESA (*.sfp)', 'BESA-SFP'; ... {'.elp'}, 'EEG: BESA (*.elp)', 'BESA-ELP'; ... {'.tsv'}, 'EEG: BIDS electrodes.tsv, subject space mm (*.tsv)', 'BIDS-SCANRAS-MM'; ... {'.tsv'}, 'EEG: BIDS electrodes.tsv, MNI space mm (*.tsv)', 'BIDS-MNI-MM'; ... {'.tsv'}, 'EEG: BIDS electrodes.tsv, ALS/SCS/CTF space mm (*.tsv)', 'BIDS-ALS-MM'; ... {'.xyz'}, 'EEG: Cartool (*.xyz)', 'CARTOOL-XYZ'; ... {'.res'}, 'EEG: Curry (*.res)', 'CURRY-RES'; ... {'.xyz'}, 'EEG: EEGLAB (*.xyz)', 'EEGLAB-XYZ'; ... {'.sfp'}, 'EEG: EGI (*.sfp)', 'EGI'; ... {'.txt'}, 'EEG/NIRS: ASCII: XYZ (*.txt)', 'ASCII_XYZ-EEG'; ... {'.txt'}, 'EEG/NIRS: ASCII: XYZ_MNI (*.txt)', 'ASCII_XYZ_MNI-EEG'; ... {'.txt'}, 'EEG/NIRS: ASCII: XYZ_World (*.txt)', 'ASCII_XYZ_WORLD-EEG'; ... {'.txt'}, 'EEG/NIRS: ASCII: Name,XYZ (*.txt)', 'ASCII_NXYZ-EEG'; ... {'.txt'}, 'EEG/NIRS: ASCII: Name,XYZ_MNI (*.txt)', 'ASCII_NXYZ_MNI-EEG'; ... {'.txt'}, 'EEG/NIRS: ASCII: Name,XYZ_World (*.txt)', 'ASCII_NXYZ_WORLD-EEG'; ... {'.txt'}, 'EEG/NIRS: ASCII: XYZ,Name (*.txt)', 'ASCII_XYZN-EEG'; ... {'.txt'}, 'EEG/NIRS: ASCII: XYZ_MNI,Name (*.txt)', 'ASCII_XYZN_MNI-EEG'; ... {'.txt'}, 'EEG/NIRS: ASCII: XYZ_World,Name (*.txt)', 'ASCII_XYZN_WORLD-EEG'; ... {'.txt'}, 'EEG/NIRS: Brainsight (*.txt)', 'BRAINSIGHT-TXT'; ... {'.tsv'}, 'NIRS: BIDS optrodes.tsv, subject space mm (*.tsv)', 'BIDS-NIRS-SCANRAS-MM'; ... {'.tsv'}, 'NIRS: BIDS optrodes.tsv, MNI space mm (*.tsv)', 'BIDS-NIRS-MNI-MM'; ... {'.tsv'}, 'NIRS: BIDS optrodes.tsv, ALS/SCS/CTF space mm (*.tsv)', 'BIDS-NIRS-ALS-MM'; ... }; case 'labelin' argout1 = {... {'.dfs'}, 'BrainSuite atlas (*.dfs)', 'DFS'; ... {'.annot'}, 'FreeSurfer atlas (*.annot)', 'FS-ANNOT'; ... {'.label'}, 'FreeSurfer ROI, single scout (*.label)', 'FS-LABEL-SINGLE'; ... {'.label'}, 'FreeSurfer ROI, probability map (*.label)', 'FS-LABEL'; ... {'.gii'}, 'GIfTI texture (*.gii)', 'GII-TEX'; ... {'.dset'}, 'SUMA atlas (*.dset)', 'DSET'; ... {'_scout'}, 'Brainstorm scouts (*scout*.mat)', 'BST'; ... {'.mri', '.fif', '.img', '.ima', '.nii', '.mgh', '.mgz', '.mnc', '.mni', '.gz', '_subjectimage'}, 'Volume mask or atlas (dilated, subject space)', 'MRI-MASK'; ... {'.mri', '.fif', '.img', '.ima', '.nii', '.mgh', '.mgz', '.mnc', '.mni', '.gz'}, 'Volume mask or atlas (dilated, MNI space)', 'MRI-MASK-MNI'; ... {'.mri', '.fif', '.img', '.ima', '.nii', '.mgh', '.mgz', '.mnc', '.mni', '.gz', '_subjectimage'}, 'Volume mask or atlas (no overlap, subject space)', 'MRI-MASK-NOOVERLAP'; ... {'.mri', '.fif', '.img', '.ima', '.nii', '.mgh', '.mgz', '.mnc', '.mni', '.gz'}, 'Volume mask or atlas (no overlap, MNI space)', 'MRI-MASK-NOOVERLAP-MNI'; ... }; case 'resultsout' argout1 = {... {'_sources'}, 'Brainstorm sources (*sources*.mat)', 'BST'; ... {'.mat'}, 'FieldTrip sources (*.mat)', 'FT-SOURCES'; ... {'.txt'}, 'ASCII: Space-separated, fixed columns size (*.txt)', 'ASCII-SPC'; ... {'.txt'}, 'ASCII: Space-separated with header, fixed column size (*.txt)', 'ASCII-SPC-HDR'; ... {'.tsv'}, 'ASCII: Tab-separated (*.tsv)', 'ASCII-TSV'; ... {'.tsv'}, 'ASCII: Tab-separated with header (*.tsv)', 'ASCII-TSV-HDR'; ... {'.tsv'}, 'ASCII: Tab-separated with header transposed (*.tsv)', 'ASCII-TSV-HDR-TR'; ... {'.csv'}, 'ASCII: Comma-separated (*.csv)', 'ASCII-CSV'; ... {'.csv'}, 'ASCII: Comma-separated with header (*.csv)', 'ASCII-CSV-HDR'; ... {'.csv'}, 'ASCII: Comma-separated with header transposed (*.csv)', 'ASCII-CSV-HDR-TR'; ... {'.xlsx'}, 'Microsoft Excel (*.xlsx)', 'EXCEL'; ... {'.xlsx'}, 'Microsoft Excel transposed (*.xlsx)', 'EXCEL-TR'; ... }; case 'timefreqout' argout1 = {... {'_timefreq'}, 'Brainstorm structure (*timefreq*.mat)', 'BST'; ... {'.mat'}, 'FieldTrip freq (*.mat)', 'FT-FREQ'; ... {'.txt'}, 'ASCII: Space-separated, fixed columns size (*.txt)', 'ASCII-SPC'; ... {'.txt'}, 'ASCII: Space-separated with header, fixed column size (*.txt)', 'ASCII-SPC-HDR'; ... {'.tsv'}, 'ASCII: Tab-separated (*.tsv)', 'ASCII-TSV'; ... {'.tsv'}, 'ASCII: Tab-separated with header (*.tsv)', 'ASCII-TSV-HDR'; ... {'.tsv'}, 'ASCII: Tab-separated with header transposed (*.tsv)', 'ASCII-TSV-HDR-TR'; ... {'.csv'}, 'ASCII: Comma-separated (*.csv)', 'ASCII-CSV'; ... {'.csv'}, 'ASCII: Comma-separated with header (*.csv)', 'ASCII-CSV-HDR'; ... {'.csv'}, 'ASCII: Comma-separated with header transposed (*.csv)', 'ASCII-CSV-HDR-TR'; ... {'.xlsx'}, 'Microsoft Excel (*.xlsx)', 'EXCEL'; ... {'.xlsx'}, 'Microsoft Excel transposed (*.xlsx)', 'EXCEL-TR'; ... }; case 'matrixout' argout1 = {... {'_matrix'}, 'Brainstorm structure (*matrix*.mat)', 'BST'; ... {'.bst'}, 'MEG/EEG: Brainstorm binary (*.bst)', 'BST-BIN'; ... {'.mat'}, 'FieldTrip timelock (*.mat)', 'FT-TIMELOCK'; ... {'.edf'}, 'EEG: EDF+ (*.edf)', 'EEG-EDF'; ... {'.txt'}, 'ASCII: Space-separated, fixed columns size (*.txt)', 'ASCII-SPC'; ... {'.txt'}, 'ASCII: Space-separated with header, fixed column size (*.txt)', 'ASCII-SPC-HDR'; ... {'.tsv'}, 'ASCII: Tab-separated (*.tsv)', 'ASCII-TSV'; ... {'.tsv'}, 'ASCII: Tab-separated with header (*.tsv)', 'ASCII-TSV-HDR'; ... {'.tsv'}, 'ASCII: Tab-separated with header transposed (*.tsv)', 'ASCII-TSV-HDR-TR'; ... {'.csv'}, 'ASCII: Comma-separated (*.csv)', 'ASCII-CSV'; ... {'.csv'}, 'ASCII: Comma-separated with header (*.csv)', 'ASCII-CSV-HDR'; ... {'.csv'}, 'ASCII: Comma-separated with header transposed (*.csv)', 'ASCII-CSV-HDR-TR'; ... {'.xlsx'}, 'Microsoft Excel (*.xlsx)', 'EXCEL'; ... {'.xlsx'}, 'Microsoft Excel transposed (*.xlsx)', 'EXCEL-TR'; ... }; case 'montagein' argout1 = {... {'.sel'}, 'MNE selection files (*.sel)', 'MNE'; ... {'.mon'}, 'Text montage files (*.mon)', 'MON'; ... {'_montage'}, 'Brainstorm montage files (montage_*.mat)', 'BST'; {'.csv'}, 'Comma-separated montage files (*.csv)', 'CSV'}; case 'montageout' argout1 = {... {'.sel'}, 'MNE selection files (*.sel)', 'MNE'; ... {'.mon'}, 'Text montage files (*.mon)', 'MON'; ... {'_montage'}, 'Brainstorm montage files (montage_*.mat)', 'BST'}; case 'clusterin' argout1 = {... {'_cluster'}, 'Brainstorm clusters file (*cluster*.mat)', 'BST'; ... {'.sel'}, 'MNE selection files (*.sel)', 'MNE'}; case 'fibers' argout1 = {... {'.trk'}, 'TrackVis (*.trk)', 'TRK'; ... {'_fibers'}, 'Brainstorm fibers files (fibers_*.mat)', 'BST'}; end %% ===== FONTS ===== case 'FigFont' if ispc argout1 = 8; else argout1 = 9; end InterfaceScaling = bst_get('InterfaceScaling'); if (InterfaceScaling ~= 100) argout1 = argout1 * InterfaceScaling / 100; end case 'Font' % Default font size if (nargin < 2) if strncmp(computer,'MAC',3) fontSize = 12; else fontSize = 11; end % Font size in input else fontSize = varargin{2}; end % Adjust for interface scaling fontSize = fontSize * bst_get('InterfaceScaling') / 100; % Font types fontTypes = {}; if (nargin >= 3) if ischar(varargin{3}) fontTypes = varargin(3); else fontTypes = varargin{3}; end else fontTypes{end + 1} = 'Arial'; % Default font fontTypes{end + 1} = 'Liberation Sans'; % Free Arial substitute end % Check for cached font foundFont = 0; for iFont = 1 : length(fontTypes) strCache = strrep(sprintf('%s%d', fontTypes{iFont}, round(fontSize*100)), ' ', '_'); if ~isempty(GlobalData) && isfield(GlobalData, 'Program') && isfield(GlobalData.Program, 'FontCache') && isfield(GlobalData.Program.FontCache, strCache) argout1 = GlobalData.Program.FontCache.(strCache); foundFont = 1; break; end end % If font not cached, find first supported font if ~foundFont ge = java.awt.GraphicsEnvironment.getLocalGraphicsEnvironment(); allFonts = cell(ge.getAvailableFontFamilyNames()); for iFont = 1 : length(fontTypes) if any(strcmp(fontTypes{iFont}, allFonts)) fontType = fontTypes{iFont}; foundFont = 1; break; end end if ~foundFont fontType = 'SansSerif'; % If nothing else works. end strCache = strrep(sprintf('%s%d', fontType, round(fontSize*100)), ' ', '_'); argout1 = java.awt.Font(fontType, java.awt.Font.PLAIN, fontSize); GlobalData.Program.FontCache.(strCache) = argout1; end %% ==== PANEL CONTAINERS ==== case 'PanelContainer' % Get Brainstorm GUI context structure bst_GUI = GlobalData.Program.GUI; if (isempty(bst_GUI) || ~isfield(bst_GUI, 'panelContainers')) error('Brainstorm GUI is not yet initialized'); end % Get ContainerName in argument if ((nargin >= 2) && (ischar(varargin{2}))) ContainerName = varargin{2}; % If no container name in argument : just display all the container names else disp('Registered panel containers :'); for iContainer = 1:length(bst_GUI.panelContainers) disp([' - ' bst_GUI.panelContainers(iContainer).name]); end return end % Look for containerName in all the registered panel containers iContainer = 1; found = 0; while (~found (iContainer <= length(bst_GUI.panelContainers))) if (strcmpi(ContainerName, bst_GUI.panelContainers(iContainer).name)) found = 1; else iContainer = iContainer + 1; end end % If container is found : return it if (found) argout1 = bst_GUI.panelContainers(iContainer).jHandle; else % warning('Brainstorm:InvalidContainer', 'Container ''%s'' could not be found.', ContainerName); end %% ==== PANELS ==== case 'Panel' % Get Brainstorm GUI context structure if (isempty(GlobalData) || isempty(GlobalData.Program.GUI) || ~isfield(GlobalData.Program.GUI, 'panels')) return end listPanels = GlobalData.Program.GUI.panels; % Get Panel in argument if ((nargin >= 2) && (ischar(varargin{2}))) PanelName = varargin{2}; % If no panel name in argument : just display all the panels names else disp('Registered panels :'); for iContainer = 1:length(listPanels) disp([' - ' get(listPanels(iContainer), 'name')]); end return end % Look for panelName in all the registered panels iPanel = find(strcmpi(PanelName, get(listPanels, 'name')), 1); if ~isempty(iPanel) argout1 = listPanels(iPanel); argout2 = iPanel; end %% ==== PANEL CONTROLS ==== % Calls : bst_get('PanelControls', PanelName) case 'PanelControls' % Get Panel name in argument if ((nargin >= 2) && (ischar(varargin{2}))) PanelName = varargin{2}; else error('Invalid call to bst_get()'); end % Find BstPanel with this name bstPanel = bst_get('Panel', PanelName); % If panel was found : return its controls if ~isempty(bstPanel) argout1 = get(bstPanel, 'sControls'); end %% ===== NODES COPY ===== % Calls : bst_get('Clipboard') case 'Clipboard' argout1 = GlobalData.Program.Clipboard.Nodes; argout2 = GlobalData.Program.Clipboard.isCut; %% ==== DIRECTORIES ==== case 'DirDefaultSubject' argout1 = '@default_subject'; case 'DirDefaultStudy' argout1 = '@default_study'; case 'DirAnalysisIntra' argout1 = '@intra'; case 'DirAnalysisInter' argout1 = '@inter'; case 'NormalizedSubjectName' argout1 = 'Group_analysis'; %% ==== OTHER ==== case 'ResizeFunction' if (bst_get('MatlabVersion') <= 803) argout1 = 'ResizeFcn'; else argout1 = 'SizeChangedFcn'; end case 'groot' if (bst_get('MatlabVersion') <= 803) argout1 = 0; else argout1 = groot; end case 'JFrame' hFig = varargin{2}; MatlabVersion = bst_get('MatlabVersion'); jFrame = []; try if (MatlabVersion <= 705) jf = get(hFig, 'javaframe'); jFrame = jf.fFigureClient.getWindow(); elseif (MatlabVersion <= 712) jf = get(handle(hFig), 'javaframe'); jFrame = jf.fFigureClient.getWindow(); elseif (MatlabVersion <= 803) jf = get(handle(hFig), 'javaframe'); jFrame = jf.fHG1Client.getWindow(); elseif (MatlabVersion < 907) % Matlab >= 2019b deprecated the JavaFrame property warning('off', 'MATLAB:HandleGraphics:ObsoletedProperty:JavaFrame'); jf = get(hFig, 'javaframe'); warning('on', 'MATLAB:HandleGraphics:ObsoletedProperty:JavaFrame'); jFrame = jf.fHG2Client.getWindow(); else disp('BST> Error: Matlab 2019b deprecated the JavaFrame property.'); end catch disp('BST> Warning: Cannot get the JavaFrame property for the selected figure.'); end argout1 = jFrame; %% ==== ERROR ==== otherwise error(sprintf('Invalid context : "%s"', contextName)); %% ==== HELPERS ==== % Return all the protocol studies that have a given file in its structures % Possible field names: Result.DataFile, Result.FileName, Data.FileName, Channel.FileName % % USAGE: [sFoundStudy, iFoundStudy, iItem] = findFileInStudies(fieldGroup, fieldName, fieldFile, iStudiesList) % [sFoundStudy, iFoundStudy, iItem] = findFileInStudies(fieldGroup, fieldName, fieldFile) function [sFoundStudy, iFoundStudy, iItem] = findFileInStudies(fieldGroup, fieldName, fieldFile, iStudiesList) global GlobalData; sFoundStudy = []; iFoundStudy = []; iItem = []; % If no file provided, return if isempty(fieldFile) return; end % Extract folder(s) of the file(s) we're looking for fieldParts = strfind(fieldFile, '|'); if ~isempty(fieldParts) fieldParts(end+1) = length(fieldFile); fieldFolders = {}; iLast = 1; for iPart = 1:length(fieldParts) folder = fileparts(fieldFile(iLast:fieldParts(iPart)-1)); if ~isempty(folder) fieldFolders{end + 1} = folder; end iLast = fieldParts(iPart) + 1; end else fieldFolders = {fileparts(fieldFile)}; end % Get protocol information ProtocolStudies = GlobalData.DataBase.ProtocolStudies(GlobalData.DataBase.iProtocol); % List studies to process if (nargin < 4) || isempty(iStudiesList) iStudiesList = [-2, -3, 1:length(ProtocolStudies.Study)]; end % NORMAL STUDIES: Look for surface file in all the surfaces of all subjects for iStudy = iStudiesList % Get study switch (iStudy) case -2, sStudy = ProtocolStudies.AnalysisStudy; case -3, sStudy = ProtocolStudies.DefaultStudy; otherwise, sStudy = ProtocolStudies.Study(iStudy); end % Check if field is available for the study if isempty(sStudy.(fieldGroup)) continue; end % Check we are in the correct folder if ~any(file_compare(fieldFolders, fileparts(sStudy.FileName))) continue; end % Get list of files from study filesList = {sStudy.(fieldGroup).(fieldName)}; if isempty(filesList) continue; end % Replace empty cells with empty strings iValidFiles = find(cellfun(@ischar, filesList)); if isempty(iValidFiles) continue; end % Find target in this list iItem = find(file_compare(filesList(iValidFiles), fieldFile)); if ~isempty(iItem) sFoundStudy = sStudy; iFoundStudy = iStudy; iItem = iValidFiles(iItem); return end end %% ===== FILL MISSING FIELDS ===== function bstPref = FillMissingFields(PrefName, defPref) global GlobalData; if isfield(GlobalData, 'Preferences') && isfield(GlobalData.Preferences, PrefName) && isstruct(GlobalData.Preferences.(PrefName)) bstPref = GlobalData.Preferences.(PrefName); bstPref = struct_copy_fields(bstPref, defPref, 0); else bstPref = defPref; end id="line-453">

database structures: bst_set.m.
1 function bst_set( varargin ) % BST_SET: Set a Brainstorm structure. % % DESCRIPTION: This function is used to abstract the way that these structures are stored. % % USAGE: % ====== DIRECTORIES ================================================================== % - bst_set('BrainstormHomeDir', BrainstormHomeDir) % - bst_set('BrainstormTmpDir', BrainstormTmpDir) % - bst_set('BrainstormDbDir', BrainstormDbDir) % - bst_set('LastUsedDirs', sDirectories) % - bst_set('BrainSuiteDir', BrainSuiteDir) % - bst_set('PythonExe', PythonExe) % - bst_set('PluginCustomPath', PluginCustomPath) % % ====== PROTOCOLS ==================================================================== % - bst_set('iProtocol', iProtocol) % - bst_set('ProtocolInfo', sProtocolInfo) % - bst_set('ProtocolSubjects', ProtocolSubjects) % - bst_set('isProtocolLoaded', isProtocolLoaded) % - bst_set('isProtocolModified',isProtocolModified) % - bst_set('ProtocolStudies', ProtocolStudies) % - bst_set('Study', iStudy, sStudy) : Set a study in current protocol % - bst_set('Subject', iSubject, sSubject) : Set a subject in current protocol % % ====== GUI ================================================================= % - bst_set('Layout', sLayout) % - bst_set('Layout', PropName, PropValue) % - bst_set('Clipboard', Nodes, isCut) : Copy operation from the tree % % ====== CONFIGURATION ================================================================= % - bst_set('Version', Version) % - bst_set('ByteOrder', value) : 'b' for big endian, 'l' for little endian % - bst_set('AutoUpdates', isAutoUpdates) % - bst_set('ExpertMode', isExpertMode) % - bst_set('DisplayGFP', isDisplayGFP) % - bst_set('DownsampleTimeSeries', isDownsampleTimeSeries) % - bst_set('GraphicsSmoothing', isGraphicsSmoothing) % - bst_set('ForceMatCompression', isForceCompression) % - bst_set('IgnoreMemoryWarnings', isIgnoreMemoryWarnings) % - bst_set('SystemCopy', isSystemCopy) % - bst_set('DisableOpenGL', isDisableOpenGL) % - bst_set('InterfaceScaling', InterfaceScaling) % - bst_set('TSDisplayMode', TSDisplayMode) : {'butterfly','column'} % - bst_set('ElectrodeConfig', ElectrodeConfig, Modality) % - bst_set('ElecInterpDist', ElecInterpDist, Modality) % - bst_set('DefaultFormats' defaultFormats) % - bst_set('BFSProperties', [scalpCond,skullCond,brainCond,scalpThick,skullThick]) % - bst_set('ImportEegRawOptions', ImportEegRawOptions) % - bst_set('BugReportOptions', BugReportOptions) % - bst_set('DefaultSurfaceDisplay', displayStruct) % - bst_set('MagneticExtrapOptions', extrapStruct) % - bst_set('TimefreqOptions_morlet', Options) % - bst_set('TimefreqOptions_fft', Options) % - bst_set('TimefreqOptions_psd', Options) % - bst_set('TimefreqOptions_hilbert', Options) % - bst_set('TimefreqOptions_plv', Options) % - bst_set('OpenMEEGOptions', Options) % - bst_set('DuneuroOptions', Options) % - bst_set('GridOptions_headmodel', Options) % - bst_set('GridOptions_dipfit', Options) % - bst_set('UniformizeTimeSeriesScales', isUniform) % - bst_set('FlipYAxis', isFlipY) % - bst_set('AutoScaleY', isAutoScaleY) % - bst_set('FixedScaleY', Modality, Value) % - bst_set('XScale', XScale) % - bst_set('YScale', YScale) % - bst_set('ShowXGrid', isShowXGrid) % - bst_set('ShowYGrid', isShowYGrid) % - bst_set('ShowZeroLines', isShowZeroLines) % - bst_set('ShowEventsMode', ShowEventsMode) % - bst_set('Resolution', [resX,resY]) % - bst_set('UseSigProcToolbox', UseSigProcToolbox) % - bst_set('RawViewerOptions', RawViewerOptions) % - bst_set('TopoLayoutOptions', TopoLayoutOptions) % - bst_set('StatThreshOptions', StatThreshOptions) % - bst_set('ContactSheetOptions', ContactSheetOptions) % - bst_set('ProcessOptions', ProcessOptions) % - bst_set('MriOptions', MriOptions) % - bst_set('CustomColormaps', CustomColormaps) % - bst_set('DigitizeOptions', DigitizeOptions) % - bst_set('PcaOptions', PcaOptions) % - bst_set('ReadOnly', ReadOnly) % - bst_set('LastPsdDisplayFunction', LastPsdDisplayFunction) % - bst_set('PlotlyCredentials', Username, ApiKey, Domain) % - bst_set('KlustersExecutable', ExecutablePath) % - bst_set('ExportBidsOptions'), ExportBidsOptions) % - bst_set('Pipelines') Saved Pipelines stored % % SEE ALSO bst_get % @============================================================================= % This function is part of the Brainstorm software: % https://neuroimage.usc.edu/brainstorm % % Copyright (c) University of Southern California & McGill University % This software is distributed under the terms of the GNU General Public License % as published by the Free Software Foundation. Further details on the GPLv3 % license can be found at http://www.gnu.org/copyleft/gpl.html. % % FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE % UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY % WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF % MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY % LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE. % % For more information type "brainstorm license" at command prompt. % =============================================================================@ % % Authors: Francois Tadel, 2008-2021 % Martin Cousineau, 2017 global GlobalData; %% ==== PARSE INPUTS ==== if ((nargin >= 1) && ischar(varargin{1})) contextName = varargin{1}; if (nargin >= 2) contextValue = varargin{2}; else contextValue = []; end error('Usage : bst_set(contextName, contextValue)'); % Get required context structure switch contextName %% ==== BRAINSTORM CONFIGURATION ==== case 'Version' GlobalData.Program.Version = contextValue; case 'BrainstormHomeDir' GlobalData.Program.BrainstormHomeDir = contextValue; case 'BrainstormDbDir' GlobalData.DataBase.BrainstormDbDir = contextValue; case 'BrainstormTmpDir' GlobalData.Preferences.BrainstormTmpDir = contextValue; case 'Pipelines' GlobalData.Processes.Pipelines = contextValue; %% ==== PROTOCOL ==== case 'iProtocol' if isnumeric(contextValue) GlobalData.DataBase.iProtocol = contextValue; else error('iProtocol should be a number.'); end case {'ProtocolSubjects', 'ProtocolStudies'} for structField = fieldnames(contextValue)' GlobalData.DataBase.(contextName)(GlobalData.DataBase.iProtocol).(structField{1}) = contextValue.(structField{1}); end GlobalData.DataBase.isProtocolModified(GlobalData.DataBase.iProtocol) = 1; case 'ProtocolInfo' for structField = fieldnames(contextValue)' GlobalData.DataBase.(contextName)(GlobalData.DataBase.iProtocol).(structField{1}) = contextValue.(structField{1}); end case 'isProtocolLoaded' GlobalData.DataBase.isProtocolLoaded(GlobalData.DataBase.iProtocol) = contextValue; case 'isProtocolModified' GlobalData.DataBase.isProtocolModified(GlobalData.DataBase.iProtocol) = contextValue; %% ==== SUBJECT ==== case 'Subject' % Get subjects list ProtocolSubjects = bst_get('ProtocolSubjects'); iSubject = varargin{2}; sSubject = varargin{3}; % If default subject if (iSubject == 0) ProtocolSubjects.DefaultSubject = sSubject; else ProtocolSubjects.Subject(iSubject) = sSubject; end % Update DataBase bst_set('ProtocolSubjects', ProtocolSubjects); %% ==== STUDY ==== case 'Study' % Get studies list ProtocolStudies = bst_get('ProtocolStudies'); iStudies = varargin{2}; sStudies = varargin{3}; iAnalysisStudy = -2; iDefaultStudy = -3; for i = 1:length(iStudies) % Normal study if (iStudies(i) > 0) ProtocolStudies.Study(iStudies(i)) = sStudies(i); % Inter-subject analysis study elseif (iStudies(i) == iAnalysisStudy) ProtocolStudies.AnalysisStudy = sStudies(i); % Default study elseif (iStudies(i) == iDefaultStudy) ProtocolStudies.DefaultStudy = sStudies(i); end end % Update DataBase bst_set('ProtocolStudies', ProtocolStudies); %% ==== GUI ==== % USAGE: bst_set('Layout', sLayout) % bst_set('Layout', PropName, PropValue) case 'Layout' if (nargin == 2) && isstruct(contextValue) GlobalData.Preferences.Layout = contextValue; isUpdateScreens = 0; elseif (nargin == 3) && ischar(contextValue) && isfield(GlobalData.Preferences, 'Layout') && isfield(GlobalData.Preferences.Layout, contextValue) GlobalData.Preferences.Layout.(contextValue) = varargin{3}; isUpdateScreens = strcmpi(contextValue, 'DoubleScreen'); else error('Invalid call to bst_set.'); end % Update screen configuration GlobalData.Program.ScreenDef = gui_layout('GetScreenClientArea'); % Update layout right now gui_layout('Update'); % If the number of screen was changed: update the maximum size of the Brainstorm window if isUpdateScreens gui_layout('UpdateMaxBstSize'); end % USAGE: bst_set('FixedScaleY', []) % bst_set('FixedScaleY', Modality, Value) case 'FixedScaleY' if (nargin == 3) && ~isempty(contextValue) && ~isempty(varargin{3}) GlobalData.Preferences.FixedScaleY.(contextValue) = varargin{3}; elseif (nargin == 2) && isempty(contextValue) GlobalData.Preferences.FixedScaleY = struct(); end case 'ByteOrder' switch(contextValue) case {'b','ieee-le','n'} GlobalData.Preferences.ByteOrder = 'b'; case {'l','ieee-be'} GlobalData.Preferences.ByteOrder = 'l'; otherwise error('Invalid byte order.'); end case 'Clipboard' if (length(varargin) >= 3) isCut = varargin{3}; else isCut = 0; end GlobalData.Program.Clipboard.Nodes = contextValue; GlobalData.Program.Clipboard.isCut = isCut; case 'ElectrodeConfig' Modality = varargin{2}; ElectrodeConf = varargin{3}; if isequal(Modality, 'ECOG+SEEG') Modality = 'ECOG_SEEG'; elseif ~ismember(Modality, {'EEG','SEEG','ECOG','MEG'}) error(['Invalid modality: ' Modality]); end GlobalData.Preferences.(contextName).(Modality) = ElectrodeConf; case 'ElecInterpDist' Modality = varargin{2}; ElecInterpDist = varargin{3}; if isequal(Modality, 'ECOG+SEEG') Modality = 'ECOG_SEEG'; elseif ~ismember(Modality, {'EEG','SEEG','ECOG','MEG'}) error(['Invalid modality: ' Modality]); end GlobalData.Preferences.(contextName).(Modality) = ElecInterpDist; case {'UniformizeTimeSeriesScales', 'XScale', 'YScale', 'FlipYAxis', 'AutoScaleY', 'ShowXGrid', 'ShowYGrid', 'ShowZeroLines', 'ShowEventsMode', ... 'Resolution', 'AutoUpdates', 'ExpertMode', 'DisplayGFP', 'ForceMatCompression', 'GraphicsSmoothing', 'DownsampleTimeSeries', ... 'DisableOpenGL', 'InterfaceScaling', 'TSDisplayMode', 'UseSigProcToolbox', 'LastUsedDirs', 'DefaultFormats', ... 'BFSProperties', 'ImportDataOptions', 'ImportEegRawOptions', 'RawViewerOptions', 'MontageOptions', 'TopoLayoutOptions', ... 'StatThreshOptions', 'ContactSheetOptions', 'ProcessOptions', 'BugReportOptions', 'DefaultSurfaceDisplay', ... 'MagneticExtrapOptions', 'MriOptions', 'ConnectGraphOptions', 'NodelistOptions', 'IgnoreMemoryWarnings', 'SystemCopy', ... 'TimefreqOptions_morlet', 'TimefreqOptions_hilbert', 'TimefreqOptions_fft', 'TimefreqOptions_psd', 'TimefreqOptions_stft', 'TimefreqOptions_plv', ... 'OpenMEEGOptions', 'DuneuroOptions', 'DigitizeOptions', 'PcaOptions', 'CustomColormaps', 'PluginCustomPath', 'BrainSuiteDir', 'PythonExe', ... 'GridOptions_headmodel', 'GridOptions_dipfit', 'LastPsdDisplayFunction', 'KlustersExecutable', 'ExportBidsOptions', 'ShowHiddenFiles'} GlobalData.Preferences.(contextName) = contextValue; case 'ReadOnly' GlobalData.DataBase.isReadOnly = contextValue; case 'PlotlyCredentials' if length(varargin) ~= 4 error('Invalid call to bst_set.'); end [username, apiKey, domain] = varargin{2:4}; % Default domain: plot.ly if isempty(domain) domain = 'https://plot.ly'; end % Plotly needs a URL with HTTP and no trailing slash. if strfind(domain, 'https://') domain = strrep(domain, 'https://', 'http://'); elseif isempty(strfind(domain, 'http://')) domain = ['http://', domain]; end if domain(end) == '/' domain = domain(1:end-1); end % Save credentials saveplotlycredentials(username, apiKey); saveplotlyconfig(domain); %% ==== ERROR ==== otherwise error('Invalid context : ''%s''', contextName); id="line-457">
structures class="line874">The structures of the different types of files were described in the sections "On the hard drive" of the introduction tutorials. Here is a summary of all these sections:
Continuous recordings: File type "raw", Event markers.
Imported recordings: File type "data", Import epochs and Average response.
Power spectrum: File type "timefreq", Power spectrum and frequency filters.
Channel files: File type "channel", Channel file / MEG-MRI coregistration.
SSP/ICA projectors: Saved in the channel files, Artifact cleaning with SSP.
Head models: File type "headmodel", Head model.
Noise covariance: File types "noisecov" and "ndatacov", Noise and data covariance matrices.
Source files: File types "results" and "link", Source estimation.
Time-frequency: File type "timefreq", Time-frequency.
Statistics: File types "pdata", "presults", "ptimefreq" and "pmatrix", Statistics.
MRI volumes: File type "subjectimage", Display the anatomy.
Surfaces: File type "tess", Display the anatomy.
Scouts and atlases: Saved in the surface files, Scouts.
processing class="line874">In many situations, you will find useful to read the files available in the database, and maybe modify them. The easiest approaches do not require any scripting, we will start by reviewing them quickly.
mand">Process: Run Matlab command class="line862">If you want to modify the values saved in a file (eg. the field "F" from a "data" file), the easiest way is probably to use the process1 File > Run Matlab command. It is also available from Process2 in the category "Other".
It loads the files in input and run them through a piece of Matlab code that you can edit freely. It can extend a lot the flexibility of the Brainstorm pipeline manager, providing an easy access to any Matlab function or script.

The corresponding script looks like this:
sFiles = bst_process('CallProcess', 'process_matlab_eval', sFiles, [], ... 'matlab', 'Data = Data.^2;', ... 'sensortypes', 'MEG', ... 'overwrite', 0);
e_database_explorer">Export/Import with the database explorer class="line862">Right-click on the Deviant average in the database explorer > File > Export to Matlab > "DataMat".

Data exported as "DataMat" -24">>> DataMat -21">DataMat = ChannelFlag: [340x1 double] ColormapType: [] Comment: 'Avg: deviant (39 files)' DataType: 'recordings' Device: 'CTF' DisplayUnits: [] F: [340x361 double] History: {45x3 cell} Std: [] Time: [1x361 double] nAvg: 39 Events: [1x1 struct]
DataMat is the exact content of the corresponding .mat file, as loaded with Matlab's load() function. Edit some of the fields of this structure from the Matlab command window:
>> DataMat.Comment = 'Test square'; -25">>> DataMat.F = DataMat.F .^ 2;
Now right-click on the folder containing the original file > File > Import from Matlab > DataMat:

If instead, you right-click on the original file and select the menu File > Import from Matlab, it overwrites the selected file instead of creating a new one with the selected structure.
ation">Reference: File manipulation class="line874">Useful functions for manipulating file names and paths (read the code of the functions for help):
file_fullpath: Converts a relative file path to an absolute path.
file_short: Converts an absolute file path to a short path, relative to the current protocol folder.
file_gettype: Returns the type of a file.
Reading files from a script (all the functions take relative paths in input):
in_bst_data(DataFile): Read an imported epoch.
in_bst_timefreq(TimefreqFile): Read a power spectrum, time-frequency or connectivity file.
in_bst_headmodel(HeadmodelFile, ApplyOrient): Read a head model file and apply orientations.
in_bst_results(ResultsFile, LoadFull): Load a source file and optionally reconstruct the full source time series on the fly (ImagingKernel * recordings).
in_bst_matrix(MatrixFile): Read a file with the type "matrix".
in_bst(FileName, TimeWindow): Read any Brainstorm data file with the possibility to load only a specific part of the file. "TimeWindow" is a range of time values in seconds: [tStart, tStop].
bst_process('LoadInputFile', FileName, Target, TimeWindow): The most high-level function for reading data files. "Target" is a string with the list of signal names or types to load.
bst_memory('GetConnectMatrix', TimefreqMat): Rebuild a full connectivity matrix.
in_fopen(DataFile, FileFormat, ImportOptions): Low-level function for opening continuous files.
in_fread(sFile, ChannelMat, iEpoch, SamplesBounds, iChannels, ImportOptions): Low-level function for reading blocks from continuous files. Requires a call to in_fopen first to get the sFile structure.
Saving files:
bst_save(FileName, FileMat, Version, isAppend): Save a file but does not register it in the database.
FileName: Absolute path to a .mat file, use in combination with file_fullpath for relative paths.
FileMat: Valid Brainstorm structure, corresponding to the file type.
Version: Defines which version of the Matlab .mat format is used to store the data:
bigger files, no compression, no files >2Gb
compressed, no files >2Gb
than the others, compressed, but only way to save files > 2Gb.
isAppend: If set to 1, updates only the fields defined in FileMat, keep the others untouched.
file_unique: Produces a unique file name by adding a number tag to it.
bst_process('GetNewFilename', OutputFolder, BaseFilename): Generate a new unique file name based on the beginning of the file name (eg. BaseFilename='data_average_test_').
Registering new files in the database:
db_add(iStudy/iSubject, FileMat): Add a new file in an anatomy folder or a functional data folder. This function saves the file and then reloads the folder. FileMat must be a structure, not a filename. You should not save the file manually before calling this function.
db_add_data(iStudy, FileName, FileMat): Register in the database a structure FileMat that has already been saved in file FileName. You should call bst_save manually before calling this function.
db_add_data(iStudy, FileName, FileMat, iItem): Overwrites the existing file #iItem.
Reload folders (if you saved or deleted files without registering correctly the modification in the database):
db_reload_studies(iStudies): Reload only the select data folders (aka "studies").
db_reload_conditions(iSubjects): Reload all the data folders for a subject.
db_reload_subjects(iSubjects): Reload the anatomy of the selected subjects.
db_reload_database('current'): Reload the entire protocol (anatomy and functional data).
Other useful database functions:
db_add_condition: Create a new folder in a subject.
db_add_subject: Create a new subject.
db_delete_studies: Delete a list of folders.
db_delete_subjects: Delete a list of subjects.
db_group_conditions: Merge two folders from the same subject.
db_rename_condition: Rename a folder.
db_rename_subject: Rename a subject.
db_set_channel: Set the channel file for a folder.
db_set_noisecov: Set the noise/data covariance for a folder, or copy to other folders/subjects.
db_set_template: Copy an anatomy template to a subject or use it as the default anatomy.
Export a file from the database to other file formats (read the comments in the functions for help):
export_channel
export_data
export_events
export_result
export_timefreq
export_matrix
export_mri
export_surfaces
export_protocol: Export a subject or an entire protocol as a .zip file.
Convert Brainstorm structures to FieldTrip structures:
out_fieldtrip_channel
out_fieldtrip_data
out_fieldtrip_timefreq
out_fieldtrip_headmodel
out_fieldtrip_results
out_fieldtrip_matrix
tions">Reference: Display functions class="line874">Create new visualization figures:
view_channels: Display sensors in a 3D figure.
view_helmet: Display the inner surface of the MEG helmet in a 3D figure.
view_timeseries: Display a data file as time series.
view_timeseries_matrix: Display a custom matrix as time series.
view_topography: Display a data file as a spatial topography.
view_erpimage: Display multiple data files as an image, signal by signal.
view_timefreq: Open a time-frequency file (various display modes available).
view_spectrum: Display a power spectrum (PSD or time-frequency files).
view_connect: Open a connectivity matrix (various display modes available).
view_matrix: Open a "matrix" file (various display modes available).
view_contactsheet: Create a contact sheet in time or across a volume from an existing figure.
view_noisecov: Display a noise or data covariance file.
view_dipoles: Open a dipoles file (various display modes available).
view_pac: Open PAC results (various display modes available).
view_mri: View a MRI file in the MRI viewer (with or without a functional overlay from a source file).
view_mri_3d: View a MRI file in a 3D figure (with or without a functional overlay from a source file).
view_surface: View a surface.
view_surface_data: View a surface file with a source file as its texture.
view_surface_matrix: View a custom surface (user defines vertices, faces, color, transparency).
view_image_reg: Display a 3D or 4D matrix as an image with time and/or frequency dimensions.
view_struct: Display a structure as with the popup menu "File > View file contents".
script_view_sources: Shortcut script to display source files.
bst_memory('UnloadAll', 'Forced'): Close all the existing figures.
Configure time-series figures:
panel_time('SetCurrentTime', t): Set current time.
panel_record('SetTimeLength', duration): Set the length of the current display page, in seconds.
panel_record('SetStartTime', t): Set the start of the current page, in seconds.
panel_record('SetDisplayMode', hFig, DisplayMode): 'column' or 'butterfly'.
panel_filter('SetFilters', isLowPass, LowPass, isHighPass, HighPass, isSinRem, SinRem, isMirror)
panel_montage('SetCurrentMontage', hFig, MontageName): Change the montage of channels.
bst_figures('SetSelectedRows', SelectedChannels): Set selected channels (cell array of strings).
figure_timeseries('SetTimeSelectionManual', hFig, TimeWindow): Select a time segment.
Configure 3D figures:
figure_3d('SetStandardView', hFig, 'left'): Change camera view (top,bottom,left,right,front,back).
figure_3d('ViewSensors', hFig, isMarkers, isLabels): Enable the view of sensor markers and labels.
panel_surface('SetShowSulci', hFig, iTess, 1): Show/hide the sulci (darker color for deeper areas).
panel_surface('SetSurfaceColor', hFig, iTess, [1 0 0]): Set the surface color.
panel_surface('SetSurfaceSmooth', hFig, iTess, Smooth, 0): Set the amount of smoothing (0-1).
panel_surface('SetSurfaceTransparency', hFig, iTess, Transp): Set the surface transparency (0-1).
panel_surface('SetDataThreshold', hFig, iTess, Thresh): Set the amplitude threshold.
panel_surface('SetSizeThreshold', hFig, iTess, MinSize): Set size threshold (min size slider).
figure_mri('SetLocation', CsName, hFig, [], xyz): CsName=voxel/mri/scs/mni, xyz=[x,y,z]
Configure time-frequency figures:
panel_freq('SetCurrentFreq', iFreq, 1): Set the current frequency index (from the Freqs vector)
panel_freq('SetCurrentFreq', Freq, 0): Set the current frequency (in Hz).
sOptions = panel_display('GetDisplayOptions'): Get display options selected in the Display tab.
panel_display('SetDisplayOptions', sOptions): Change the options selected in the Display tab.
sOptions.HideEdgeEffects: Controls the checkbox "Hide edge effects" (0 or 1).
sOptions.HighResolution: Controls the checkbox "Smooth display" (0 or 1).
sOptions.RowName: Controls the signal that is currently displayed (for 'SingleSensor' display mode).
sOptions.Function: Controls the display function (magnitude, power, log, phase).
Configure colormaps:
bst_colormaps('SetColormapName', ColormapType, ColormapName): 'jet', 'parula', 'cmap_rbw', ...
bst_colormaps('SetMaxMode', ColormapType, MaxMode): Colorbar range ('global', 'local', 'custom').
bst_colormaps('SetMaxCustom', ColormapType, [], Min, Max): Set a custom colorbar range.
bst_colormaps('SetColormapAbsolute', ColormapType, isAbsolute): Show positive or relative values
bst_colormaps('SetDisplayColorbar', ColormapType, isDisplay): Show colorbar in the figures.
bst_colormaps('RestoreDefaults', ColormapType): Restore the default configuration for a colormap.
ColormapType: anatomy, meg, eeg, sources, stat1, stat2, time, timefreq, connect1, connectn, image
Configure statistical thresholding:
StatThreshOptions = bst_get('StatThreshOptions'): Get display options selected in the Stat tab.
bst_set('StatThreshOptions', StatThreshOptions): Change the options selected in the Stat tab.
StatThreshOptions.pThreshold: Current p-Value threshold.
StatThreshOptions.Correction: Correction for multiple comparisons ('none', 'fdr', 'bonferroni')
StatThreshOptions.Control: List of dimensions to correct for multiple comparisons (default = [1 2 3])
Export the contents of a figure to a file:
out_figure_image: Screen capture of any Brainstorm figure.
out_figure_movie: Save a movie from one or multiple Brainstorm figures.
out_figure_timefreq: Extract some of the data displayed in a time-frequency figure.
out_figure_timeseries: Extract some of the data displayed in a time series figure.
_file">Example: Creating a new file class="line874">This section illustrates how to add new files to the database. We will create a sinusoidal signal and save it in a "matrix" file, in a new folder of the subject "Test".
% Time: 1 second with a sampling frequency of 1000Hz = 0:0.001:1; Generate two sinsuoidal signals (20Hz,30Hz) = [sin(20*2*pi*t); 0.5*sin(30*2*pi*t)]; -16"> Initialize an empty "matrix" structure -15">sMat = db_template('matrixmat'); Fill the required fields of the structure -11">sMat.Value = F; 0-9">sMat.Comment = 'Test sinusoids'; 1-9">sMat.Description = {'Signal #1: 20Hz'; 'Signal #2: 30Hz'}; 2-9">sMat.Time = t; 3-9"> Create a new folder "Script" in subject "Test" 5-7">iStudy = db_add_condition('Test', 'Script'); Get the corresponding study structure 7-6">sStudy = bst_get('Study', iStudy);
There are many options to add a new file to the database, with various levels of requirements. You can call the db_add function (reloads the destination folder, therefore slow if you save many files), save the file in the corresponding folder and reload the protocol (slow as well), or register the file in the database manually (more complicated but faster).
Option #1: db_add
OutputFile = db_add(iStudy, sMat);
Option #2: bst_save / db_reload_studies
% Get the full path to the new folder (same folder as the brainstormstudy.mat file for this study) -23">OutputFolder = bst_fileparts(file_fullpath(sStudy.FileName)); Get a new unique filename (including a timestamp) -17">MatrixFile = bst_process('GetNewFilename', OutputFolder, 'matrix_test'); Save file -16">bst_save(MatrixFile, sMat, 'v6'); Reload the folder in which the new file was saved -12">db_reload_studies(iStudy);
Option #3: bst_save / db_add_data
% Another way to generate a unique filename (without a timestamp) -28">MatrixFile = file_unique(bst_fullfile(OutputFolder, 'matrix_test.mat')); Save file -21">bst_save(MatrixFile, sMat, 'v6'); Reference saved file in the database -17">db_add_data(iStudy, MatrixFile, sMat); Update the database explorer display -15">panel_protocols('UpdateNode', 'Study', iStudy);

Editing events class="line874">A step that commonly requires manual changes is the definition of the event markers. For example, we have to combine external triggers or behavioral information with the existing events. This example illustrates how to load the events, modify them and save them back.
For the continuous recordings, the events are saved in the .mat file corresponding to the "Link to raw file". These structures contain only meta-data and information created with Brainstorm, the EEG/MEG recordings are available in a separate binary file. First, we need to load this link.
% Right-click on a "Link to raw file" in the database explorer > File > Copy file path to clipboard -25">RawFile = '/.../@rawS01.../data_0raw_S01_..._01_600Hz_notch.mat' -22"> Load the "sFile" structure, contained in the .F structure of the link file (data_0raw...mat) -18">sRaw = in_bst_data(RawFile, 'F'); -16"> -13">>> sRaw.F.events 0-10">ans = 1-10">1x7 struct array with fields: label color epochs samples times reactTimes select
For example, let's say we want to add 30ms to all the events in the category "button" in order to compensate for some hardware delay, and create a new event category with the modified timing. We need first to identify what is the index of the category "button", in this array of 7 event structures.
% Find the index of the event category "button" -30">iEvtButton = find(strcmpi({sRaw.F.events.label}, 'button')); -26"> -23">>> iEvtButton -20">iEvtButton = 3
In the code above, note this special Matlab syntax that allows the concatenation of the values of one field across multiple structures, in an array of structures:
>> {sRaw.F.events.label} -31">ans = 'standard' 'deviant' 'button' 'cardiac' 'blink' 'bad_1-7Hz' 'bad_40-240Hz'
If you want to search instead all the events containing a specific tag, for example "bad", you can use the cellfun function (applies the same function sequentially to all the elements in a cell array and concatenates the results) in combination with the strfind function (search for a substring). The final call to the find function returns at which indices the list of tags found in the event label is not empty.
>> iEvtBad = find( ~cellfun( @(c)isempty(strfind(c,'bad')), ... {sRaw.F.events.label})) -28">iEvtBad = 6 7
The code below copies the existing event category "button", renames it and add a 30ms offset. Note that the times and samples field must always match. If you modify one, you must modify the others as well (times = samples/sfreq). If you add or remove events, you must adjust the size of the epochs field (always 1 for most file formats).
% Copy the event category "button" to a new category -33">iEvtNew = length(sRaw.F.events) + 1; -29">sRaw.F.events(iEvtNew) = sRaw.F.events(iEvtButton); Rename the new event to "button_offset" -21">sRaw.F.events(iEvtNew).label = 'button_offset'; -20"> How many samples in 30ms (0.030s * 600Hz = 18 samples) -17">offsetSample = round(0.030 .* sRaw.F.prop.sfreq); Apply offset to the events in the "button_offset" category 0-11">sRaw.F.events(iEvtNew).samples = ... sRaw.F.events(iEvtNew).samples + offsetSample; 2-11">% Re-compute the corresponding times 3-11">sRaw.F.events(iEvtNew).times = ... sRaw.F.events(iEvtNew).samples ./ sRaw.F.prop.sfreq; Re-generate an epochs field with only ones (optional here, as we didn't change the number of evt) 7-8">sRaw.F.events(iEvtNew).epochs = ... ones(1, size(sRaw.F.events(iEvtNew).times, 2)); Change the event color to yellow (red=1, green=1, blue=0) 0-5">sRaw.F.events(iEvtNew).color = [1 1 0]; 1-5"> 2-5">>> sRaw.F.events(iEvtNew) 3-5">ans = label: 'button_offset' color: [1 1 0] epochs: [1x40 double] samples: [1x40 double] times: [1x40 double] reactTimes: [] select: 1
The last step is to save the modifications back to the "Link to raw file". Here the call to file_fullpath is optional because the variable RawFile already contains the absolute path to the file.
% Update the sRaw structure to the RawFile file (the last parameter appends to the existing struct) -34">bst_save(file_fullpath(RawFile), sRaw, 'v6', 1);
Open the recordings to make sure your transformation worked the way you expected.

examples in the code class="line862">The easier way to understand how to use a function is to search the code with the "Find files" interface in Matlab. Go to the brainstorm3 folder, click on "Find files" (or Ctrl+Shift+F), enter the name of a function in "Find files containing text", Include subfolders, Match case. It will return all the lines that include the string you entered across all the files in the Brainstorm distribution. Just double-click on a line to jump to the code in the Matlab editor.

You can use the same interface to find what function is called when you click on a button or menu in the interface. Search for the label or the tooltip of the interface element in the same way. The example below shows how to track what happens when you click on the headmodel popup menu "Check spheres".

If you have trouble understanding how to set some input parameters, you can use the debugger to explore a real use case. Place a breakpoint at the begging of your function of interest (watch this tutorial if you don't know how to do this), for example in view_timeseries.m. Then click on the corresponding menus in the Brainstorm interface (eg. double-click on a data file). When the execution reaches the line you selected, it stops and gives you back the commands. You can explore the values in all the variables, modify them, and execute the code step by step (many options available in the Editor tab of Matlab).

rol">Additional quality control class="line862">You can add in the reports all the information that may help you control the quality of the analysis, or figures you want to include in publications or clinical reports. The process "File > Save snapshot" lets you save some predefined views, but you can also custom screen captures. The example below shows how to add a "raster plot" for all the deviant trials from Run#01 in the report.
% Get all the deviant trials in Run#01 (the list includes the deviant average) -35">sDeviant = bst_process('CallProcess', 'process_select_files_data', [], [], ... 'subjectname', 'Subject01', ... 'condition', 'S01_AEF_20131218_01_600Hz_notch', ... 'tag', 'deviant'); -21"> Open raster plot -18">hFig = view_erpimage({sDeviant.FileName}, 'erpimage', 'MEG'); Select the channel MRT34 0-12">sOptions = panel_display('GetDisplayOptions'); 1-12">sOptions.RowName = 'MRT34'; 2-12">panel_display('SetDisplayOptions', sOptions); 3-12"> 4-11">% Screen capture of this figure 5-10">% bst_report('Snapshot', hFig, FileName, Comment, WindowPosition); 6-9">bst_report('Snapshot', hFig, [], 'ERP image: MRT34', [300 100 600 400]); Close figure 8-7">close(hFig);
You can also add messages in the reports (information, warning or errors).
% Function call: bst_report(MsgType, sProcess, sInputs, Message) -36">bst_report('Info', [], sDeviant, 'This is an information message.'); -31">bst_report('Warning', [], sDeviant, 'This is a warning.'); -28">bst_report('Error', [], sDeviant, 'This is an error.'); -23"> Open the report viewer to show the current report (not saved yet) -21">bst_report('Open', 'Current');
Report generated with the code above:

over subjects class="line862">Creating loops is not supported yet by the script generator, but relatively easy to do from a script without knowing too much about Matlab programming. The example below shows how to create a loop over subjects to import their anatomy. The dataset used here is from the tutorial MEG visual: single subject.
With the Process1 box empty, select the process "Import > Import anatomy > Import anatomy folder" and generate a script. Simplify if using the guidelines presented in the previous sections:
% Input files -37">SubjectNames = {'sub001'}; -32">RawFiles = {... '/.../Tutorials/sample_group/freesurfer/sub001'}; -24"> Process: Import anatomy folder -22">bst_process('CallProcess', 'process_import_anatomy', [], [], ... 'subjectname', SubjectNames{1}, ... 'mrifile', {RawFiles{1}, 'FreeSurfer'}, ... 'nvertices', 15000);
Add the other subject names and corresponding FreeSurfer folders in the script header:
SubjectNames = {'sub001', 'sub002', 'sub003', 'sub004'}; -38">RawFiles = {... '/.../Tutorials/sample_group/freesurfer/sub001', ... '/.../Tutorials/sample_group/freesurfer/sub002', ... '/.../Tutorials/sample_group/freesurfer/sub003', ... '/.../Tutorials/sample_group/freesurfer/sub004'};
Add a for loop around all the steps to repeat on each subject ("for" before, and "end" after the code), and replace the indices "1" with the loop variable:
% Loop on subjects -39">for iSubject = 1:length(SubjectNames) % Process: Import anatomy folder bst_process('CallProcess', 'process_import_anatomy', [], [], ... 'subjectname', SubjectNames{iSubject}, ... 'mrifile', {RawFiles{iSubject}, 'FreeSurfer'}, ... 'nvertices', 15000); -20">end
over acquisition runs class="line862">If you have multiple subjects for which the anatomy is already imported, and multiple runs to process for each subject, you can add two nested for loops to link all the runs to the database in the same script. The dataset used here is from the tutorial MEG visual: single subject.
With the Process1 box empty, select the process "Import > Import recordings > Create link to raw file" and generate a script. Simplify if using the guidelines presented in the previous sections:
% Input files -40">SubjectNames = {'sub001'}; -35">RawFiles = {... '/.../sample_group/ds117/sub001/MEG/run_01_sss.fif'}; -27"> Process: Create link to raw file -24">sFileRaw = bst_process('CallProcess', 'process_import_data_raw', [], [], ... 'subjectname', SubjectNames{1}, ... 'datafile', {RawFiles{1}, 'FIF'}, ... 'channelreplace', 0, ... 'channelalign', 0, ... 'evtmode', 'value');
Add the other subject names and all the runs for all the subjects (array of cell arrays) in the script header:
SubjectNames = {'sub001', 'sub002'}; -41">RawFiles = {... {'/.../sample_group/ds117/sub001/MEG/run_01_sss.fif', ... '/.../sample_group/ds117/sub001/MEG/run_02_sss.fif', ... '/.../sample_group/ds117/sub001/MEG/run_03_sss.fif'}, ... {'/.../sample_group/ds117/sub002/MEG/run_01_sss.fif', ... '/.../sample_group/ds117/sub002/MEG/run_02_sss.fif', ... '/.../sample_group/ds117/sub002/MEG/run_03_sss.fif'}};
Add two for loops around the code to repeat on all the runs:
% Loop on subjects -42">for iSubject = 1:length(SubjectNames) % Loop on runs for each subject for iRun = 1:length(RawFiles{iSubject}) % Process: Create link to raw file sFileRaw = bst_process('CallProcess', 'process_import_data_raw', [], [], ... 'subjectname', SubjectNames{iSubject}, ... 'datafile', {RawFiles{iSubjects}{iRun}, 'FIF'}, ... 'channelreplace', 0, ... 'channelalign', 0, ... 'evtmode', 'value'); end 3-13">end
to process an entire study class="line874">This section proposes a standard workflow for processing a full group study with Brainstorm. It contains the same steps of analysis as the introduction tutorials, but separating what can be done automatically from what should be done manually. This workflow can be adapted to most ERP studies (stimulus-based).
Prototype: Start by processing one or two subjects completely interactively (exactly like in the introduction tutorials). Use the few pilot subjects that you have for your study to prototype the analysis pipeline and check manually all the intermediate stages. Take notes of what you're doing along the way, so that you can later write a script that reproduces the same operations.
Anatomical fiducials: Set NAS/LPA/RPA and compute the MNI transformation for each subject.
Segmentation: Run FreeSurfer/BrainSuite to get surfaces and atlases for all the subjects.
File > Batch MRI fiducials: This menu prompts for the selection of the fiducials for all the subjects and saves a file fiducials.m in each segmentation folder. You will not have to redo this even if you have to start over your analysis from the beginning.
Script: Write a loop that calls the process "Import anatomy folder" for all the subjects.
Alternatives: Create and import the subjects one by one and set the fiducials at the import time. Or use the default anatomy for all the subjects (or use warped templates).
Script #1: Pre-processing: Loop on the subjects and the acquisition runs.
Create link to raw files: Link the subject and noise recordings to the database.
Event markers: Read and group triggers from digital and analog channel, fix stimulation delays
Evaluation: Power spectrum density of the recordings to evaluate their quality.
Pre-processing: Notch filter, sinusoid removal, band-pass filter.
Evaluation: Power spectrum density of the recordings to make sure the filters worked well.
Cleanup: Delete the links to the original files (the filtered ones are copied in the database).
Detect artifacts: Detect heartbeats, Detect eye blinks, Remove simultaneous.
Compute SSP: Heartbeats, Blinks (this selects the first component of each decomposition)
Compute ICA: If you have some artifacts you'd like to remove with ICA (no default selection).
Screenshots: Check the MRI/sensors registration, PSD before and after corrections, SSP.
Export the report: One report per subject, or one report for all the subjects, saved in HTML.
Manual inspection #1:
Check the reports: Information messages (number of events, errors and warnings) and screen captures (registration problems, obvious noisy channels, incorrect SSP topographies).
Mark bad channels: Open the recordings, select the channels and mark them as bad. Or use the process "Set bad channels" to mark the same bad channels in multiple files.
Fix the SSP/ICA: For the suspicious runs: Open the file, adjust the list of blink and cardiac events, remove and recompute the SSP decompositions, manually select the components.
Detect other artifacts: Run the process on all the runs of all the subjects at once (select all the files in Process1 and run the process, or generate the equivalent script).
Mark bad segments: Review the artifacts detected in 1-7Hz and 40-240Hz, keep only the ones you really want to remove, then mark the event categories as bad. Review quickly the rest of the file and check that there are no other important artifacts.
Additional SSP: If you find one type of artifact that repeats (typically saccades and SQUID jumps), you can create additional SSP projectors, either with the process "SSP: Generic" or directly from a topography figure (right-click on the figure > Snapshot> Use as SSP projector).
Script #2: Subject-level analysis: Epoching, averaging, sources, time-frequency.
Importing: Process "Import MEG/EEG: Events" and "Pre-process > Remove DC offset".
Averaging: Average trials by run, average runs by subject (registration problem in MEG).
Noise covariance: Compute from empty room or resting recordings, copy to other folders.
Head model: Compute for each run, or compute once and copy if the runs are co-registered.
Sources: Compute for each run, average across runs and subjects in source space for MEG.
Time-frequency: Computation with Hilbert transform or Morlet wavelets, then normalize.
Screenshots: Check the quality of all the averages (time series, topographies, sources).
Export the report: One report per subject, or one report for all the subjects, saved in HTML.
Manual inspection #2:
Check the reports: Check the number of epochs imported and averaged in each condition, check the screen capture of the averages (all the primary responses should be clearly visible).
Regions of interest: If not using predefined regions from an atlas, define the scouts on the anatomy of each subject (or on the template and then project them to the subjects).
Script #3: Group analysis, ROI-based analysis, etc.
Averaging: Group averages for the sensor data, the sources and the time-frequency maps.
Statistics: Contrast between conditions or groups of subjects.
Regions of interest: Any operation that involve scouts.
scripts 030">
The following script from the Brainstorm distribution reproduces the introduction tutorials ("Get started"): brainstorm3/toolbox/script/tutorial_introduction.m - Report: report_TutorialIntroduction.html
1 function tutorial_introduction(tutorial_dir, reports_dir) % TUTORIAL_INTRODUCTION: Script that runs all the Brainstorm introduction tutorials. % % INPUTS: % - tutorial_dir : Directory where the sample_introduction.zip file has been unzipped % - reports_dir : Directory where to save the execution report (instead of displaying it) % @============================================================================= % This function is part of the Brainstorm software: % https://neuroimage.usc.edu/brainstorm % % Copyright (c) University of Southern California & McGill University % This software is distributed under the terms of the GNU General Public License % as published by the Free Software Foundation. Further details on the GPLv3 % license can be found at http://www.gnu.org/copyleft/gpl.html. % % FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE % UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY % WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF % MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY % LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE. % % For more information type "brainstorm license" at command prompt. % =============================================================================@ % % Author: Francois Tadel, 2016-2017 % ===== FILES TO IMPORT ===== % Output folder for reports if (nargin < 2) || isempty(reports_dir) || ~isdir(reports_dir) reports_dir = []; % You have to specify the folder in which the tutorial dataset is unzipped if (nargin == 0) || isempty(tutorial_dir) || ~file_exist(tutorial_dir) error('The first argument must be the full path to the dataset folder.'); % Subject name SubjectName = 'Subject01'; % Build the path of the files to import AnatDir = fullfile(tutorial_dir, 'sample_introduction', 'anatomy'); = fullfile(tutorial_dir, 'sample_introduction', 'data', 'S01_AEF_20131218_01_600Hz.ds'); = fullfile(tutorial_dir, 'sample_introduction', 'data', 'S01_AEF_20131218_02_600Hz.ds'); NoiseFile = fullfile(tutorial_dir, 'sample_introduction', 'data', 'S01_Noise_20131218_02_600Hz.ds'); % Check if the folder contains the required files if ~file_exist(Run1File) error(['The folder ' tutorial_dir ' does not contain the folder from the file sample_introduction.zip.']); % Re-inialize random number generator if (bst_get('MatlabVersion') >= 712) rng('default'); %% ===== TUTORIAL #1: CREATE PROTOCOL ================================================ % =================================================================================== disp([10 'DEMO> Tutorial #1: Create protocol' 10]); % The protocol name has to be a valid folder name (no spaces, no weird characters...) ProtocolName = 'TutorialIntroduction'; % Start brainstorm without the GUI if ~brainstorm('status') brainstorm nogui % Delete existing protocol gui_brainstorm('DeleteProtocol', ProtocolName); % Create new protocol gui_brainstorm('CreateProtocol', ProtocolName, 0, 0); % Start a new report bst_report('Start'); % Reset colormaps bst_colormaps('RestoreDefaults', 'meg'); % Set the current display mode to 'butterfly' bst_set('TSDisplayMode', 'butterfly'); %% ===== TUTORIAL #2: IMPORT ANATOMY ================================================= % =================================================================================== disp([10 'DEMO> Tutorial #2: Import anatomy' 10]); % Process: Import FreeSurfer folder bst_process('CallProcess', 'process_import_anatomy', [], [], ... 'subjectname', SubjectName, ... 'mrifile', {AnatDir, 'FreeSurfer'}, ... 'nvertices', 15000, ... 'nas', [127, 213, 139], ... 'lpa', [ 52, 113, 96], ... 'rpa', [202, 113, 91]); % This automatically calls the SPM registration procedure because the AC/PC/IH points are not defined %% ===== TUTORIAL #3: EXPLORE ANATOMY ================================================ % =================================================================================== disp([10 'DEMO> Tutorial #3: Explore anatomy' 10]); % Get subject definition sSubject = bst_get('Subject', SubjectName); % Get MRI file and surface files MriFile = sSubject.Anatomy(sSubject.iAnatomy).FileName; CortexFile = sSubject.Surface(sSubject.iCortex).FileName; = sSubject.Surface(sSubject.iScalp).FileName; % Display MRI hFigMri1 = view_mri(MriFile); hFigMri3 = view_mri_3d(MriFile, [], [], 'NewFigure'); hFigMri2 = view_mri_slices(MriFile, 'x', 20); pause(0.5); % Close figures close([hFigMri1 hFigMri2 hFigMri3]); % Display scalp and cortex hFigSurf = view_surface(HeadFile); hFigSurf = view_surface(CortexFile, [], [], hFigSurf); hFigMriSurf = view_mri(MriFile, CortexFile); % Figure configuration iTess = 2; panel_surface('SetShowSulci', hFigSurf, iTess, 1); panel_surface('SetSurfaceColor', hFigSurf, iTess, [1 0 0]); panel_surface('SetSurfaceSmooth', hFigSurf, iTess, 0.5, 0); panel_surface('SetSurfaceTransparency', hFigSurf, iTess, 0.8); figure_3d('SetStandardView', hFigSurf, 'left'); pause(0.5); % Close figures close([hFigSurf hFigMriSurf]); %% ===== TUTORIAL #4: CHANNEL FILE =================================================== % =================================================================================== disp([10 'DEMO> Tutorial #4: Channel file' 10]); % Process: Create link to raw files sFilesRun1 = bst_process('CallProcess', 'process_import_data_raw', [], [], ... 'subjectname', SubjectName, ... 'datafile', {Run1File, 'CTF'}, ... 'channelalign', 1); sFilesRun2 = bst_process('CallProcess', 'process_import_data_raw', [], [], ... 'subjectname', SubjectName, ... 'datafile', {Run2File, 'CTF'}, ... 'channelalign', 1); sFilesNoise = bst_process('CallProcess', 'process_import_data_raw', [], [], ... 'subjectname', SubjectName, ... 'datafile', {NoiseFile, 'CTF'}, ... 'channelalign', 0); sFilesRaw = [sFilesRun1, sFilesRun2, sFilesNoise]; % Process: Snapshot: Sensors/MRI registration bst_process('CallProcess', 'process_snapshot', [sFilesRun1, sFilesRun2], [], ... 'target', 1, ... % Sensors/MRI registration 'modality', 1, ... % MEG (All) 'orient', 1, ... % left 'Comment', 'MEG/MRI Registration'); % View sensors hFig = view_surface(HeadFile); hFig = view_channels(sFilesRun1.ChannelFile, 'MEG', 1, 1, hFig); % Hide sensors pause(0.5); hFig = view_channels(sFilesRun1.ChannelFile, 'MEG', 0, 0, hFig); % View coils hFig = view_channels(sFilesRun1.ChannelFile, 'CTF', 1, 1, hFig); % View helmet pause(0.5); hFig = view_helmet(sFilesRun1.ChannelFile, hFig); pause(0.5); close(hFig); % Edit good/bad channel for current file gui_edit_channel(sFilesRun1.ChannelFile); pause(0.5); % Unload everything bst_memory('UnloadAll', 'Forced'); %% ===== TUTORIAL #5: REVIEW RAW ===================================================== % =================================================================================== disp([10 'DEMO> Tutorial #5: Review raw' 10]); % Process: Convert to continuous (CTF): Continuous bst_process('CallProcess', 'process_ctf_convert', sFilesRaw, [], ... 'rectype', 2); % Continuous % View recordings hFigMeg = view_timeseries(sFilesRun1.FileName, 'MEG'); hFigEeg = view_timeseries(sFilesRun1.FileName, 'Misc'); hFigSel = view_timeseries(sFilesRun1.FileName, 'MEG', {'MLT11','MLT12','MLT13'}); % Figure configuration pause(0.5); panel_record('SetTimeLength', 3); panel_record('SetStartTime', 100); panel_record('SetDisplayMode', hFigMeg, 'column'); panel_montage('SetCurrentMontage', hFigMeg, 'CTF LT'); % Set filters: panel_filter('SetFilters', LowPassEnabled, LowPassValue, HighPassEnabled, HighPassValue, SinRemovalEnabled, SinRemovalValue, MirrorEnabled, FullSourcesEnabled) panel_filter('SetFilters', 1, 100, 1, 1, 0, [], 0, 0); pause(0.5); panel_record('SetDisplayMode', hFigMeg, 'butterfly'); panel_montage('SetCurrentMontage', hFigMeg, ''); % Close figures close([hFigMeg hFigEeg hFigSel]); %% ===== TUTORIAL #8: STIM DELAYS ==================================================== % =================================================================================== disp([10 'DEMO> Tutorial #8: Stim delays' 10]); % Process: Detect: standard_fix bst_process('CallProcess', 'process_evt_detect_analog', [sFilesRun1, sFilesRun2], [], ... 'eventname', 'standard_fix', ... 'channelname', 'UADC001', ... 'timewindow', [], ... 'threshold', 1.2, ... 'blanking', 0.2, ... 'highpass', 0, ... 'lowpass', 0, ... 'refevent', 'standard', ... 'isfalling', 0, ... 'ispullup', 0, ... 'isclassify', 0); % Process: Detect: deviant_fix bst_process('CallProcess', 'process_evt_detect_analog', [sFilesRun1, sFilesRun2], [], ... 'eventname', 'deviant_fix', ... 'channelname', 'UADC001', ... 'timewindow', [], ... 'threshold', 1.2, ... 'blanking', 0.2, ... 'highpass', 0, ... 'lowpass', 0, ... 'refevent', 'deviant', ... 'isfalling', 0, ... 'ispullup', 0, ... 'isclassify', 0); % Process: Read from channel bst_process('CallProcess', 'process_evt_read', [sFilesRun1, sFilesRun2], [], ... 'stimchan', 'UDIO001', ... 'trackmode', 1, ... % Value: detect the changes of channel value 'zero', 0); % Process: Delete events bst_process('CallProcess', 'process_evt_delete', [sFilesRun1, sFilesRun2], [], ... 'eventname', 'standard, deviant, button'); % Process: Rename event (standard_fix>standard) bst_process('CallProcess', 'process_evt_rename', [sFilesRun1, sFilesRun2], [], ... 'src', 'standard_fix', ... 'dest', 'standard'); % Process: Rename event (deviant_fix>deviant) bst_process('CallProcess', 'process_evt_rename', [sFilesRun1, sFilesRun2], [], ... 'src', 'deviant_fix', ... 'dest', 'deviant'); % Process: Rename event (64>button) bst_process('CallProcess', 'process_evt_rename', [sFilesRun1, sFilesRun2], [], ... 'src', '64', ... 'dest', 'button'); %% ===== TUTORIAL #10: FREQUENCY FILTERS ============================================= % =================================================================================== disp([10 'DEMO> Tutorial #10: Frequency filters' 10]); % Process: Sinusoid removal: 60Hz 120Hz 180Hz 300Hz sFilesNotch = bst_process('CallProcess', 'process_notch', sFilesRaw, [], ... 'freqlist', [60, 120, 180], ... 'sensortypes', 'MEG', ... 'read_all', 0); % Process: Power spectrum density (Welch) sFilesPsd = bst_process('CallProcess', 'process_psd', [sFilesRaw, sFilesNotch], [], ... 'timewindow', [], ... 'win_length', 4, ... 'win_overlap', 50, ... 'clusters', {}, ... 'sensortypes', 'MEG', ... 'edit', struct(... 'Comment', 'Power', ... 'TimeBands', [], ... 'Freqs', [], ... 'ClusterFuncTime', 'none', ... 'Measure', 'power', ... 'Output', 'all', ... 'SaveKernel', 0)); % Process: Snapshot: Frequency spectrum bst_process('CallProcess', 'process_snapshot', sFilesPsd, [], ... 'target', 10, ... % Frequency spectrum 'modality', 1, ... % MEG (All) 'Comment', 'Power spectrum density'); % Process: Delete folders bst_process('CallProcess', 'process_delete', sFilesRaw, [], ... 'target', 2); % Delete folders % Separate the three outputs sFilesRun1 = {sFilesNotch(1).FileName}; sFilesRun2 = {sFilesNotch(2).FileName}; sFilesNoise = {sFilesNotch(3).FileName}; %% ===== TUTORIAL #11: BAD CHANNELS ================================================== % =================================================================================== % % Process: Set bad channels % sFiles = bst_process('CallProcess', 'process_channel_setbad', sFilesRun2, [], ... % 'sensortypes', 'MRT51, MLO52, MLO42, MLO43'); %% ===== TUTORIAL #12: ARTIFACTS DETECTION =========================================== % =================================================================================== disp([10 'DEMO> Tutorial #12: Artifacts detection' 10]); % Process: Detect heartbeats bst_process('CallProcess', 'process_evt_detect_ecg', [sFilesRun1, sFilesRun2], [], ... 'channelname', 'ECG', ... 'timewindow', [], ... 'eventname', 'cardiac'); % Process: Detect eye blinks bst_process('CallProcess', 'process_evt_detect_eog', [sFilesRun1, sFilesRun2], [], ... 'channelname', 'VEOG', ... 'timewindow', [], ... 'eventname', 'blink'); % Process: Remove simultaneous bst_process('CallProcess', 'process_evt_remove_simult', [sFilesRun1, sFilesRun2], [], ... 'remove', 'cardiac', ... 'target', 'blink', ... 'dt', 0.25, ... 'rename', 0); %% ===== TUTORIAL #13: SSP =========================================================== % =================================================================================== disp([10 'DEMO> Tutorial #13: SSP' 10]); % Process: SSP ECG: cardiac bst_process('CallProcess', 'process_ssp_ecg', [sFilesRun1, sFilesRun2], [], ... 'eventname', 'cardiac', ... 'sensortypes', 'MEG', ... 'usessp', 0, ... 'select', 1); % Process: SSP EOG: blink bst_process('CallProcess', 'process_ssp_eog', sFilesRun1, [], ... 'eventname', 'blink', ... 'sensortypes', 'MEG', ... 'usessp', 0, ... 'select', [1 2]); bst_process('CallProcess', 'process_ssp_eog', sFilesRun2, [], ... 'eventname', 'blink', ... 'sensortypes', 'MEG', ... 'usessp', 0, ... 'select', 1); %% ===== TUTORIAL #14: BAD SEGMENTS ================================================== % =================================================================================== disp([10 'DEMO> Tutorial #14: Bad segments' 10]); % Process: Detect other artifacts bst_process('CallProcess', 'process_evt_detect_badsegment', [sFilesRun1, sFilesRun2], [], ... 'timewindow', [], ... 'sensortypes', 'MEG', ... 'threshold', 3, ... % 3 'isLowFreq', 1, ... 'isHighFreq', 1); % Process: Rename event (1-7Hz > saccade) (Run02 only) bst_process('CallProcess', 'process_evt_rename', sFilesRun2, [], ... 'src', '1-7Hz', ... 'dest', 'saccade'); % Manual selection of saccades (cannot be done from the pipeline editor: manual edition of the structures) sMatRun2 = in_bst_data(sFilesRun2{1}, 'F'); iEvtSaccade = find(strcmpi({sMatRun2.F.events.label}, 'saccade')); sMatRun2.F.events(iEvtSaccade).times = [30, 81.5, 104, 142.5, 167, 187.5, 246.5, 319; 31, 83, 105, 144, 168, 188.5, 248, 320]; sMatRun2.F.events(iEvtSaccade).epochs = ones(1, size(sMatRun2.F.events(iEvtSaccade).times, 2)); sMatRun2.F.events(iEvtSaccade).channels = []; sMatRun2.F.events(iEvtSaccade).notes = []; bst_save(file_fullpath(sFilesRun2{1}), sMatRun2, 'v6', 1); % Process: SSP: saccade (Run02 only) bst_process('CallProcess', 'process_ssp', sFilesRun2, [], ... 'timewindow', [], ... 'eventname', 'saccade', ... 'eventtime', [-0.2, 0.2], ... 'bandpass', [1.5, 7], ... 'sensortypes', 'MEG', ... 'usessp', 1, ... 'saveerp', 0, ... 'method', 1, ... 'select', 1); % Process: Detect other artifacts (Run02 only) bst_process('CallProcess', 'process_evt_detect_badsegment', sFilesRun2, [], ... 'timewindow', [], ... 'sensortypes', 'MEG', ... 'threshold', 3, ... % 3 'isLowFreq', 1, ... 'isHighFreq', 1); % Process: Rename event (1-7Hz > bad_1-7Hz) bst_process('CallProcess', 'process_evt_rename', [sFilesRun1, sFilesRun2], [], ... 'src', '1-7Hz', ... 'dest', 'bad_1-7Hz'); % Process: Rename event (40-240Hz > bad_40-240Hz) bst_process('CallProcess', 'process_evt_rename', [sFilesRun1, sFilesRun2], [], ... 'src', '40-240Hz', ... 'dest', 'bad_40-240Hz'); % Process: Snapshot: SSP projectors bst_process('CallProcess', 'process_snapshot', [sFilesRun1, sFilesRun2], [], ... 'target', 2, ... % SSP projectors 'Comment', 'SSP projectors'); %% ===== TUTORIAL #15: IMPORT EVENTS ================================================= % =================================================================================== disp([10 'DEMO> Tutorial #15: Import events' 10]); % Process: Import MEG/EEG: Events (Run01) sFilesEpochs1 = bst_process('CallProcess', 'process_import_data_event', sFilesRun1, [], ... 'subjectname', SubjectName, ... 'condition', '', ... 'eventname', 'standard, deviant', ... 'timewindow', [], ... 'epochtime', [-0.100, 0.500], ... 'createcond', 0, ... 'ignoreshort', 1, ... 'usectfcomp', 1, ... 'usessp', 1, ... 'freq', [], ... 'baseline', [-0.1, -0.0017]); % Process: Import MEG/EEG: Events (Run02) sFilesEpochs2 = bst_process('CallProcess', 'process_import_data_event', sFilesRun2, [], ... 'subjectname', SubjectName, ... 'condition', '', ... 'eventname', 'standard, deviant', ... 'timewindow', [], ... 'epochtime', [-0.100, 0.500], ... 'createcond', 0, ... 'ignoreshort', 1, ... 'usectfcomp', 1, ... 'usessp', 1, ... 'freq', [], ... 'baseline', [-0.1, -0.0017]); % Display raster plot hFigRaster = view_erpimage({sFilesEpochs1.FileName}, 'erpimage', 'MEG'); panel_display(); bst_report('Snapshot', hFigRaster, sFilesEpochs1(1).FileName, 'ERP image'); close(hFigRaster); %% ===== TUTORIAL #16: AVERAGE ======================================================= % =================================================================================== disp([10 'DEMO> Tutorial #16: Average' 10]); % Process: Average: By trial group (folder average) sFilesAvg = bst_process('CallProcess', 'process_average', [sFilesEpochs1, sFilesEpochs2], [], ... 'avgtype', 5, ... % By trial groups (folder average) 'avg_func', 1, ... % Arithmetic average: mean(x) 'weighted', 0, ... 'keepevents', 1); % Process: Delete events 'cardiac' bst_process('CallProcess', 'process_evt_delete', sFilesAvg, [], ... 'eventname', 'cardiac'); % Process: Snapshot: Recordings time series bst_process('CallProcess', 'process_snapshot', sFilesAvg, [], ... 'target', 5, ... % Recordings time series 'modality', 1, ... % MEG (All) 'Comment', 'Evoked response'); % Set colormap: global color scale bst_colormaps('SetMaxMode', 'meg', 'global'); % Process: Snapshot: Recordings topography (contact sheet) bst_process('CallProcess', 'process_snapshot', sFilesAvg, [], ... 'target', 7, ... % Recordings topography (contact sheet) 'modality', 1, ... % MEG 'contact_time', [0, 0.350], ... 'contact_nimage', 15, ... 'Comment', 'Evoked response'); % Process: Average+Stderr: By trial group (subject average) sFilesAvgAll = bst_process('CallProcess', 'process_average', [sFilesEpochs1, sFilesEpochs2], [], ... 'avgtype', 6, ... % By trial group (subject average) 'avg_func', 7, ... % Arithmetic average + Standard error 'weighted', 0, ... 'keepevents', 1); % Process: Delete events 'cardiac' bst_process('CallProcess', 'process_evt_delete', sFilesAvgAll, [], ... 'eventname', 'cardiac'); % Process: Delete events 'saccade' bst_process('CallProcess', 'process_evt_delete', sFilesAvgAll, [], ... 'eventname', 'saccade'); % Process: Snapshot: Recordings time series bst_process('CallProcess', 'process_snapshot', sFilesAvgAll, [], ... 'target', 5, ... % Recordings time series 'modality', 1, ... % MEG (All) 'Comment', 'Evoked response'); %% ===== TUTORIAL #17: EXPLORATION =================================================== % =================================================================================== disp([10 'DEMO> Tutorial #17: Bad segments' 10]); % View averages hFigMeg1 = view_timeseries(sFilesAvg(1).FileName, 'MEG'); hFigMeg2 = view_timeseries(sFilesAvg(2).FileName, 'MEG'); hFigEeg1 = view_timeseries(sFilesAvg(1).FileName, 'Misc'); hFigEeg2 = view_timeseries(sFilesAvg(2).FileName, 'Misc'); hFigTopo1 = view_topography(sFilesAvg(1).FileName, 'MEG', '2DSensorCap'); hFigTopo2 = view_topography(sFilesAvg(2).FileName, 'MEG', '2DSensorCap'); = view_topography(sFilesAvg(3).FileName, 'MEG', '3DSensorCap'); = view_topography(sFilesAvg(3).FileName, 'MEG', '2DDisc'); = view_topography(sFilesAvg(3).FileName, 'MEG', '2DLayout'); % Set time: 90ms panel_time('SetCurrentTime', 0.090); % Set filters: 40Hz low-pass, no high-pass panel_filter('SetFilters', 1, 40, 0, [], 0, [], 0, 0); % View selected sensors SelectedChannels = {'MLC31', 'MLC32'}; bst_figures('SetSelectedRows', SelectedChannels); view_timeseries(sFilesAvg(4).FileName, [], SelectedChannels); % Select time window figure_timeseries('SetTimeSelectionManual', hFigMeg1, [0.070, 0.130]); % Show sensors on 2DSensorCap topography isMarkers = 1; isLabels = 0; figure_3d('ViewSensors', hFigTopo1, isMarkers, isLabels); % Display time contact sheet for a figure pause(0.5); hContactFig = view_contactsheet( hFigTopo2, 'time', 'fig', [], 12, [0 0.120] ); pause(0.5); close(hContactFig); %% ===== TUTORIAL #18: COLORMAPS ===================================================== % =================================================================================== disp([10 'DEMO> Tutorial #18: Colormaps' 10]); % Set 'Meg' colormap to 'jet' bst_colormaps('SetColormapName', 'meg', 'jet'); pause(0.5); % Set 'Meg' colormap to 'rwb' bst_colormaps('SetColormapName', 'meg', 'cmap_rbw'); % Set colormap to display absolute values bst_colormaps('SetColormapAbsolute', 'meg', 1); % Normalize colormap for each time frame bst_colormaps('SetMaxMode', 'meg', 'local'); % Hide colorbar bst_colormaps('SetDisplayColorbar', 'meg', 0); pause(0.5); % Restore colormap to default values bst_colormaps('RestoreDefaults', 'meg'); % Edit good/bad channel for current file gui_edit_channelflag(sFilesAvg(1).FileName); % Close figures pause(0.5); bst_memory('UnloadAll', 'Forced'); %% ===== TUTORIAL #20: HEAD MODEL ==================================================== % =================================================================================== disp([10 'DEMO> Tutorial #20: Head model' 10]); % Process: Compute head model bst_process('CallProcess', 'process_headmodel', sFilesAvg, [], ... 'comment', '', ... 'sourcespace', 1, ... 'meg', 3); % Overlapping spheres % Get study structure sStudy = bst_get('Study', sFilesAvg(1).iStudy); % Show spheres hFig = view_spheres(sStudy.HeadModel(sStudy.iHeadModel).FileName, sStudy.Channel.FileName, sSubject); pause(0.5); close(hFig); %% ===== TUTORIAL #21: NOISE COVARIANCE ============================================== % =================================================================================== disp([10 'DEMO> Tutorial #21: Noise covariance' 10]); % Process: Compute covariance (noise or data) bst_process('CallProcess', 'process_noisecov', sFilesNoise, [], ... 'baseline', [], ... 'sensortypes', 'MEG, EEG, SEEG, ECOG', ... 'target', 1, ... % Noise covariance (covariance over baseline time window) 'dcoffset', 1, ... % Block by block, to avoid effects of slow shifts in data 'identity', 0, ... 'copycond', 1, ... 'copysubj', 0, ... 'replacefile', 1); % Replace % Process: Snapshot: Noise covariance bst_process('CallProcess', 'process_snapshot', sFilesNoise, [], ... 'target', 3, ... % Noise covariance 'Comment', 'Noise covariance'); % Process: Compute covariance (noise or data) [Run01] bst_process('CallProcess', 'process_noisecov', sFilesEpochs1, [], ... 'baseline', [-0.1, -0.0017], ... 'datatimewindow', [0, 0.5], ... 'sensortypes', 'MEG, EEG, SEEG, ECOG', ... 'target', 2, ... % Data covariance (covariance over data time window) 'dcoffset', 1, ... % Block by block, to avoid effects of slow shifts in data 'identity', 0, ... 'copycond', 0, ... 'copysubj', 0, ... 'replacefile', 1); % Replace % Process: Compute covariance (noise or data) [Run02] bst_process('CallProcess', 'process_noisecov', sFilesEpochs2, [], ... 'baseline', [-0.1, -0.0017], ... 'datatimewindow', [0, 0.5], ... 'sensortypes', 'MEG, EEG, SEEG, ECOG', ... 'target', 2, ... % Data covariance (covariance over data time window) 'dcoffset', 1, ... % Block by block, to avoid effects of slow shifts in data 'identity', 0, ... 'copycond', 0, ... 'copysubj', 0, ... 'replacefile', 1); % Replace % Process: Snapshot: Data covariance bst_process('CallProcess', 'process_snapshot', [sFilesEpochs1(1), sFilesEpochs2(1)], [], ... 'target', 12, ... % Data covariance 'Comment', 'Data covariance'); %% ===== TUTORIAL #22: SOURCE ESTIMATION ============================================= % =================================================================================== disp([10 'DEMO> Tutorial #22: Source estimation' 10]); % === GET DEVIANT AVERAGE RUN01 === % Process: Select recordings in: Subject01/S01_AEF_20131218_01_600Hz_notch sFiles01 = bst_process('CallProcess', 'process_select_files_data', [], [], ... 'subjectname', SubjectName, ... 'condition', 'S01_AEF_20131218_01_600Hz_notch', ... 'includebad', 0); % Process: Select file comments with tag: deviant sFilesAvgDeviant01 = bst_process('CallProcess', 'process_select_tag', sFiles01, [], ... 'tag', 'Avg: deviant', ... 'search', 2, ... % Search the file comments 'select', 1); % Select only the files with the tag % === CONSTRAINED EXAMPLE === % Minimum norm options InverseOptions = struct(... 'Comment', 'MN: MEG', ... 'InverseMethod', 'minnorm', ... 'InverseMeasure', 'amplitude', ... 'SourceOrient', {{'fixed'}}, ... 'Loose', 0.2, ... 'UseDepth', 1, ... 'WeightExp', 0.5, ... 'WeightLimit', 10, ... 'NoiseMethod', 'reg', ... 'NoiseReg', 0.1, ... 'SnrMethod', 'fixed', ... 'SnrRms', 0.001, ... 'SnrFixed', 3, ... 'ComputeKernel', 1, ... 'DataTypes', {{'MEG'}}); % Process: Compute sources [2018] sFilesSrcDeviant01 = bst_process('CallProcess', 'process_inverse_2018', sFilesAvgDeviant01, [], ... 'output', 2, ... % Kernel only: one per file 'inverse', InverseOptions); % === DISPLAY SOURCES MANUALLY === % View time series hFigSrc1 = view_timeseries(sFilesAvgDeviant01(1).FileName, 'MEG'); % View on the cortex surface hFigSrc2 = script_view_sources(sFilesSrcDeviant01.FileName, 'cortex'); % Set current time to 90ms panel_time('SetCurrentTime', 0.090); % Set orientation figure_3d('SetStandardView', hFigSrc2, 'left'); % Set surface threshold iSurf = 1; thresh = .30; panel_surface('SetDataThreshold', hFigSrc2, iSurf, thresh); % Set surface smoothing panel_surface('SetSurfaceSmooth', hFigSrc2, iSurf, .6, 0); % Show sulci panel_surface('SetShowSulci', hFigSrc2, iSurf, 1); % View sources on MRI (3D orthogonal slices) hFigSrc3 = script_view_sources(sFilesSrcDeviant01.FileName, 'mri3d'); panel_surface('SetDataThreshold', hFigSrc3, iSurf, thresh); % Set the position of the cuts in the 3D figure cutsPosVox = [74 93 159]; panel_surface('PlotMri', hFigSrc3, cutsPosVox); % View sources with MRI Viewer hFigSrc4 = script_view_sources(sFilesSrcDeviant01.FileName, 'mriviewer'); panel_surface('SetDataThreshold', hFigSrc4, iSurf, thresh); % Set the position of the cuts in the MRI Viewer (values in millimeters) figure_mri('SetLocation', 'voxel', hFigSrc4, [], cutsPosVox); % Close figures close([hFigSrc1 hFigSrc2 hFigSrc3 hFigSrc4]); % === UNCONSTRAINED EXAMPLE === % Unconstrained minnorm InverseOptions.Comment = 'MN: MEG'; InverseOptions.InverseMeasure = 'amplitude'; InverseOptions.SourceOrient = {'free'}; % Process: Compute sources [2018] sFilesSrcUnconst = bst_process('CallProcess', 'process_inverse_2018', sFilesAvgDeviant01, [], ... 'output', 2, ... % Kernel only: one per file 'inverse', InverseOptions); % === NORMALIZED SOURCES === % dSPM InverseOptions.Comment = 'dSPM: MEG'; InverseOptions.InverseMeasure = 'dspm2018'; InverseOptions.SourceOrient = {'fixed'}; sFilesSrcDspm = bst_process('CallProcess', 'process_inverse_2018', sFilesAvgDeviant01, [], ... 'output', 2, ... % Kernel only: one per file 'inverse', InverseOptions); % sLORETA (old function) sFilesSrcSloreta = bst_process('CallProcess', 'process_inverse', sFilesAvgDeviant01, [], ... 'comment', '', ... 'method', 3, ... % sLORETA 'wmne', struct(... 'SourceOrient', {{'fixed'}}, ... 'loose', 0.2, ... 'SNR', 3, ... 'pca', 1, ... 'diagnoise', 0, ... 'regnoise', 1, ... 'magreg', 0.1, ... 'gradreg', 0.1, ... 'depth', 1, ... 'weightexp', 0.5, ... 'weightlimit', 10), ... 'sensortypes', 'MEG, MEG MAG, MEG GRAD, EEG', ... 'output', 2); % Kernel only: one per file % Process: Z-score normalization: [-100ms,-2ms] sFilesSrcZscore = bst_process('CallProcess', 'process_baseline_norm', sFilesSrcDeviant01, [], ... 'baseline', [-0.100, -0.002], ... 'source_abs', 0, ... 'method', 'zscore'); % Z-score transformation: x_std = (x - μ) / σ % Process: Snapshot: Sources (one time) bst_process('CallProcess', 'process_snapshot', sFilesSrcDeviant01, [], ... 'target', 8, ... % Sources (one time) 'orient', 1, ... % left 'time', 0.09, ... 'threshold', 30, ... 'Comment', 'Current density map (Constrained)'); bst_process('CallProcess', 'process_snapshot', sFilesSrcDspm, [], ... 'target', 8, ... % Sources (one time) 'orient', 1, ... % left 'time', 0.09, ... 'threshold', 60, ... 'Comment', 'dSPM'); bst_process('CallProcess', 'process_snapshot', sFilesSrcSloreta, [], ... 'target', 8, ... % Sources (one time) 'orient', 1, ... % left 'time', 0.09, ... 'threshold', 60, ... 'Comment', 'sLORETA'); bst_process('CallProcess', 'process_snapshot', sFilesSrcZscore, [], ... 'target', 8, ... % Sources (one time) 'orient', 1, ... % left 'time', 0.09, ... 'threshold', 60, ... 'Comment', 'Z-score'); bst_process('CallProcess', 'process_snapshot', sFilesSrcUnconst, [], ... 'target', 8, ... % Sources (one time) 'orient', 1, ... % left 'time', 0.0917, ... 'threshold', 0, ... 'Comment', 'Current density map (Unconstrained)'); % === DELETE EXPERIMENTS === % Process: Delete constrained example bst_process('CallProcess', 'process_delete', [sFilesSrcDeviant01, sFilesSrcDspm, sFilesSrcSloreta, sFilesSrcZscore, sFilesSrcUnconst], [], ... 'target', 1); % Delete selected files % === SHARED KERNEL === % Constrained minnorm InverseOptions.Comment = 'MN: MEG'; InverseOptions.InverseMeasure = 'amplitude'; InverseOptions.SourceOrient = {'fixed'}; % Process: Compute sources [2018] sFilesAvgSrc = bst_process('CallProcess', 'process_inverse_2018', sFilesAvg, [], ... 'output', 1, ... % Kernel only: shared 'inverse', InverseOptions); % === AVERAGE SOURCES ACROSS RUNS === % Process: Average: By trial group (subject average) sFilesIntraSrc = bst_process('CallProcess', 'process_average', sFilesAvgSrc, [], ... 'avgtype', 6, ... % By trial group (subject average) 'avg_func', 1, ... % Arithmetic average: mean(x) 'weighted', 1, ... 'scalenormalized', 0); % Process: Low-pass:40Hz sFilesIntraSrcLow = bst_process('CallProcess', 'process_bandpass', sFilesIntraSrc, [], ... 'highpass', 0, ... 'lowpass', 40, ... 'attenuation', 'strict', ... % 60dB 'mirror', 0, ... 'overwrite', 0); % Process: Z-score normalization: [-100ms,-2ms] sFilesIntraZscore = bst_process('CallProcess', 'process_baseline_norm', sFilesIntraSrcLow, [], ... 'baseline', [-0.100, -0.0017], ... 'source_abs', 0, ... 'method', 'zscore'); % Z-score transformation: x_std = (x - μ) / σ % Process: Delete intermediate results bst_process('CallProcess', 'process_delete', sFilesIntraSrcLow, [], ... 'target', 1); % Delete selected files % Screen captures bst_process('CallProcess', 'process_snapshot', sFilesIntraZscore, [], ... 'target', 8, ... % Sources (one time) 'orient', 1, ... % left 'time', 0.09, ... 'threshold', 40, ... 'Comment', 'Average across runs (left)'); bst_process('CallProcess', 'process_snapshot', sFilesIntraZscore, [], ... 'target', 8, ... % Sources (one time) 'orient', 2, ... % right 'time', 0.09, ... 'threshold', 40, ... 'Comment', 'Average across runs (right)'); bst_process('CallProcess', 'process_snapshot', sFilesIntraZscore(1), [], ... 'target', 9, ... % Sources (contact sheet) 'orient', 1, ... % left 'contact_time', [0, 0.35], ... 'contact_nimage', 15, ... 'threshold', 20, ... 'Comment', 'Average across runs'); %% ===== TUTORIAL #23: SCOUTS ======================================================== % =================================================================================== disp([10 'DEMO> Tutorial #23: Scouts' 10]); % Load surface file sCortex = in_tess_bst(CortexFile); % Add new scouts in first atlas sCortex.iAtlas = find(strcmpi({sCortex.Atlas.Name}, 'Destrieux')); % Save file bst_save(file_fullpath(CortexFile), sCortex, 'v7'); % Unload everything bst_memory('UnloadAll', 'Forced'); % Find scouts indices to display: {'A1L', 'A1R', 'IFGL', 'M1L'} [tmp,iScouts,tmp] = intersect({sCortex.Atlas(sCortex.iAtlas).Scouts.Label}, {'G_temp_sup-G_T_transv L', 'G_temp_sup-G_T_transv R', 'G_front_inf-Opercular L', 'G_precentral L'}); % View cortex hFigSurf1 = view_surface(CortexFile, [], [], 'NewFigure'); hFigSurf2 = view_surface(CortexFile, [], [], 'NewFigure'); figure_3d('SetStandardView', hFigSurf1, 'left'); figure_3d('SetStandardView', hFigSurf2, 'right'); panel_surface('SetSurfaceSmooth', hFigSurf1, 1, .6, 0); panel_surface('SetSurfaceSmooth', hFigSurf2, 1, .6, 0); panel_surface('SetShowSulci', hFigSurf1, 1, 1); panel_surface('SetShowSulci', hFigSurf2, 1, 1); % Configure scouts display panel_scout('SetScoutsOptions', 0, 1, 1, 'all', 0.7, 1, 1, 0); % View scouts hFigScouts = view_scouts({sFilesIntraZscore.FileName}, iScouts); hLegend = findobj(hFigScouts, 'Type', 'legend'); if ~isempty(hLegend) && ishandle(hLegend(1)) set(hLegend(1), 'Units', 'pixels'); pos = get(hLegend(1), 'Position'); set(hLegend(1), 'Position', [1, 1, pos(3), pos(4)]); % Save figures bst_report('Snapshot', hFigScouts, sFilesIntraZscore(1).FileName, 'Scouts', [100 100 670 250]); % Close all pause(1); bst_memory('UnloadAll', 'Forced'); %% ===== TUTORIAL #24: TIME-FREQUENCY ================================================ % =================================================================================== disp([10 'DEMO> Tutorial #24: Time-frequency' 10]); % Process: Simulate generic signals sSim = bst_process('CallProcess', 'process_simulate_matrix', [], [], ... 'subjectname', 'Test', ... 'condition', 'Simulation', ... 'samples', 6000, ... 'srate', 1000, ... 'matlab', ['f1 = 2; f2 = 20; f3 = 50;' 10 'i =2000:6000;' 10 'Data(1,i) = sin(f1*2*pi*t(i)) + 0.4 * cos(f2*2*pi*t(i));' 10 'Data = Data + 0.2 * sin(f3*2*pi*t) + 0.4 * rand(1,6000);']); % Time-frequency options TfOptions = struct(... 'Comment', 'Power,1-60Hz', ... 'TimeBands', [], ... 'Freqs', [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60], ... 'MorletFc', 1, ... 'MorletFwhmTc', 3, ... 'ClusterFuncTime', 'none', ... 'Measure', 'power', ... 'Output', 'average', ... 'SaveKernel', 0); % Process: Time-frequency (Morlet wavelets) sSimTf1 = bst_process('CallProcess', 'process_timefreq', sSim, [], ... 'edit', TfOptions, ... 'normalize', 'multiply'); % 1/f compensation: Multiply output values by frequency % === NORMALIZATION === % Process: Time-frequency (Morlet wavelets) sSimTf2 = bst_process('CallProcess', 'process_timefreq', sSim, [], ... 'edit', TfOptions, ... 'normalize', 'none'); % None: Save non-standardized time-frequency maps % Process: Spectral flattening sSimTf2Multi = bst_process('CallProcess', 'process_tf_norm', sSimTf2, [], ... 'normalize', 'multiply', ... % 1/f compensation (multiple by frequency) 'overwrite', 0); % Process: Event-related perturbation (ERS/ERD): [750ms,1250ms] sSimTf2Ersd = bst_process('CallProcess', 'process_baseline_norm', sSimTf2, [], ... 'baseline', [0.75, 1.25], ... 'method', 'ersd', ... % Event-related perturbation (ERS/ERD): x_std = (x - μ) / μ * 100 'overwrite', 0); % Process: Snapshot: Time-frequency maps bst_process('CallProcess', 'process_snapshot', sSimTf2, [], ... 'target', 14, ... % Time-frequency maps 'Comment', 'Not normalized'); % Process: Snapshot: Time-frequency maps bst_process('CallProcess', 'process_snapshot', sSimTf2Multi, [], ... 'target', 14, ... % Time-frequency maps 'Comment', 'Spectral flattening: 1/f compensation'); % Process: Snapshot: Time-frequency maps bst_process('CallProcess', 'process_snapshot', sSimTf2Ersd, [], ... 'target', 14, ... % Time-frequency maps 'Comment', 'ERS/ERD'); % Spectrum/Time series hFigTf1 = view_spectrum(sSimTf2.FileName, 'Spectrum'); hFigTf2 = view_spectrum(sSimTf2.FileName, 'TimeSeries'); panel_time('SetCurrentTime', 0.5); panel_freq('SetCurrentFreq', 2, 0); bst_report('Snapshot', [hFigTf1 hFigTf2], sSimTf2.FileName, 'Not normalized: 2s/20Hz', [200, 200, 400, 250]); panel_time('SetCurrentTime', 2.02); panel_freq('SetCurrentFreq', 20, 0); bst_report('Snapshot', [hFigTf1 hFigTf2], sSimTf2.FileName, 'Not normalized: 2s/20Hz', [200, 200, 400, 250]); bst_memory('UnloadAll', 'Forced'); % === HILBERT TRANSFORM === % Process: Hilbert transform sSimHilbert = bst_process('CallProcess', 'process_hilbert', sSim, [], ... 'edit', struct(... 'Comment', 'Power', ... 'TimeBands', [], ... 'Freqs', {{'delta', '2, 4', 'mean'; 'theta', '5, 7', 'mean'; 'alpha', '8, 12', 'mean'; 'beta', '15, 29', 'mean'; 'gamma1', '30, 59', 'mean'; 'gamma2', '60, 90', 'mean'}}, ... 'ClusterFuncTime', 'none', ... 'Measure', 'power', ... 'Output', 'all', ... 'SaveKernel', 0), ... 'normalize', 'none', ... % None: Save non-standardized time-frequency maps 'mirror', 0); % Process: Spectral flattening sSimHilbertMulti = bst_process('CallProcess', 'process_tf_norm', sSimHilbert, [], ... 'normalize', 'multiply', ... % 1/f compensation (multiple by frequency) 'overwrite', 0); % Process: Event-related perturbation (ERS/ERD): [750ms,1250ms] sSimHilbertErsd = bst_process('CallProcess', 'process_baseline_norm', sSimHilbert, [], ... 'baseline', [0.75, 1.25], ... 'method', 'ersd', ... % Event-related perturbation (ERS/ERD): x_std = (x - μ) / μ * 100 'overwrite', 0); % Process: Snapshot: Time-frequency maps bst_process('CallProcess', 'process_snapshot', sSimHilbert, [], ... 'target', 14, ... % Time-frequency maps 'Comment', 'Not normalized'); % Process: Snapshot: Time-frequency maps bst_process('CallProcess', 'process_snapshot', sSimHilbertMulti, [], ... 'target', 14, ... % Time-frequency maps 'Comment', 'Spectral flattening: 1/f compensation'); % Process: Snapshot: Time-frequency maps bst_process('CallProcess', 'process_snapshot', sSimHilbertErsd, [], ... 'target', 14, ... % Time-frequency maps 'Comment', 'ERS/ERD'); % === SINGLE TRIALS === TfOptions.Comment = 'Avg,Power,1-150Hz'; TfOptions.Freqs = [1, 2, 3.1, 4.2, 5.4, 6.7, 8, 9.5, 11, 12.6, 14.3, 16.1, 18.1, 20.1, 22.3, 24.6, 27, 29.6, 32.4, 35.3, 38.4, 41.6, 45.1, 48.8, 52.7, 56.9, 61.3, 66, 70.9, 76.2, 81.8, 87.7, 94, 100.6, 107.7, 115.2, 123.1, 131.6, 140.5, 150]; % Process: Time-frequency (Morlet wavelets) sEpochsAvgTf = bst_process('CallProcess', 'process_timefreq', sFilesEpochs1, [], ... 'sensortypes', 'MEG, EEG', ... 'edit', TfOptions, ... 'normalize', 'none'); % None: Save non-standardized time-frequency maps % Process: Event-related perturbation (ERS/ERD): [-75ms,0ms] sEpochsAvgTfErsd = bst_process('CallProcess', 'process_baseline_norm', sEpochsAvgTf, [], ... 'baseline', [-0.075, 0], ... 'method', 'ersd', ... % Event-related perturbation (ERS/ERD): x_std = (x - μ) / μ * 100 'overwrite', 0); % === DISPLAY === % View time-frequency file hFigTf1 = view_timefreq(sEpochsAvgTfErsd.FileName, 'SingleSensor'); % Configure display sOptions = panel_display('GetDisplayOptions'); sOptions.HideEdgeEffects = 1; sOptions.HighResolution = 1; panel_display('SetDisplayOptions', sOptions); % Other display modes hFigTf2 = view_timefreq(sEpochsAvgTfErsd.FileName, 'AllSensors'); hFigTf3 = view_timefreq(sEpochsAvgTfErsd.FileName, '2DLayout'); hFigTf4 = view_timefreq(sEpochsAvgTfErsd.FileName, '2DLayoutOpt'); bst_colormaps('SetColormapName', 'stat2', 'jet'); bst_colormaps('SetColormapAbsolute', 'stat2', 1); bst_report('Snapshot', hFigTf1, sEpochsAvgTfErsd.FileName, 'Time-frequency', [200, 200, 400, 250]); bst_report('Snapshot', [hFigTf2 hFigTf3 hFigTf4], sEpochsAvgTfErsd.FileName, 'Time-frequency', [200, 200, 750, 400]); close([hFigTf1 hFigTf2 hFigTf3 hFigTf4]); % Image [channel x time] hFigTf5 = view_erpimage(sEpochsAvgTfErsd.FileName, 'trialimage'); % Topographies hFigTf6 = view_topography(sEpochsAvgTfErsd.FileName, 'MEG', '3DSensorCap'); hFigTf7 = view_topography(sEpochsAvgTfErsd.FileName, 'MEG', '2DDisc'); hFigTf8 = view_topography(sEpochsAvgTfErsd.FileName, 'MEG', '2DSensorCap'); hFigTf9 = view_topography(sEpochsAvgTfErsd.FileName, 'MEG', '2DLayout'); panel_time('SetCurrentTime', 0.175); panel_freq('SetCurrentFreq', 8, 0); bst_report('Snapshot', [hFigTf5 hFigTf6 hFigTf7 hFigTf8 hFigTf9], sEpochsAvgTfErsd.FileName, 'Time-frequency: 8Hz', [200, 200, 400, 250]); close([hFigTf5 hFigTf6 hFigTf7 hFigTf8 hFigTf9]); % === AVERAGE FOR SCOUTS === % Select all sources for the single deviant epochs sFilesEpochDeviantSrc = bst_process('CallProcess', 'process_select_files_results', [], [], ... 'subjectname', SubjectName, ... 'condition', '', ... 'includebad', 0); sFilesEpochDeviantSrc = bst_process('CallProcess', 'process_select_tag', sFilesEpochDeviantSrc, [], ... 'tag', 'deviant', ... 'search', 1, ... % Search the file names 'select', 1); % Select only the files with the tag sFilesEpochDeviantSrc = bst_process('CallProcess', 'process_select_tag', sFilesEpochDeviantSrc, [], ... 'tag', 'average', ... 'search', 1, ... % Search the file names 'select', 2); % Exclude the files with the tag % Process: Time-frequency (Morlet wavelets) sFilesTfScout = bst_process('CallProcess', 'process_timefreq', sFilesEpochDeviantSrc, [], ... 'clusters', {'Destrieux', {'G_temp_sup-G_T_transv L', 'G_temp_sup-G_T_transv R', 'G_front_inf-Opercular L', 'G_precentral L'}}, ... 'scoutfunc', 1, ... % Mean 'edit', struct(... 'Comment', 'Deviant: Scouts,Avg,Power,1-150Hz', ... 'TimeBands', [], ... 'Freqs', [1, 2, 3.1, 4.2, 5.4, 6.7, 8, 9.5, 11, 12.6, 14.3, 16.1, 18.1, 20.1, 22.3, 24.6, 27, 29.6, 32.4, 35.3, 38.4, 41.6, 45.1, 48.8, 52.7, 56.9, 61.3, 66, 70.9, 76.2, 81.8, 87.7, 94, 100.6, 107.7, 115.2, 123.1, 131.6, 140.5, 150], ... 'MorletFc', 1, ... 'MorletFwhmTc', 3, ... 'ClusterFuncTime', 'after', ... 'Measure', 'power', ... 'Output', 'average', ... 'SaveKernel', 0), ... 'normalize', 'none'); % None: Save non-standardized time-frequency maps) % Process: Event-related perturbation (ERS/ERD): [-75ms,0ms] sFilesTfScoutErsd = bst_process('CallProcess', 'process_baseline_norm', sFilesTfScout, [], ... 'baseline', [-0.075, 0], ... 'method', 'ersd', ... % Event-related perturbation (ERS/ERD): x_std = (x - μ) / μ * 100 'overwrite', 0); % Process: Snapshot: Time-frequency maps bst_process('CallProcess', 'process_snapshot', sFilesTfScoutErsd, [], ... 'target', 14, ... % Time-frequency maps 'Comment', 'ERS/ERD'); % === FULL CORTEX / HILBERT === % Process: Hilbert transform sFilesHilbertCortex = bst_process('CallProcess', 'process_hilbert', sFilesEpochDeviantSrc, [], ... 'clusters', {}, ... 'scoutfunc', 1, ... % Mean 'edit', struct(... 'Comment', 'Deviant: Avg,Magnitude', ... 'TimeBands', [], ... 'Freqs', {{'delta', '2, 4', 'mean'; 'theta', '5, 7', 'mean'; 'alpha', '8, 12', 'mean'; 'beta', '15, 29', 'mean'; 'gamma1', '30, 59', 'mean'; 'gamma2', '60, 90', 'mean'}}, ... 'ClusterFuncTime', 'none', ... 'Measure', 'power', ... 'Output', 'average', ... 'RemoveEvoked', 0, ... 'SaveKernel', 0), ... 'normalize', 'none', ... % None: Save non-standardized time-frequency maps 'mirror', 0); % Process: Event-related perturbation (ERS/ERD): [-75ms,0ms] sFilesHilbertCortexErsd = bst_process('CallProcess', 'process_baseline_norm', sFilesHilbertCortex, [], ... 'baseline', [-0.075, 0], ... 'method', 'ersd', ... % Event-related perturbation (ERS/ERD): x_std = (x - μ) / μ * 100 'overwrite', 0); % View results hFigTf1 = view_surface_data([], sFilesHilbertCortexErsd.FileName); hFigTf2 = view_timefreq(sFilesHilbertCortexErsd.FileName, 'SingleSensor', 362); figure_3d('SetStandardView', hFigTf1, 'left'); panel_surface('SetDataThreshold', hFigTf1, 1, 0.5); panel_time('SetCurrentTime', 0.175); panel_freq('SetCurrentFreq', 3); bst_colormaps('RestoreDefaults', 'stat2'); bst_report('Snapshot', [hFigTf1 hFigTf2], sFilesHilbertCortexErsd.FileName, 'Hilbert transform: Alpha band', [200, 200, 400, 250]); bst_memory('UnloadAll', 'Forced'); %% ===== TUTORIAL #25: DIFFRERENCE =================================================== % =================================================================================== disp([10 'DEMO> Tutorial #25: Difference' 10]); % ===== SELECT TRIALS (DATA) ===== % Process: Select recordings in: Subject01/* sFilesAll = bst_process('CallProcess', 'process_select_files_data', [], [], ... 'subjectname', SubjectName, ... 'condition', '', ... 'includebad', 0); % Process: Select file names with tag: deviant_trial sEpochDeviant = bst_process('CallProcess', 'process_select_tag', sFilesAll, [], ... 'tag', 'deviant_trial', ... 'search', 1, ... % Search the file names 'select', 1); % Select only the files with the tag % Process: Select file names with tag: standard_trial sEpochStandard = bst_process('CallProcess', 'process_select_tag', sFilesAll, [], ... 'tag', 'standard_trial', ... 'search', 1, ... % Search the file names 'select', 1); % Select only the files with the tag % ===== SELECT TRIALS (SOURCE) ===== % Process: Select recordings in: Subject01/* sFilesAllSrc = bst_process('CallProcess', 'process_select_files_results', [], [], ... 'subjectname', SubjectName, ... 'condition', '', ... 'includebad', 0); % Process: Select file names with tag: deviant_trial sEpochDeviantSrc = bst_process('CallProcess', 'process_select_tag', sFilesAllSrc, [], ... 'tag', 'deviant_trial', ... 'search', 1, ... % Search the file names 'select', 1); % Select only the files with the tag % Process: Select file names with tag: standard_trial sEpochStandardSrc = bst_process('CallProcess', 'process_select_tag', sFilesAllSrc, [], ... 'tag', 'standard_trial', ... 'search', 1, ... % Search the file names 'select', 1); % Select only the files with the tag % ===== ABSOLUTE DIFFERENCE ====== % Process: Difference: A-B, abs sDiffSrc = bst_process('CallProcess', 'process_diff_ab', sFilesIntraSrc(1).FileName, sFilesIntraSrc(2).FileName, ... 'source_abs', 1); % Process: Set comment: deviant|abs - standard|abs sDiffSrc = bst_process('CallProcess', 'process_set_comment', sDiffSrc, [], ... 'tag', 'deviant|abs - standard|abs', ... 'isindex', 1); % Process: Low-pass:40Hz sDiffSrcZscore = bst_process('CallProcess', 'process_bandpass', sDiffSrc, [], ... 'highpass', 0, ... 'lowpass', 40, ... 'attenuation', 'strict', ... % 60dB 'mirror', 0, ... 'overwrite', 1); % Process: Z-score transformation: [-100ms,-2ms] sDiffSrcZscore = bst_process('CallProcess', 'process_baseline_norm', sDiffSrcZscore, [], ... 'baseline', [-0.1, -0.002], ... 'source_abs', 0, ... 'method', 'zscore', ... % Z-score transformation: x_std = (x - μ) / σ 'overwrite', 0); % Process: Snapshot: Sources (contact sheet) bst_process('CallProcess', 'process_snapshot', sDiffSrcZscore, [], ... 'target', 9, ... % Sources (contact sheet) 'modality', 1, ... % MEG (All) 'orient', 1, ... % left 'contact_time', [0, 0.35], ... 'contact_nimage', 15, ... 'threshold', 30, ... 'Comment', 'Difference deviant - standard (absolute)'); % ===== RELATIVE DIFFERENCE ===== % Process: Difference: A-B sDiffSrcRel = bst_process('CallProcess', 'process_diff_ab', sFilesIntraSrc(1).FileName, sFilesIntraSrc(2).FileName, ... 'source_abs', 0); % Process: Set comment: deviant - standard sDiffSrcRel = bst_process('CallProcess', 'process_set_comment', sDiffSrcRel, [], ... 'tag', 'deviant - standard', ... 'isindex', 1); % Process: Low-pass:40Hz sDiffSrcRelZscore = bst_process('CallProcess', 'process_bandpass', sDiffSrcRel, [], ... 'highpass', 0, ... 'lowpass', 40, ... 'attenuation', 'strict', ... % 60dB 'mirror', 0, ... 'overwrite', 1); % Process: Z-score transformation: [-100ms,-2ms] sDiffSrcRelZscore = bst_process('CallProcess', 'process_baseline_norm', sDiffSrcRelZscore, [], ... 'baseline', [-0.1, -0.002], ... 'source_abs', 0, ... 'method', 'zscore', ... % Z-score transformation: x_std = (x - μ) / σ 'overwrite', 0); % Configure colormap: hot/absolute bst_colormaps('SetColormapName', 'stat2', 'hot'); bst_colormaps('SetColormapAbsolute', 'stat2', 1); % Process: Snapshot: Sources (contact sheet) bst_process('CallProcess', 'process_snapshot', sDiffSrcRelZscore, [], ... 'target', 9, ... % Sources (contact sheet) 'modality', 1, ... % MEG (All) 'orient', 1, ... % left 'contact_time', [0, 0.35], ... 'contact_nimage', 15, ... 'threshold', 30, ... 'Comment', 'Difference deviant - standard (relative)'); % Restore colormap: rwb/relative bst_colormaps('SetColormapName', 'stat2', 'cmap_rbw'); bst_colormaps('SetColormapAbsolute', 'stat2', 0); % ===== DIFFERENCE OF MEANS ===== % Process: Select uniform number of files [uniform] [sEpochDeviantUni, sEpochStandardUni] = bst_process('CallProcess', 'process_select_uniform2', sEpochDeviant, sEpochStandard, ... 'nfiles', 0, ... 'method', 4); % Uniformly distributed % Process: Difference of means [mean] sDiffMean = bst_process('CallProcess', 'process_diff_mean', sEpochDeviantUni, sEpochStandardUni, ... 'avg_func', 1, ... % Arithmetic average mean(A) - mean(B) 'weighted', 0); % Process: Snapshot: Recordings time series bst_process('CallProcess', 'process_snapshot', sDiffMean, [], ... 'target', 5, ... % Recordings time series 'modality', 1, ... % MEG (All) 'Comment', 'Difference of means'); %% ===== TUTORIAL #26: STATISTICS ==================================================== % =================================================================================== disp([10 'DEMO> Tutorial #26: Statistics' 10]); % ===== HISTOGRAMS ===== % Process: Extract values: [160ms] MLP57 sHistoDeviant = bst_process('CallProcess', 'process_extract_values', sEpochDeviant, [], ... 'timewindow', [0.16, 0.16], ... 'sensortypes', 'MLP57', ... 'isabs', 0, ... 'avgtime', 0, ... 'avgrow', 0, ... 'dim', 2, ... % Concatenate time (dimension 2) 'Comment', ''); % Process: Extract values: [160ms] MLP57 sHistoStandard = bst_process('CallProcess', 'process_extract_values', sEpochStandard, [], ... 'timewindow', [0.16, 0.16], ... 'sensortypes', 'MLP57', ... 'isabs', 0, ... 'avgtime', 0, ... 'avgrow', 0, ... 'dim', 2, ... % Concatenate time (dimension 2) 'Comment', ''); % Display histograms hFigHisto = view_histogram({sHistoDeviant.FileName, sHistoStandard.FileName}); bst_report('Snapshot', hFigHisto, sHistoDeviant.FileName, 'Histograms for MLP57/160ms'); close(hFigHisto); % ===== EXEMPLE #1: PARAMETRIC/DATA ===== % Process: t-test [equal] [-100ms,500ms] H0:(A-B = 0) sTestParamData = bst_process('CallProcess', 'process_test_parametric2', sEpochDeviant, sEpochStandard, ... 'timewindow', [-0.1, 0.5], ... 'sensortypes', '', ... 'isabs', 0, ... 'avgtime', 0, ... 'avgrow', 0, ... 'Comment', '', ... 'test_type', 'ttest_equal', ... % Student's t-test (equal variance) t = (mean(A)-mean(B)) / (Sx * sqrt(1/nA + 1/nB))Sx = sqrt(((nA-1)*var(A) + (nB-1)*var(B)) / (nA+nB-2)) df = nA + nB - 2 'tail', 'two'); % Two-tailed % Set display properties StatThreshOptions = bst_get('StatThreshOptions'); StatThreshOptions.pThreshold = 0.05; StatThreshOptions.Correction = 'fdr'; StatThreshOptions.Control = [1 2 3]; bst_set('StatThreshOptions', StatThreshOptions); % Process: Snapshot: Recordings time series bst_process('CallProcess', 'process_snapshot', sTestParamData, [], ... 'target', 5, ... % Recordings time series 'modality', 1, ... % MEG (All) 'time', 0.16, ... 'Comment', 'Parametric t-test (p<0.05, FDR)'); % Process: Snapshot: Recordings topography (one time) bst_process('CallProcess', 'process_snapshot', sTestParamData, [], ... 'target', 6, ... % Recordings topography (one time) 'modality', 1, ... % MEG (All) 'time', 0.16, ... 'Comment', 'Parametric t-test (p<0.05, FDR)'); % ===== EXEMPLE #2: NON-PARAMETRIC/DATA ===== % Process: Perm t-test equal [-100ms,500ms MEG] H0:(A=B), H1:(A<>B) sTestPermData = bst_process('CallProcess', 'process_test_permutation2', sEpochDeviant, sEpochStandard, ... 'timewindow', [-0.1, 0.5], ... 'sensortypes', 'MEG', ... 'isabs', 0, ... 'avgtime', 0, ... 'avgrow', 0, ... 'iszerobad', 1, ... 'Comment', '', ... 'test_type', 'ttest_equal', ... % Student's t-test (equal variance) t = (mean(A)-mean(B)) / (Sx * sqrt(1/nA + 1/nB))Sx = sqrt(((nA-1)*var(A) + (nB-1)*var(B)) / (nA+nB-2)) 'randomizations', 1000, ... 'tail', 'two'); % Two-tailed % Process: Snapshot: Recordings time series bst_process('CallProcess', 'process_snapshot', sTestPermData, [], ... 'target', 5, ... % Recordings time series 'modality', 1, ... % MEG (All) 'time', 0.16, ... 'Comment', 'Non-parametric t-test (p<0.05, FDR)'); % Process: Snapshot: Recordings topography (one time) bst_process('CallProcess', 'process_snapshot', sTestPermData, [], ... 'target', 6, ... % Recordings topography (one time) 'modality', 1, ... % MEG (All) 'time', 0.16, ... 'Comment', 'Non-parametric t-test (p<0.05, FDR)'); % ===== EXEMPLE #3: CLUSTER/DATA ===== % Process: FT t-test unequal cluster [-100ms,500ms MEG] H0:(A=B), H1:(A<>B) sTestClustData = bst_process('CallProcess', 'process_ft_timelockstatistics', sEpochDeviant, sEpochStandard, ... 'sensortypes', 'MEG', ... 'timewindow', [-0.1, 0.5], ... 'isabs', 0, ... 'avgtime', 0, ... 'avgchan', 0, ... 'randomizations', 1000, ... 'statistictype', 1, ... % Independent t-test 'tail', 'two', ... % Two-tailed 'correctiontype', 2, ... % cluster 'minnbchan', 0, ... 'clusteralpha', 0.05); % Process: Snapshot: Recordings time series bst_process('CallProcess', 'process_snapshot', sTestClustData, [], ... 'target', 5, ... % Recordings time series 'time', 0.16, ... 'modality', 1, ... % MEG (All) 'Comment', 'Cluster-based permutation test'); % Process: Snapshot: Recordings topography (one time) bst_process('CallProcess', 'process_snapshot', sTestClustData, [], ... 'target', 6, ... % Recordings topography (one time) 'modality', 1, ... % MEG (All) 'time', 0.16, ... 'Comment', 'Cluster-based permutation test'); % ===== EXAMPLE #4: PARAMETRIC/SOURCES ===== % Process: t-test [equal] [-100ms,500ms] H0:(A-B = 0) sTestParamSrc = bst_process('CallProcess', 'process_test_parametric2', sEpochDeviantSrc, sEpochStandardSrc, ... 'timewindow', [-0.1, 0.5], ... 'scoutsel', {}, ... 'scoutfunc', 1, ... % Mean 'isnorm', 0, ... 'avgtime', 0, ... 'Comment', '', ... 'test_type', 'ttest_equal', ... % Student's t-test (equal variance) t = (mean(A)-mean(B)) / (Sx * sqrt(1/nA + 1/nB))Sx = sqrt(((nA-1)*var(A) + (nB-1)*var(B)) / (nA+nB-2)) df = nA + nB - 2 'tail', 'two'); % Two-tailed % Process: Difference of means [abs(mean)] sDiffMeanSrc = bst_process('CallProcess', 'process_diff_mean', sEpochDeviantSrc, sEpochStandardSrc, ... 'avg_func', 2, ... % Absolute value of average abs(mean(A)) - abs(mean(B)) 'weighted', 0); % Process: Apply statistic threshold: p<0.05 (FDR:1,2,3) sDiffMeanSrcThresh = bst_process('CallProcess', 'process_extract_pthresh2', sTestParamSrc, sDiffMeanSrc, ... 'pthresh', 0.05, ... 'correction', 3, ... % False discovery rate (FDR) 'control1', 1, ... 'control2', 1, ... 'control3', 1); % Process: Snapshot: Sources (one time) bst_process('CallProcess', 'process_snapshot', sTestParamSrc, [], ... 'target', 8, ... % Sources (one time) 'orient', 1, ... % left 'time', 0.148, ... 'threshold', 40, ... 'Comment', 'Parametric t-test (p<0.05, FDR)'); % Process: Snapshot: Sources (one time) bst_process('CallProcess', 'process_snapshot', sDiffMeanSrc, [], ... 'target', 8, ... % Sources (one time) 'orient', 1, ... % left 'time', 0.148, ... 'threshold', 40, ... 'Comment', 'abs(average(deviant)) - abs(average(standard))'); % Process: Snapshot: Sources (one time) bst_process('CallProcess', 'process_snapshot', sDiffMeanSrcThresh, [], ... 'target', 8, ... % Sources (one time) 'orient', 1, ... % left 'time', 0.148, ... 'threshold', 0, ... 'Comment', 'Different of mean thresholded with t-test results'); % ===== EXAMPLE #5: PARAMETRIC/SCOUTS ===== % Process: t-test equal [-100ms,500ms] H0:(A=B), H1:(A<>B) sTestParamScout = bst_process('CallProcess', 'process_test_parametric2', sEpochDeviantSrc, sEpochStandardSrc, ... 'timewindow', [-0.1, 0.5], ... 'scoutsel', {'Destrieux', {'G_front_inf-Opercular L', 'G_precentral L', 'G_temp_sup-G_T_transv L'}}, ... 'scoutfunc', 1, ... % Mean 'isnorm', 0, ... 'avgtime', 0, ... 'Comment', '', ... 'test_type', 'ttest_equal', ... % Student's t-test (equal variance) t = (mean(A)-mean(B)) / (Sx * sqrt(1/nA + 1/nB))Sx = sqrt(((nA-1)*var(A) + (nB-1)*var(B)) / (nA+nB-2)) df = nA + nB - 2 'tail', 'two'); % Two-tailed % Process: Apply statistic threshold: p<0.05 (FDR:1,2,3) sTestParamScoutThresh = bst_process('CallProcess', 'process_extract_pthresh', sTestParamScout, [], ... 'pthresh', 0.05, ... 'correction', 3, ... % False discovery rate (FDR) 'control1', 1, ... 'control2', 1, ... 'control3', 1); % Process: Compute head model bst_process('CallProcess', 'process_headmodel', sTestParamScoutThresh, [], ... 'sourcespace', 1, ... % Cortex surface 'meg', 3); % Overlapping spheres % Process: Simulate recordings from scouts sSimulData = bst_process('CallProcess', 'process_simulate_recordings', sTestParamScoutThresh, [], ... 'scouts', {'Destrieux', {'G_front_inf-Opercular L', 'G_precentral L', 'G_temp_sup-G_T_transv L'}}, ... 'savesources', 1); % Get corresponding source file [sStudy,iStudy,iRes] = bst_get('ResultsForDataFile', sSimulData.FileName); sSimulSrc = sStudy.Result(iRes).FileName; % Reset visualization filters panel_filter('SetFilters', 0, [], 0, [], 0, [], 0, 0); % Process: Snapshot: Recordings time series bst_process('CallProcess', 'process_snapshot', sTestParamScout, [], ... 'target', 5, ... % Recordings time series 'time', 0.148, ... 'Comment', 'Parametric t-test (p<0.05, FDR)'); % Process: Snapshot: Sources (one time) bst_process('CallProcess', 'process_snapshot', sSimulSrc, [], ... 'target', 8, ... % Sources (one time) 'orient', 1, ... % left 'time', 0.148, ... 'threshold', 0, ... 'Comment', 'Simulated sources'); % Process: Snapshot: Recordings time series bst_process('CallProcess', 'process_snapshot', sSimulData, [], ... 'target', 5, ... % Recordings time series 'modality', 1, ... % MEG (All) 'time', 0.148, ... 'Comment', 'Simulated MEG recordings'); % ===== EXAMPLE #6: NON-PARAMETRIC/TIMEFREQ ===== TfOptions.Output = 'all'; % Process: Time-frequency (Morlet wavelets) / DEVIANT sEpochDeviantTf = bst_process('CallProcess', 'process_timefreq', sEpochDeviant, [], ... 'sensortypes', 'MLP57', ... 'edit', TfOptions, ... 'normalize', 'none'); % None: Save non-standardized time-frequency maps % Process: Time-frequency (Morlet wavelets) / STANDARD sEpochStandardTf = bst_process('CallProcess', 'process_timefreq', sEpochStandard, [], ... 'sensortypes', 'MLP57', ... 'edit', TfOptions, ... 'normalize', 'none'); % None: Save non-standardized time-frequency maps % Process: Perm t-test equal [-100ms,500ms 1-150Hz] H0:(A=B), H1:(A<>B) sTestTf = bst_process('CallProcess', 'process_test_permutation2', sEpochDeviantTf, sEpochStandardTf, ... 'timewindow', [-0.1, 0.5], ... 'freqrange', [1, 150], ... 'rows', '', ... 'isabs', 0, ... 'avgtime', 0, ... 'avgrow', 0, ... 'avgfreq', 0, ... 'matchrows', 0, ... 'iszerobad', 1, ... 'Comment', '', ... 'test_type', 'ttest_equal', ... % Student's t-test (equal variance) t = (mean(A)-mean(B)) / (Sx * sqrt(1/nA + 1/nB))Sx = sqrt(((nA-1)*var(A) + (nB-1)*var(B)) / (nA+nB-2)) 'randomizations', 1000, ... 'tail', 'two'); % Two-tailed % Set stat threshold StatThreshOptions.pThreshold = 0.05; StatThreshOptions.Correction = 'none'; bst_set('StatThreshOptions', StatThreshOptions); % Process: Snapshot: Time-frequency maps bst_process('CallProcess', 'process_snapshot', sTestTf, [], ... 'target', 14, ... % Time-frequency maps 'Comment', 'Non-parametric t-test (p<0.05, Uncorrected)'); % Process: Delete intermediate results bst_process('CallProcess', 'process_delete', [sEpochDeviantTf, sEpochStandardTf], [], ... 'target', 1); % Delete selected files %% ===== SAVE REPORT ===== % Save and display report ReportFile = bst_report('Save', []); if ~isempty(reports_dir) && ~isempty(ReportFile) bst_report('Export', ReportFile, reports_dir); bst_report('Open', ReportFile); disp([10 'DEMO> Done.' 10]); id="line-1033">

illustrating how to create loops, look at the tutorial MEG visual: single subject. brainstorm3/toolbox/script/tutorial_visual_single.m - Report: report_TutorialVisual_sub001.html
1 function tutorial_visual_single(bids_dir, reports_dir) % TUTORIAL_VISUAL_SINGLE: Runs the Brainstorm/SPM group analysis pipeline (single subject, BIDS version). % % ONLINE TUTORIALS: https://neuroimage.usc.edu/brainstorm/Tutorials/VisualSingle % % INPUTS: % - bids_dir: Path to folder ds000117 (https://openneuro.org/datasets/ds000117) % |- derivatives/freesurfer/sub-XX : Segmentation folders generated with FreeSurfer % |- derivatives/meg_derivatives/sub-XX/ses-meg/meg/*.fif : MEG+EEG recordings (processed with MaxFilter's SSS) % |- derivatives/meg_derivatives/sub-emptyroom/ses-meg/meg/*.fif : Empty room measurements % - reports_dir: If defined, exports all the reports as HTML to this folder % @============================================================================= % This function is part of the Brainstorm software: % https://neuroimage.usc.edu/brainstorm % % Copyright (c) University of Southern California & McGill University % This software is distributed under the terms of the GNU General Public License % as published by the Free Software Foundation. Further details on the GPLv3 % license can be found at http://www.gnu.org/copyleft/gpl.html. % % FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE % UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY % WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF % MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY % LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE. % % For more information type "brainstorm license" at command prompt. % =============================================================================@ % % Author: Francois Tadel, Elizabeth Bock, 2016-2018 %% ===== SCRIPT VARIABLES ===== % Full list of subjects to process SubjectNames = {'sub-01', 'sub-02', 'sub-03', 'sub-04', 'sub-05', 'sub-06', 'sub-07', 'sub-08', ... 'sub-09', 'sub-10', 'sub-11', 'sub-12', 'sub-13', 'sub-14', 'sub-15', 'sub-16'}; % Empty-room dates for each subject (so that we can match automatically recordings with empty-room) EmptyRoomSubj = 'sub-emptyroom'; AcquisitionDates = {'09-Apr-2009', '06-May-2009', '11-May-2009', '18-May-2009', '15-May-2009', '15-May-2009', '15-May-2009', '15-May-2009', ... '15-May-2009', '15-May-2009', '01-Jun-2009', '01-Jun-2009', '01-Jun-2009', '26-Nov-2009', '08-Dec-2009', '08-Dec-2009'}; % Bad channels {iSubj} = {Run01, Run02, Run03, Run04, Run05, Run06} BadChannels{1} = {'EEG016', 'EEG070', 'EEG050',{'EEG008','EEG050'}, [], []}; BadChannels{2} = {{'EEG027', 'EEG030', 'EEG038'}, 'EEG010', 'EEG010', 'EEG010', 'EEG010', 'EEG010'}; BadChannels{3} = {{'EEG008','EEG017'}, {'EEG008','EEG017'}, {'EEG008','EEG017'}, {'EEG008','EEG017'}, {'EEG008','EEG017','EEG001'}, {'EEG008','EEG017','EEG020'}}; BadChannels{4} = {{'EEG038'}, {'EEG038','EEG001','EEG016'}, {'EEG038','EEG001','EEG016'}, {'EEG038','EEG001'}, {'EEG038','EEG001','EEG016'}, {'EEG038','EEG001','EEG016'}}; BadChannels{5} = {'EEG001', 'EEG001', [], [], [], []}; BadChannels{6} = {'EEG068', [], 'EEG004', [], [], []}; BadChannels{7} = {[], [], {'EEG004','EEG008'}, {'EEG004','EEG008'},{'EEG004','EEG008','EEG043','EEG045','EEG047'}, {'EEG004','EEG008'}}; BadChannels{8} = {[], [], [], [], [], []}; BadChannels{9} = {[], 'EEG004', 'EEG004', [], 'EEG004', 'EEG004'}; BadChannels{10} = {[], [], [], [], [], []}; BadChannels{11} = {{'EEG010','EEG050'}, 'EEG050', 'EEG050', 'EEG050', 'EEG050', 'EEG050'}; BadChannels{12} = {{'EEG024','EEG057'}, {'EEG024','EEG057'}, {'EEG024','EEG057'}, {'EEG024','EEG057','EEG070'}, {'EEG024','EEG057'}, {'EEG024','EEG057','EEG070'}}; BadChannels{13} = {'EEG009', 'EEG009', {'EEG009','EEG057','EEG69'}, 'EEG009', {'EEG009','EEG044'}, {'EEG009','EEG044'}}; BadChannels{14} = {'EEG029', 'EEG029', 'EEG029', {'EEG004','EEG008','EEG016','EEG029'}, {'EEG004','EEG008','EEG016','EEG029'}, {'EEG004','EEG008','EEG016','EEG029'}}; BadChannels{15} = {'EEG038', 'EEG038', 'EEG038', 'EEG038', {'EEG054','EEG038'}, 'EEG038'}; BadChannels{16} = {'EEG008', 'EEG008', 'EEG008', 'EEG008', 'EEG008', 'EEG008'}; % SSP components to remove {iSubj} = {sRun01, sRun02, sRun03, sRun03, sRun04, sRun05, sRun06}, sRun0X={ECG_GRAD,ECG_MAG} SspSelect{1} = {{1,1}, {1,1}, {1,1}, {1,1}, {1,1}, {1,1}}; SspSelect{2} = {{1,1}, {1,1}, {1,1}, {1,1}, {3,1}, {1,1}}; SspSelect{3} = {{[],1}, {1,1}, {1,1}, {1,1}, {1,1}, {1,1}}; SspSelect{4} = {{[],1}, {[],1}, {[],1}, {[],1}, {[],1}, {[],1}}; SspSelect{5} = {{2,1}, {1,1}, {1,1}, {[],1}, {1,1}, {1,1}}; SspSelect{6} = {{2,1}, {2,1}, {1,1}, {2,1}, {1,1}, {2,1}}; SspSelect{7} = {{1,1}, {1,1}, {1,1}, {1,1}, {1,1}, {1,1}}; SspSelect{8} = {{1,1}, {1,1}, {[],1}, {2,1}, {1,1}, {2,1}}; SspSelect{9} = {{1,1}, {1,1}, {[],1}, {[],1}, {1,1}, {1,1}}; SspSelect{10} = {{1,1}, {1,1}, {1,1}, {1,1}, {1,1}, {1,1}}; SspSelect{11} = {{[],1}, {[],1}, {[],1}, {[],1}, {[],[]}, {[],[]}}; SspSelect{12} = {{[1,2],[1,2]}, {1,1}, {1,1}, {1,1}, {1,1}, {1,1}}; SspSelect{13} = {{[],[]}, {[],[]}, {[],[]}, {[],[]}, {[],[]}, {[],[]}}; SspSelect{14} = {{1,1}, {1,1}, {1,1}, {1,1}, {1,1}, {1,1}}; SspSelect{15} = {{1,1}, {1,1}, {1,1}, {1,1}, {1,1}, {1,1}}; SspSelect{16} = {{1,1}, {1,1}, {1,1}, {2,1}, {1,1}, {1,1}}; %% ===== CREATE PROTOCOL ===== % Start brainstorm without the GUI if ~brainstorm('status') brainstorm nogui % Output folder for reports if (nargin < 2) || isempty(reports_dir) || ~isdir(reports_dir) reports_dir = []; % You have to specify the folder in which the tutorial dataset is unzipped if (nargin < 1) || isempty(bids_dir) || ~file_exist(bids_dir) || ~file_exist(bst_fullfile(bids_dir, 'derivatives')) || ~file_exist(bst_fullfile(bids_dir, 'dataset_description.json')) error('The first argument must be the full path to the tutorial folder.'); % The protocol name has to be a valid folder name (no spaces, no weird characters...) ProtocolName = 'TutorialVisual'; % Delete existing protocol gui_brainstorm('DeleteProtocol', ProtocolName); % Create new protocol gui_brainstorm('CreateProtocol', ProtocolName, 0, 0); % Set visualization filters: 40Hz low-pass, no high-pass panel_filter('SetFilters', 1, 40, 0, [], 0, [], 0, 0); % Set colormap: local color scale bst_colormaps('SetMaxMode', 'meg', 'local'); bst_colormaps('SetMaxMode', 'eeg', 'local'); %% ===== PRE-PROCESS AND IMPORT ===== for iSubj = 1:16 % Start a new report (one report per subject) bst_report('Start'); disp(sprintf('\n===== IMPORT: SUBJECT #%d =====\n', iSubj)); % If subject already exists: delete it [sSubject, iSubject] = bst_get('Subject', SubjectNames{iSubj}); if ~isempty(sSubject) db_delete_subjects(iSubject); end % ===== FILES TO IMPORT ===== % Build the path of the files to import AnatDir = fullfile(bids_dir, 'derivatives', 'freesurfer', SubjectNames{iSubj}, 'ses-mri', 'anat'); DataDir = fullfile(bids_dir, 'derivatives', 'meg_derivatives', SubjectNames{iSubj}, 'ses-meg', 'meg'); % Check if the folder contains the required files if ~file_exist(AnatDir) error(['The folder "' AnatDir '" does not exist.']); end if ~file_exist(DataDir) error(['The folder "' DataDir '" does not exist.']); end % ===== ANATOMY ===== % Process: Import anatomy folder bst_process('CallProcess', 'process_import_anatomy', [], [], ... 'subjectname', SubjectNames{iSubj}, ... 'mrifile', {AnatDir, 'FreeSurfer'}, ... 'nvertices', 15000); % ===== PROCESS EACH RUN ===== for iRun = 1:6 % Files to import FifFile = bst_fullfile(DataDir, sprintf('%s_ses-meg_task-facerecognition_run-%02d_proc-sss_meg.fif', SubjectNames{iSubj}, iRun)); % ===== LINK CONTINUOUS FILE ===== % Process: Create link to raw file sFileRaw = bst_process('CallProcess', 'process_import_data_raw', [], [], ... 'subjectname', SubjectNames{iSubj}, ... 'datafile', {FifFile, 'FIF'}, ... 'channelreplace', 1, ... 'channelalign', 0); % Set acquisition date panel_record('SetAcquisitionDate', sFileRaw.iStudy, AcquisitionDates{iSubj}); % ===== PREPARE CHANNEL FILE ===== % Process: Set channels type bst_process('CallProcess', 'process_channel_settype', sFileRaw, [], ... 'sensortypes', 'EEG061, EEG064', ... 'newtype', 'NOSIG'); bst_process('CallProcess', 'process_channel_settype', sFileRaw, [], ... 'sensortypes', 'EEG062', ... 'newtype', 'EOG'); bst_process('CallProcess', 'process_channel_settype', sFileRaw, [], ... 'sensortypes', 'EEG063', ... 'newtype', 'ECG'); % Process: Remove head points sFileRaw = bst_process('CallProcess', 'process_headpoints_remove', sFileRaw, [], ... 'zlimit', 0); % Process: Refine registration sFileRaw = bst_process('CallProcess', 'process_headpoints_refine', sFileRaw, []); % Process: Project electrodes on scalp sFileRaw = bst_process('CallProcess', 'process_channel_project', sFileRaw, []); % Process: Snapshot: Sensors/MRI registration bst_process('CallProcess', 'process_snapshot', sFileRaw, [], ... 'target', 1, ... % Sensors/MRI registration 'modality', 1, ... % MEG (All) 'orient', 1, ... % left 'Comment', sprintf('MEG/MRI Registration: Subject #%d, Run #%d', iSubj, iRun)); bst_process('CallProcess', 'process_snapshot', sFileRaw, [], ... 'target', 1, ... % Sensors/MRI registration 'modality', 4, ... % EEG 'orient', 1, ... % left 'Comment', sprintf('EEG/MRI Registration: Subject #%d, Run #%d', iSubj, iRun)); % ===== IMPORT TRIGGERS ===== % Process: Read from channel bst_process('CallProcess', 'process_evt_read', sFileRaw, [], ... 'stimchan', 'STI101', ... 'trackmode', 2, ... % Bit: detect the changes for each bit independently 'zero', 0); % Process: Group by name bst_process('CallProcess', 'process_evt_groupname', sFileRaw, [], ... 'combine', 'Unfamiliar=3,4', ... 'dt', 0, ... 'delete', 1); % Process: Rename event bst_process('CallProcess', 'process_evt_rename', sFileRaw, [], ... 'src', '3', ... 'dest', 'Famous'); % Process: Rename event bst_process('CallProcess', 'process_evt_rename', sFileRaw, [], ... 'src', '5', ... 'dest', 'Scrambled'); % Process: Add time offset bst_process('CallProcess', 'process_evt_timeoffset', sFileRaw, [], ... 'info', [], ... 'eventname', 'Famous, Unfamiliar, Scrambled', ... 'offset', 0.0345); % Process: Delete events bst_process('CallProcess', 'process_evt_delete', sFileRaw, [], ... 'eventname', '1,2,6,7,8,9,10,11,12,13,14,15,16'); % Process: Detect cHPI activity (Elekta):STI201 bst_process('CallProcess', 'process_evt_detect_chpi', sFileRaw, [], ... 'eventname', 'chpi_bad', ... 'channelname', 'STI201', ... 'method', 'off'); % Mark as bad when the HPI coils are OFF % ===== FREQUENCY FILTERS ===== % Process: Notch filter: 50Hz 100Hz 150Hz 200Hz sFileClean = bst_process('CallProcess', 'process_notch', sFileRaw, [], ... 'freqlist', [50, 100, 150, 200], ... 'sensortypes', 'MEG, EEG', ... 'read_all', 0); % Process: Power spectrum density (Welch) sFilesPsd = bst_process('CallProcess', 'process_psd', [sFileRaw, sFileClean], [], ... 'timewindow', [], ... 'win_length', 4, ... 'win_overlap', 50, ... 'sensortypes', 'MEG, EEG', ... 'edit', struct(... 'Comment', 'Power', ... 'TimeBands', [], ... 'Freqs', [], ... 'ClusterFuncTime', 'none', ... 'Measure', 'power', ... 'Output', 'all', ... 'SaveKernel', 0)); % Process: Snapshot: Frequency spectrum bst_process('CallProcess', 'process_snapshot', sFilesPsd, [], ... 'target', 10, ... % Frequency spectrum 'Comment', sprintf('Power spctrum: Subject #%d, Run #%d', iSubj, iRun)); % ===== BAD CHANNELS ===== if ~isempty(BadChannels{iSubj}{iRun}) % Process: Set bad channels bst_process('CallProcess', 'process_channel_setbad', sFileClean, [], ... 'sensortypes', BadChannels{iSubj}{iRun}); end % ===== EEG REFERENCE ===== % Process: Re-reference EEG bst_process('CallProcess', 'process_eegref', sFileClean, [], ... 'eegref', 'AVERAGE', ... 'sensortypes', 'EEG'); % ===== DETECT ARTIFACTS ====== % Process: Detect heartbeats bst_process('CallProcess', 'process_evt_detect_ecg', sFileClean, [], ... 'channelname', 'EEG063', ... 'timewindow', [], ... 'eventname', 'cardiac'); % Different amplitude thresholds for different subjects if strcmpi(SubjectNames{iSubj}, 'sub-05') thresholdMAX = 50; else thresholdMAX = 100; end % Process: Detect: blink_BAD - Detects all events where the amplitude exceeds 100uV bst_process('CallProcess', 'process_evt_detect_threshold', sFileClean, [], ... 'eventname', 'blink_BAD', ... 'channelname', 'EEG062', ... 'timewindow', [], ... 'thresholdMAX', thresholdMAX, ... 'units', 3, ... % uV (10^-6) 'bandpass', [0.3, 20], ... 'isAbsolute', 1, ... 'isDCremove', 0); % ===== SSP COMPUTATION ===== % Process: SSP ECG: cardiac bst_process('CallProcess', 'process_ssp_ecg', sFileClean, [], ... 'eventname', 'cardiac', ... 'sensortypes', 'MEG GRAD', ... 'usessp', 1, ... 'select', SspSelect{iSubj}{iRun}{1}); bst_process('CallProcess', 'process_ssp_ecg', sFileClean, [], ... 'eventname', 'cardiac', ... 'sensortypes', 'MEG MAG', ... 'usessp', 1, ... 'select', SspSelect{iSubj}{iRun}{2}); % Process: Snapshot: SSP projectors bst_process('CallProcess', 'process_snapshot', sFileClean, [], ... 'target', 2, ... 'Comment', sprintf('Subject #%d, Run #%d', iSubj, iRun)); % SSP projectors % ===== IMPORT BAD EVENTS ===== % Get bad segments: this is typically done manually, not from a script BadSegments = GetBadSegments(iSubj, iRun); % Process: Import from file bst_process('CallProcess', 'process_evt_import', sFileClean, [], ... 'evtfile', {BadSegments, 'ARRAY-TIMES'}, ... 'evtname', 'BAD'); % ===== IMPORT TRIALS ===== % Process: Import MEG/EEG: Events sFilesEpochs = bst_process('CallProcess', 'process_import_data_event', sFileClean, [], ... 'subjectname', SubjectNames{iSubj}, ... 'condition', '', ... 'eventname', 'Famous, Scrambled, Unfamiliar', ... 'timewindow', [], ... 'epochtime', [-0.5, 1.2], ... 'createcond', 0, ... 'ignoreshort', 1, ... 'usectfcomp', 1, ... 'usessp', 1, ... 'freq', [], ... 'baseline', [-0.5, -0.0009]); % ===== AVERAGE: RUN ===== % Process: Average: By trial group (folder average) sFilesAvg = bst_process('CallProcess', 'process_average', sFilesEpochs, [], ... 'avgtype', 5, ... % By trial group (folder average) 'avg_func', 1, ... % Arithmetic average: mean(x) 'weighted', 0, ... 'keepevents', 0); % Process: Snapshot: Recordings time series bst_process('CallProcess', 'process_snapshot', sFilesAvg, [], ... 'target', 5, ... % Recordings time series 'modality', 4, ... % EEG 'time', 0.11, ... 'Comment', sprintf('Subject #%d, Run #%d', iSubj, iRun)); % Process: Snapshot: Recordings topography bst_process('CallProcess', 'process_snapshot', sFilesAvg, [], ... 'target', 6, ... % Recordings topography (one time) 'modality', 4, ... % EEG 'time', 0.11, ... 'Comment', sprintf('Subject #%d, Run #%d', iSubj, iRun)); % ===== COMPUTE NOISECOV: EEG ===== % Process: Compute covariance (noise or data) bst_process('CallProcess', 'process_noisecov', sFilesEpochs, [], ... 'baseline', [-0.5, -0.0009], ... 'sensortypes', 'EEG', ... 'target', 1, ... % Noise covariance (covariance over baseline time window) 'dcoffset', 1, ... % Block by block, to avoid effects of slow shifts in data 'identity', 0, ... 'copycond', 0, ... 'copysubj', 0, ... 'replacefile', 1); % Replace end % Save report ReportFile = bst_report('Save', []); if ~isempty(reports_dir) && ~isempty(ReportFile) bst_report('Export', ReportFile, bst_fullfile(reports_dir, ['report_' ProtocolName '_' SubjectNames{iSubj} '.html'])); end %% ===== EMPTY ROOM RECORDINGS ===== disp(sprintf('\n===== IMPORT: EMPTY-ROOM =====\n')); % Loop on all the noise sessions NoiseFiles = {}; for ses = {'20090409', '20090506', '20090511', '20090515', '20090518', '20090601', '20091126', '20091208'} NoiseFiles{end+1} = fullfile(bids_dir, 'derivatives', 'meg_derivatives', EmptyRoomSubj, ['ses-' ses{1}], 'meg', ['sub-emptyroom_ses-' ses{1} '_task-noise_proc-sss_meg.fif']); % Process: Create link to raw file sFilesNoise = bst_process('CallProcess', 'process_import_data_raw', [], [], ... 'subjectname', EmptyRoomSubj, ... 'datafile', {NoiseFiles, 'FIF'}, ... 'channelreplace', 1, ... 'channelalign', 0); % Process: Notch filter: 50Hz 100Hz 150Hz 200Hz sFileNoiseClean = bst_process('CallProcess', 'process_notch', sFilesNoise, [], ... 'freqlist', [50, 100, 150, 200], ... 'sensortypes', 'MEG, EEG', ... 'read_all', 0); % Process: Compute noise covariance bst_process('CallProcess', 'process_noisecov', sFileNoiseClean, [], ... 'baseline', [], ... 'sensortypes', 'MEG', ... 'target', 1, ... % Noise covariance (covariance over baseline time window) 'dcoffset', 1, ... % Block by block, to avoid effects of slow shifts in data 'identity', 0, ... 'copycond', 1, ... 'copysubj', 1, ... 'copymatch', 1, ... 'replacefile', 2); % Merge %% ===== SOURCE ESTIMATION ===== % Start a new report (one report for the source estimation of all the subjects) bst_report('Start'); % Loop on the subjects: This loop is separated from the previous one, because we should % compute the BEM surfaces after importing all the runs, so that the registration is done % using the high resolution head surface, instead of the smooth scalp BEM layer. for iSubj = 1:length(SubjectNames) disp(sprintf('\n===== SOURCES: SUBJECT #%d =====\n', iSubj)); % ===== BEM SURFACES ===== % Process: Generate BEM surfaces bst_process('CallProcess', 'process_generate_bem', [], [], ... 'subjectname', SubjectNames{iSubj}, ... 'nscalp', 1082, ... 'nouter', 642, ... 'ninner', 642, ... 'thickness', 4, ... 'method', 'brainstorm'); % ===== SELECT ALL AVERAGES ===== % Process: Select data files in: */* sFilesAvg = bst_process('CallProcess', 'process_select_files_data', [], [], ... 'subjectname', SubjectNames{iSubj}); % Process: Select file comments with tag: Avg sFilesAvg = bst_process('CallProcess', 'process_select_tag', sFilesAvg, [], ... 'tag', 'Avg'); % Select only the files with the tag % ===== COMPUTE HEAD MODELS ===== % Process: Compute head model (only for the first run of the subject) bst_process('CallProcess', 'process_headmodel', sFilesAvg(1), [], ... 'sourcespace', 1, ... % Cortex surface 'meg', 3, ... % Overlapping spheres 'eeg', 3, ... % OpenMEEG BEM 'ecog', 1, ... % 'seeg', 1, ... % 'openmeeg', struct(... 'BemSelect', [1, 1, 1], ... 'BemCond', [1, 0.0125, 1], ... 'BemNames', {{'Scalp', 'Skull', 'Brain'}}, ... 'BemFiles', {{}}, ... 'isAdjoint', 0, ... 'isAdaptative', 1, ... 'isSplit', 0, ... 'SplitLength', 4000)); % Get all the runs for this subject (ie the list of the study indices) iStudyOther = setdiff(unique([sFilesAvg.iStudy]), sFilesAvg(1).iStudy); % Copy the forward model file to the other runs sHeadmodel = bst_get('HeadModelForStudy', sFilesAvg(1).iStudy); for iStudy = iStudyOther db_add(iStudy, sHeadmodel.FileName); end % ===== COMPUTE SOURCES: MEG ===== % Process: Compute sources [2018] sAvgSrcMeg = bst_process('CallProcess', 'process_inverse_2018', sFilesAvg, [], ... 'output', 1, ... % Kernel only: shared 'inverse', struct(... 'Comment', 'MN: MEG ALL', ... 'InverseMethod', 'minnorm', ... 'InverseMeasure', 'amplitude', ... 'SourceOrient', {{'fixed'}}, ... 'Loose', 0.2, ... 'UseDepth', 1, ... 'WeightExp', 0.5, ... 'WeightLimit', 10, ... 'NoiseMethod', 'reg', ... 'NoiseReg', 0.1, ... 'SnrMethod', 'fixed', ... 'SnrRms', 1e-06, ... 'SnrFixed', 3, ... 'ComputeKernel', 1, ... 'DataTypes', {{'MEG GRAD', 'MEG MAG'}})); % Process: Snapshot: Sources (one time) - Loop only to get a correct comment for the report for i = 1:length(sAvgSrcMeg) bst_process('CallProcess', 'process_snapshot', sAvgSrcMeg(i), [], ... 'target', 8, ... % Sources (one time) 'orient', 4, ... % bottom 'time', 0.11, ... 'threshold', 20, ... 'Comment', ['MEG sources: ' sFilesAvg(i).FileName]); end % ===== COMPUTE SOURCES: EEG ===== % Process: Compute sources [2018] sAvgSrcEeg = bst_process('CallProcess', 'process_inverse_2018', sFilesAvg, [], ... 'output', 1, ... % Kernel only: shared 'inverse', struct(... 'Comment', 'MN: EEG', ... 'InverseMethod', 'minnorm', ... 'InverseMeasure', 'amplitude', ... 'SourceOrient', {{'fixed'}}, ... 'Loose', 0.2, ... 'UseDepth', 1, ... 'WeightExp', 0.5, ... 'WeightLimit', 10, ... 'NoiseMethod', 'reg', ... 'NoiseReg', 0.1, ... 'SnrMethod', 'fixed', ... 'SnrRms', 1e-06, ... 'SnrFixed', 3, ... 'ComputeKernel', 1, ... 'DataTypes', {{'EEG'}})); % Process: Snapshot: Sources (one time) - Loop only to get a correct comment for the report for i = 1:length(sAvgSrcEeg) bst_process('CallProcess', 'process_snapshot', sAvgSrcEeg(i), [], ... 'target', 8, ... % Sources (one time) 'orient', 4, ... % bottom 'time', 0.11, ... 'threshold', 10, ... 'Comment', ['EEG sources: ' sFilesAvg(i).FileName]); end % Save report ReportFile = bst_report('Save', []); if ~isempty(reports_dir) && ~isempty(ReportFile) bst_report('Export', ReportFile, bst_fullfile(reports_dir, ['report_' ProtocolName '_sources.html'])); %% ===== TIME-FREQUENCY ===== % Start a new report (one report for the time-frequency of all the subjects) bst_report('Start'); % List of conditions to process separately AllConditions = {'Famous', 'Scrambled', 'Unfamiliar'}; % Channels to display in the screen capture, by order of preference (if the first channel is bad, use the following) SelChannel = {'EEG070','EEG060','EEG065','EEG050','EEG003'}; % Compute one separate time-frequency average for each subject/run/condition for iSubj = 1:length(SubjectNames) disp(sprintf('\n===== TIME-FREQUENCY: SUBJECT #%d =====\n', iSubj)); for iRun = 1:6 % Process: Select data files in: Subject/Run sTrialsAll = bst_process('CallProcess', 'process_select_files_data', [], [], ... 'subjectname', SubjectNames{iSubj}, ... 'condition', sprintf('sub-%02d_ses-meg_task-facerecognition_run-%02d_proc-sss_meg_notch', iSubj, iRun)); % Loop on the conditions for iCond = 1:length(AllConditions) % Comment describing this average strComment = [SubjectNames{iSubj}, ' / ', sprintf('run_%02d', iRun), ' / ', AllConditions{iCond}]; disp(['BST> ' strComment]); % Find the first good channel in the display list if isempty(BadChannels{iSubj}{iRun}) iSel = 1; else iSel = find(~ismember(SelChannel,BadChannels{iSubj}{iRun}), 1); end % Process: Select file comments with tag: Avg sTrialsCond = bst_process('CallProcess', 'process_select_tag', sTrialsAll, [], ... 'tag', [AllConditions{iCond}, '_trial'], ... 'search', 1, ... % Search the file names 'select', 1); % Select only the files with the tag % Process: Time-frequency (Morlet wavelets), averaged across trials sTimefreq = bst_process('CallProcess', 'process_timefreq', sTrialsCond, [], ... 'sensortypes', 'MEG MAG, EEG', ... 'edit', struct(... 'Comment', ['Avg: ' AllConditions{iCond} ', Power, 6-60Hz'], ... 'TimeBands', [], ... 'Freqs', [6, 6.8, 7.6, 8.6, 9.7, 11, 12.4, 14, 15.8, 17.9, 20.2, 22.8, 25.7, 29, 32.7, 37, 41.7, 47.1, 53.2, 60], ... 'MorletFc', 1, ... 'MorletFwhmTc', 3, ... 'ClusterFuncTime', 'none', ... 'Measure', 'power', ... 'Output', 'average', ... 'RemoveEvoked', 0, ... 'SaveKernel', 0), ... 'normalize', 'none'); % None: Save non-standardized time-frequency maps % Process: Extract time: [-200ms,900ms] sTimefreq = bst_process('CallProcess', 'process_extract_time', sTimefreq, [], ... 'timewindow', [-0.2, 0.9], ... 'overwrite', 1); % Screen capture of one sensor hFigTf = view_timefreq(sTimefreq.FileName, 'SingleSensor', SelChannel{iSel}); bst_report('Snapshot', hFigTf, strComment, 'Time-frequency', [200, 200, 400, 250]); close(hFigTf); end end % Save report ReportFile = bst_report('Save', []); if ~isempty(reports_dir) && ~isempty(ReportFile) bst_report('Export', ReportFile, bst_fullfile(reports_dir, ['report_' ProtocolName '_timefreq.html'])); %% ===== SUPPORT FUNCTIONS ===== function BadSeg = GetBadSegments(iSubj, iRun) BadSegments{1} = {... [247.867 248.185; 598.999 598.999; 598.999 598.999; 611.999 611.999; 612.999 612.999; 613.999 613.999; 616.999 616.999; 617.999 617.999; 623.999 623.999; 715.209 715.467], ... [84.791 85.166], ... [79.183 80.167], ... [64.309 65.185], ... [90.958 91.167; 178.005 178.355; 293.282 295.919; 312.298 316.479; 353.835 357.716], ... [60.292 66.802; 69.975 71.210; 105.233 107.586; 108.822 109.506; 376.225 376.325]}; BadSegments{2} = {... [223.806 224.199; 279.772 279.895; 453.241 455.108; 692.423 692.593], ... [65.298 66.194; 304.727 306.178; 399.165 400.732], ... [203.141 205.085; 281.579 287.883; 420.395 421.128], ... [387.118 388.229; 440.318 441.900; 554.825 558.744], ... [71.000 80.999; 82.750 87.367; 149.528 149.667; 264.747 267.995; 368.415 371.973; 376.263 378.763; 398.334 401.551; 537.410 541.645], ... [38.000 47.999; 47.825 50.046; 61.298 61.384; 249.653 253.379; 282.917 283.820; 286.135 287.616; 298.167 300.196; 328.254 329.511; 335.957 337.817; 478.277 480.707]}; BadSegments{3} = {... [406.312 407.207; 727.055 728.714], ... [84.894 85.156; 152.028 152.946; 297.835 298.915; 418.272 421.845; 554.084 554.794], ... [73.758 74.159; 378.212 378.536; 406.065 407.099; 470.541 471.698; 488.900 491.168; 529.596 530.453], ... [94.874 95.152; 317.385 321.374; 325.696 327.055; 439.220 439.829; 454.473 455.175; 486.196 486.829; 518.660 522.015; 524.400 525.249; 562.417 570.325], ... [96.208 97.181; 98.942 99.096; 135.005 135.754; 143.990 144.599; 250.139 250.247; 300.459 300.559; 338.265 339.322; 545.913 546.067], ... [91.415 92.156; 284.843 286.525; 297.886 298.404; 317.046 317.163; 332.698 332.791; 358.946 359.402; 428.405 428.775; 478.374 478.690; 549.866 550.128]}; BadSegments{4} = {... [22.967 22.967; 50.036 50.098; 52.058 52.058; 156.653 156.653; 171.565 173.386; 239.544 242.105; 268.162 270.175; 268.992 268.992; 316.032 316.032; 338.283 339.000; 357.959 361.909; 370.871 370.871; 381.579 383.677; 437.731 437.731; 463.482 468.505; 476.135 479.838; 486.652 488.272; 504.860 508.999], ... [309.493 311.707; 342.681 344.525; 354.019 357.321; 390.023 391.225; 393.926 395.855; 404.221 405.069; 432.522 435.932; 459.048 460.715; 471.763 478.529; 549.387 551.999; 591.087 594.143; 608.541 611.079; 624.847 626.615; 649.648 651.570], ... [57.411 58.198; 88.346 88.955; 200.761 202.335; 227.016 227.688; 257.726 258.054; 356.798 359.005; 404.260 411.003], ... [46.000 54.823; 61.000 70.332; 203.005 207.125; 275.875 278.121; 313.500 314.824; 337.973 338.636; 422.505 426.239], ... [58.000 62.479; 78.250 85.166; 89.955 91.360; 116.322 117.888; 130.013 131.987; 149.509 150.489; 174.650 175.823; 182.030 183.334; 196.758 197.384; 204.458 204.697; 205.236 208.663; 311.028 316.383; 320.700 327.181; 332.437 335.354; 344.205 346.133; 374.208 374.865; 385.519 386.214; 441.942 444.241; 453.957 456.997; 486.039 487.004; 501.238 504.185; 512.962 514.675; 553.398 556.215], ... [41.406 45.743; 58.681 59.144; 108.086 108.896; 140.633 143.750; 196.110 199.474; 210.778 210.971; 234.649 235.143; 258.081 259.632; 339.101 340.805; 390.277 390.609; 438.935 442.122; 528.221 534.031]}; BadSegments{5} = {... [265.539 265.778; 266.334 266.495; 268.479 268.965; 367.428 367.636; 439.655 442.779; 453.497 453.853; 504.997 505.329; 519.513 519.683; 595.674 595.982; 602.000 602.463], ... [121.113 121.499; 124.971 126.213; 253.735 254.075; 272.232 272.464; 272.895 273.104; 346.368 346.645; 368.812 369.052; 406.382 406.605; 452.920 453.113; 454.903 455.112; 507.655 507.840; 508.766 509.013; 584.853 585.030; 594.831 595.656; 597.261 602.249], ... [37.251 37.497; 38.825 39.056; 40.615 41.849; 43.624 44.758; 53.333 53.641; 54.698 55.076; 57.668 59.196; 79.129 79.360; 81.475 81.714; 122.658 123.375; 284.787 285.296; 288.754 288.993; 345.790 346.022; 421.212 421.459; 481.428 482.207; 503.408 503.685; 504.272 504.449; 524.451 524.714; 526.913 531.499], ... [87.322 88.178; 91.085 91.325; 95.121 95.491; 114.174 114.397; 129.874 130.113; 151.220 151.544; 281.689 281.959; 532.966 533.345], ... [59.176 60.218; 74.854 75.317; 308.180 309.877; 380.705 381.059], ... [182.382 183.245; 196.220 196.736; 276.018 276.327; 292.490 294.086; 370.755 370.847; 435.644 436.624; 467.535 468.460; 522.838 525.847]}; BadSegments{6} = {... [141.690 142.424; 157.070 157.417; 355.138 356.025; 423.999 423.999; 424.999 424.999; 426.999 426.999; 427.999 427.999; 486.430 488.151; 493.999 493.999; 501.511 501.619; 501.549 501.549; 501.585 501.585; 502.999 502.999; 503.999 503.999; 540.999 540.999; 541.999 541.999; 555.999 555.999; 556.999 556.999; 561.999 561.999; 563.999 563.999; 564.999 564.999; 565.999 565.999; 567.999 567.999], ... [64.898 65.161; 71.700 72.718; 226.185 226.740; 324.124 324.425; 329.062 329.301; 486.143 486.975], ... [62.300 63.148; 266.254 266.639; 409.920 410.221], ... [54.048 55.214; 330.893 331.255], ... [185.616 186.495; 331.411 331.796; 386.843 387.028; 387.999 387.999; 389.999 389.999; 434.575 434.875; 519.802 519.995], ... [44.720 45.167; 211.446 211.964; 368.955 369.172]}; BadSegments{7} = {... [154.966 155.144; 551.639 551.855], ... [88.774 89.167; 107.999 107.999; 109.999 109.999; 110.999 110.999; 112.999 112.999; 113.999 113.999; 114.999 114.999; 119.999 119.999; 121.999 121.999; 124.223 125.465; 137.011 138.871], ... [81.627 82.136; 377.953 381.046], ... [241.136 242.171; 543.849 544.196; 596.639 598.553; 600.227 601.075; 603.999 603.999; 605.999 605.999; 609.999 609.999; 611.305 612.809; 614.999 614.999; 615.803 616.937; 623.694 625.877; 653.999 653.999; 655.055 655.756; 663.999 663.999], ... [68.852 69.481; 74.034 75.200; 78.426 78.600; 104.497 105.963; 253.951 254.034; 256.964 257.038; 257.915 258.048; 323.254 324.156; 365.880 368.131; 369.952 370.060; 371.728 372.999; 430.931 431.965; 535.521 542.999], ... [70.271 71.205; 94.441 96.445; 98.613 99.126; 112.318 112.749; 131.686 132.265; 148.935 150.615; 161.120 161.600; 205.325 208.214; 215.035 215.863; 217.403 218.818; 286.178 287.171; 399.075 404.853]}; BadSegments{8} = {... [238.505 238.546; 256.354 257.224; 316.116 316.167; 341.519 341.558; 356.493 356.566; 380.095 380.170; 391.906 392.048; 448.457 448.562; 469.931 470.028; 530.488 530.575; 555.180 558.136; 562.152 562.245; 588.403 588.502; 625.205 625.662; 638.019 638.438; 649.982 650.008; 650.691 651.357; 651.925 652.061; 665.445 665.472; 695.923 696.015; 706.528 706.720; 729.706 732.534], ... [99.546 106.114; 113.245 114.199; 150.885 154.989; 277.486 278.075; 333.645 335.574; 339.358 340.646; 371.860 375.394; 497.459 499.156], ... [49.008 50.205; 231.446 233.406; 329.590 329.659; 355.101 356.019; 360.733 360.973; 372.955 374.891; 389.283 392.068; 453.610 455.431; 464.632 465.265; 489.209 489.996; 514.777 515.295], ... [178.368 179.232; 293.865 294.521; 418.252 418.314; 450.124 450.209; 480.236 480.445; 492.725 493.975; 495.170 497.624; 500.382 500.459; 504.247 504.402; 628.017 628.079; 628.827 628.905; 630.209 630.332], ... [100.616 101.172; 107.691 108.539; 188.814 188.875; 193.119 193.281; 207.964 208.033; 432.254 432.385; 489.834 489.911; 517.960 518.037; 518.955 519.040; 520.938 521.062; 521.945 522.037; 523.959 524.052; 525.942 526.057; 526.945 527.015; 528.958 529.059; 531.138 531.192; 531.979 532.048; 532.951 533.028; 533.962 534.024], ... [135.997 137.232; 383.565 383.657; 418.763 418.955]}; BadSegments{9} = {... [215.107 216.187; 262.388 262.388; 287.519 287.635; 289.895 290.135; 311.999 311.999; 350.161 351.179; 526.154 527.033; 564.999 564.999; 584.935 585.059; 587.999 587.999; 601.999 601.999; 603.999 603.999; 608.999 608.999; 612.999 612.999], ... [47.667 47.775; 49.172 54.681; 67.195 70.805; 78.988 80.477; 138.701 138.948; 138.727 138.727; 138.728 138.728; 138.728 138.728; 138.734 138.734; 138.734 138.734; 138.881 138.881; 138.881 138.881; 138.907 138.907; 140.993 141.093; 141.037 141.037; 141.045 141.045; 155.795 155.864; 155.822 155.822; 155.849 155.849; 168.999 168.999; 206.999 206.999; 219.999 219.999; 225.999 225.999; 226.999 226.999; 228.999 228.999; 236.999 236.999; 242.463 242.463; 242.463 242.463; 242.487 242.487; 247.999 247.999; 251.999 251.999; 252.483 252.483; 253.315 254.163; 265.999 265.999; 267.999 267.999; 272.358 272.358; 272.410 272.410; 298.999 298.999; 300.999 300.999; 314.037 314.037; 314.047 314.047; 321.813 321.813; 321.813 321.813; 321.833 321.833; 329.117 329.117; 329.117 329.117; 329.156 329.156; 346.999 346.999; 347.999 347.999; 349.320 349.320; 349.329 349.329; 352.528 355.869; 364.040 364.040; 396.278 397.420; 404.865 404.865; 407.905 407.905; 407.905 407.905; 407.954 407.954; 418.454 418.454; 418.454 418.454; 418.486 418.486; 441.999 441.999; 444.999 444.999; 447.999 447.999; 453.550 453.650; 454.931 455.055; 457.999 457.999; 479.964 480.079; 481.999 481.999; 482.949 483.073; 488.948 489.064; 511.999 511.999; 520.999 520.999; 523.999 523.999; 526.954 527.069; 533.999 533.999; 537.999 537.999], ... [82.889 83.198; 206.143 207.424; 403.873 404.096; 406.790 407.485; 413.936 414.075; 415.912 416.112; 536.621 537.532], ... [182.999 182.999; 182.999 182.999; 183.999 183.999; 195.999 195.999; 208.999 208.999; 209.999 209.999; 278.601 278.955; 413.913 414.067; 415.250 417.792; 419.940 420.087; 420.999 420.999; 512.999 512.999; 514.363 516.254; 521.917 522.134; 522.999 522.999; 523.915 524.101; 533.999 533.999; 538.999 538.999; 539.892 540.062; 543.999 543.999; 548.874 549.089; 549.900 550.062; 552.755 554.075; 585.999 585.999; 587.957 588.073; 588.999 588.999; 594.999 594.999; 603.971 604.056; 604.928 605.097; 615.986 618.495; 623.999 623.999], ... [53.215 54.203; 164.227 168.965; 201.433 202.775; 292.973 295.889; 303.961 304.817; 309.354 311.236; 313.123 313.639; 322.547 323.017; 331.141 334.852; 356.637 356.985; 367.855 368.079; 369.995 373.459; 377.849 378.142; 406.072 407.306; 436.164 436.665; 458.033 458.905; 516.889 518.656; 517.812 518.684], ... [113.945 115.225; 198.570 198.863; 264.162 264.795; 383.705 385.641; 396.477 397.064; 399.706 406.457; 452.261 453.179; 486.338 487.102; 498.869 499.579; 507.968 508.925; 546.266 547.285; 558.825 560.128]}; BadSegments{10} = {... [235.104 236.184; 324.272 325.028; 330.799 331.401; 541.062 541.826; 564.747 565.072], ... [100.581 101.229; 285.644 285.644; 285.644 285.644; 297.979 298.033; 298.999 298.999; 300.949 301.026; 301.999 301.999; 303.999 303.999; 304.999 304.999; 306.999 306.999; 307.999 307.999; 310.999 310.999; 311.999 311.999; 313.971 314.025; 314.999 314.999; 316.995 317.035; 317.999 317.999; 319.999 319.999; 320.923 321.046; 326.971 327.048; 327.999 327.999; 329.999 329.999; 330.999 330.999; 332.974 333.028; 333.999 333.999; 335.971 336.025; 336.999 336.999; 338.973 339.035; 339.999 339.999; 341.951 342.044; 343.999 343.999; 344.964 345.033; 346.999 346.999; 347.999 347.999; 452.015 453.411; 458.735 459.776; 467.974 468.089], ... [41.266 41.675; 53.905 55.240; 159.159 159.345; 220.255 220.394], ... [66.751 67.190; 201.674 201.812; 294.119 295.168; 303.188 303.528; 316.992 317.037; 317.999 317.999; 317.999 317.999; 319.999 319.999; 320.980 321.042; 322.999 322.999; 325.999 325.999; 326.955 327.048; 328.999 328.999; 333.999 333.999; 334.999 334.999; 342.999 342.999; 343.999 343.999; 351.915 352.038; 352.999 352.999; 407.979 408.056; 409.999 409.999; 411.999 411.999; 415.405 416.154; 435.999 435.999; 436.962 437.046; 468.885 469.100; 469.999 469.999; 470.999 470.999; 516.210 516.357], ... [105.369 106.172; 141.468 142.178; 199.008 199.818; 201.269 201.716; 352.851 353.083; 449.865 452.041; 459.508 459.802], ... [229.948 230.033; 230.999 230.999; 230.999 230.999; 259.588 259.990; 343.970 345.798; 361.999 361.999; 362.970 363.046; 364.999 364.999; 366.999 366.999; 367.962 368.031; 372.521 374.179; 405.999 405.999; 409.999 409.999; 411.999 411.999; 412.999 412.999; 434.999 434.999; 435.970 436.031; 516.999 516.999; 519.999 519.999]}; BadSegments{11} = {... [179.045 180.225; 323.999 323.999; 323.999 323.999; 324.999 324.999; 327.978 328.025; 328.966 329.028; 330.999 330.999; 365.999 365.999; 367.999 367.999; 370.999 370.999; 371.999 371.999; 373.999 373.999; 375.965 376.042; 377.999 377.999], ... [52.107 53.156; 521.077 521.155], ... [65.331 66.156], ... [81.579 82.143; 108.565 108.565; 108.566 108.566; 112.176 112.176; 122.377 122.377; 122.565 122.565; 213.882 213.882; 215.305 215.305; 224.851 224.851; 224.919 224.919; 255.815 255.815; 257.893 257.893; 359.952 359.952; 361.630 361.754; 370.285 370.285; 376.853 376.853; 511.600 511.600; 513.631 513.631; 513.988 513.988; 518.215 518.215], ... [63.205 64.154; 170.951 171.036; 176.841 176.841; 176.842 176.842; 177.282 177.282; 223.886 223.971; 259.963 259.963; 261.547 261.547; 341.185 341.302; 368.999 368.999; 370.999 370.999; 374.999 374.999; 382.971 383.033; 383.999 383.999; 386.999 386.999; 388.958 389.035; 390.999 390.999; 391.955 392.031; 394.955 395.040; 396.999 396.999; 398.999 398.999; 400.999 400.999; 402.999 402.999; 404.963 405.033; 406.999 406.999; 429.829 429.829; 430.346 430.346; 465.184 465.184; 470.290 470.290], ... [50.195 51.145; 158.850 159.012]}; BadSegments{12} = {... [193.435 194.175; 500.000 501.000; 08.988 509.868; 528.999 528.999; 528.999 528.999; 529.999 529.999; 531.999 531.999; 547.999 547.999], ... [133.484 134.185; 134.911 135.065; 553.999 553.999; 553.999 553.999; 554.999 554.999; 557.999 557.999; 558.999 558.999; 564.999 564.999; 565.977 566.046; 568.999 568.999; 569.951 570.028; 571.999 571.999; 579.959 580.028; 580.977 581.055; 583.971 584.033; 583.999 583.999; 585.999 585.999; 586.999 586.999; 588.980 589.026; 590.999 590.999; 591.958 592.044; 595.999 595.999], ... [46.028 47.216; 129.557 130.236; 200.999 200.999; 200.999 200.999; 201.975 202.075; 203.999 203.999; 204.967 205.053; 213.627 214.515; 218.958 219.044; 222.959 228.252; 309.999 309.999; 311.897 317.537; 311.999 311.999; 351.968 353.234; 399.999 399.999; 446.508 451.454; 487.999 487.999; 512.278 512.926], ... [82.535 84.062; 102.247 102.355; 134.999 134.999; 134.999 134.999; 136.999 136.999; 138.973 139.042; 147.999 147.999; 148.999 148.999; 149.999 149.999; 193.999 193.999; 194.999 194.999; 224.984 226.095; 241.954 242.077; 243.948 244.087; 280.999 280.999; 281.999 281.999; 305.000 305.451; 310.945 311.068; 328.999 328.999; 352.999 352.999; 353.999 353.999; 397.025 397.411; 415.944 418.096; 415.999 415.999; 470.999 470.999; 477.971 478.041; 483.997 484.737; 492.958 493.089; 493.999 493.999; 494.999 494.999; 522.999 522.999; 523.999 523.999; 524.955 525.039], ... [175.183 176.155; 246.112 246.991; 412.005 413.340; 483.915 484.061; 485.959 486.028; 497.360 498.880; 594.457 594.944; 596.641 598.006; 615.277 618.710], ... [66.900 72.232; 75.510 78.688; 543.495 545.999]}; BadSegments{13} = {... [307.246 308.179; 627.881 628.089; 629.941 630.049], ... [171.506 172.301; 172.999 172.999; 430.999 430.999; 432.999 432.999; 434.999 434.999; 448.999 448.999; 479.999 479.999; 489.999 489.999; 490.999 490.999; 491.999 491.999], ... [92.059 93.209], ... [52.791 53.231; 54.999 54.999; 65.985 68.138; 91.240 91.386; 92.137 92.207; 105.346 105.493; 121.120 121.398; 146.546 146.955; 194.025 197.652; 242.985 243.571; 247.101 247.556; 269.889 270.083; 270.946 271.070; 274.408 275.866; 294.565 295.267; 319.370 319.879; 365.999 365.999; 375.913 376.044; 376.869 377.055; 377.999 377.999; 390.130 393.225; 403.965 404.035; 404.953 405.075; 419.265 419.565; 427.015 427.154; 427.879 428.118; 427.999 427.999; 428.913 429.067; 480.945 482.095; 484.285 484.571; 516.929 517.099; 517.963 518.079], ... [115.921 116.060; 117.999 117.999; 120.999 120.999; 126.896 127.058; 130.955 131.039; 131.957 132.043; 132.961 133.015; 134.999 134.999; 135.950 136.043; 139.999 139.999; 143.999 143.999; 144.850 145.066; 145.999 145.999; 146.999 146.999; 160.929 161.045; 161.999 161.999; 189.086 189.310; 193.939 194.063; 195.975 196.045; 199.961 200.045; 201.952 202.059; 202.939 205.084; 210.999 210.999; 211.738 213.629; 217.954 218.061; 218.987 219.049; 219.975 220.028; 258.953 259.037; 259.952 260.045; 260.963 261.032; 261.958 262.043; 262.954 263.054; 262.999 262.999; 288.999 288.999; 295.477 295.655; 298.976 299.054; 299.979 300.018; 300.975 301.005; 336.952 337.044; 337.977 338.032; 338.988 339.027; 338.999 338.999; 339.991 340.045; 340.975 341.029; 341.978 342.016; 343.976 344.054; 361.961 362.045; 365.942 366.050; 370.999 370.999; 384.961 385.045; 409.977 410.047; 415.984 416.030; 426.944 427.059; 430.999 430.999; 436.999 436.999; 448.999 448.999; 449.500 452.131; 481.962 482.055; 482.973 483.027; 484.975 485.060; 503.999 503.999; 504.999 504.999; 507.967 508.028; 508.955 509.032; 510.999 510.999; 512.999 512.999; 518.865 520.292; 522.958 523.043; 523.999 523.999; 524.948 525.034; 525.959 526.044; 526.946 527.055; 527.942 528.027; 528.961 529.053; 529.945 530.022; 535.999 535.999; 536.957 537.058; 538.967 539.036; 539.963 540.040; 541.976 542.045; 543.999 543.999; 551.956 552.034; 552.990 553.028; 553.977 554.024; 555.968 556.022; 556.204 557.454; 557.963 558.032; 559.969 560.023; 563.973 564.035; 563.999 563.999], ... [87.308 87.639; 107.039 108.189; 427.943 428.035; 437.965 438.027; 439.973 440.026; 491.275 492.571]}; BadSegments{14} = {... [365.982 367.194; 368.999 368.999; 368.999 368.999; 369.999 369.999; 371.999 371.999; 373.999 373.999; 375.942 376.050; 376.999 376.999; 378.999 378.999; 380.999 380.999; 382.999 382.999; 383.999 383.999; 386.999 386.999; 387.999 387.999; 418.999 418.999; 444.999 444.999; 690.178 693.218], ... [101.796 102.183; 218.999 218.999; 219.999 219.999; 221.999 221.999; 222.999 222.999; 227.999 227.999; 229.999 229.999; 230.999 230.999; 232.999 232.999; 233.999 233.999; 235.999 235.999; 237.999 237.999; 238.985 239.031; 240.999 240.999; 242.999 242.999; 243.999 243.999; 246.999 246.999; 247.999 247.999; 253.999 253.999; 258.999 258.999; 259.999 259.999; 260.227 261.123; 264.999 264.999; 265.999 265.999; 268.999 268.999; 269.999 269.999; 274.999 274.999; 276.999 276.999; 277.999 277.999; 280.999 280.999; 282.966 283.021; 284.999 284.999; 285.999 285.999; 360.999 360.999; 362.973 363.026; 364.999 364.999; 365.999 365.999; 367.999 367.999; 368.985 369.024; 370.999 370.999; 371.999 371.999; 378.999 378.999; 379.999 379.999; 381.999 381.999; 383.999 383.999; 385.999 385.999; 387.999 387.999; 388.999 388.999; 398.999 398.999; 415.999 415.999; 417.999 417.999; 418.999 418.999; 421.999 421.999; 422.999 422.999], ... [89.285 90.187], ... [85.991 87.179; 88.999 88.999; 89.999 89.999; 92.966 93.027; 93.999 93.999; 107.999 107.999; 110.999 110.999; 111.971 112.025; 118.999 118.999; 121.999 121.999; 122.999 122.999; 166.999 166.999; 168.957 169.035; 173.999 173.999; 174.999 174.999; 175.957 176.035; 198.999 198.999; 199.999 199.999; 202.999 202.999; 203.999 203.999; 205.999 205.999; 207.999 207.999; 208.999 208.999; 210.974 211.044; 211.999 211.999; 212.999 212.999; 232.984 233.023; 234.999 234.999; 235.999 235.999; 236.999 236.999; 239.958 240.044; 240.999 240.999], ... [71.132 72.227], ... [98.134 98.827; 110.497 110.814; 114.000 117.272; 279.999 279.999; 279.999 279.999; 280.999 280.999; 282.999 282.999; 283.999 283.999; 284.999 284.999; 286.999 286.999; 287.999 287.999; 288.999 288.999; 289.999 289.999; 291.966 292.044; 292.999 292.999; 346.999 346.999; 437.608 437.646; 518.988 519.104; 522.969 523.015; 534.999 534.999; 536.967 537.029; 562.725 563.426]}; BadSegments{15} = {... [66.755 67.172; 257.988 258.042; 258.714 259.385; 260.958 261.044; 265.931 266.062; 267.968 268.022; 268.978 269.033; 270.992 271.031; 272.964 273.017; 273.968 274.030; 275.975 276.059; 276.970 277.046; 288.976 289.038; 289.984 290.015; 295.994 296.025; 296.982 297.013; 300.966 301.152; 364.730 364.800], ... [46.531 46.555; 65.156 66.148; 87.535 87.642; 183.896 183.934; 294.342 294.375; 330.004 330.528; 333.785 333.815; 345.177 345.203; 399.544 399.573; 480.964 480.980], ... [53.557 54.175; 148.851 149.136], ... [43.681 44.214; 361.255 361.587; 409.462 411.021], ... [90.868 91.130; 410.935 411.044], ... [64.786 65.141; 132.385 132.786; 177.735 178.252; 278.747 278.902; 313.959 314.028; 314.970 315.031]}; BadSegments{16} = {... [38.958 44.335; 305.280 312.826; 324.778 326.067; 393.183 398.367; 403.410 422.854], ... [49.726 50.251; 58.675 65.465; 263.918 264.088; 321.795 322.195; 522.881 523.081], ... [61.245 62.325; 65.628 65.905; 315.686 317.275; 335.184 336.449; 387.870 388.117; 389.892 390.062], ... [56.020 57.255; 60.711 61.096; 64.353 64.924; 73.202 73.757; 76.134 76.844; 95.625 96.859; 171.436 172.625; 178.359 178.715; 212.828 213.415; 352.425 352.617; 367.755 369.097; 488.400 489.426], ... [71.665 72.513; 76.347 77.181; 127.134 128.862], ... [46.190 47.209; 53.461 55.752; 194.317 194.510; 213.101 213.240; 216.356 216.442; 225.962 226.286; 245.163 245.464; 252.041 253.422; 254.648 254.856; 292.966 294.340; 340.928 341.067; 346.298 346.452]}; BadSeg = BadSegments{iSubj}{iRun}'; id="line-1037">
uster">Running scripts on a cluster 039">
Like mentioned above Brainstorm can be started in different ways. To use Brainstorm on a distant server the starting command "brainstorm server" needs to be used.
Before using Brainstorm on a distant server a few adjustments need to be done.
At first Matlab (including the Signal Processing Toolbox --- depending on the used functions) needs to be installed on the server and a Brainstorm version needs to be located on the server. For the Brainstorm database, the folder "brainstorm_db" needs to be created. Regarding the file structure on the server, the path for the brainstorm folders could look like this:
/home/user/brainstorm3
/home/user/brainstorm_db/anat
/home/user/brainstorm_db/data
In the "brainstorm_db" folder all the files you want to process need to be included. To not miss any files, the easiest solution would be to upload the whole "brainstorm_db" folder from your computer to the server. On the local computer Brainstorm might create missing files, e.g. "protocol.m", on its own. On the server it might not be able to do so and will crash.
To run a script using Brainstorm on a distant server also the script needs to be prepared. The following lines should be included:
% Set up the Brainstorm files -43">pathStr = '/home/user/brainstorm3/'; -38">addpath(genpath(pathStr)); -35">BrainstormDbDir = '/home/user/brainstorm_db'; Start Brainstorm -29">if ~brainstorm('status') brainstorm server -24">end -19">bst_set('BrainstormDbDir',BrainstormDbDir) 0-16">% Select the correct protocol 1-15">ProtocolName = 'Study'; % Enter the name of your protocol 2-15">sProtocol.Comment = ProtocolName; 3-14">sProtocol.SUBJECTS = [home 'anat']; 4-12">sProtocol.STUDIES = [home 'data']; 5-11">db_edit_protocol('load',sProtocol); 6-10">% Get the protocol index 7-10">iProtocol = bst_get('Protocol', ProtocolName); 8-8">if isempty(iProtocol) error(['Unknown protocol: ' ProtocolName]); 0-6">end Select the current procotol 2-6">gui_brainstorm('SetCurrentProtocol', iProtocol);
Afterwards, you might add your analysis script. For example, you may create a script using the Brainstorm pipeline and add these lines to the top of your script and run it on the server.
To run a script using Brainstorm on a server you should check that there is a free matlab license on the server and RAM/Quota is big enough for the data you will create while processing. Also the Matlab version might differ from the version installed on your local computer. The lines above were tested using Matlab 2015b on a server.
A Brainstorm script can be executed either directly (it needs to start Brainstorm itself), or started using the syntax brainstorm <script.m> <parameters> (starts Brainstorm in server mode, executes the script and quit Brainstorm).
Brainstorm scripts can also be executed from the compiled version of Brainstorm, therefore not requiring a Matlab license, only the installation of the free MCR library (see the Installation page). Add the full path to the script to execute and the script parameters to the start script:
<script.m> or brainstorm3.command <script.m>.
ack_functions">Finding interface callback functions 088">
If you are looking for the function called by a menu or a button in the interface:
In Matlab, go to the "brainstorm3" folder
Click on the button "Find file" in the ribbon "Editor" of Matlab interface (Ctrl+Shift+F)
Select the option "Include subfolders"
Search for the text of the menu or button you are looking for (eg. 'Set as default'); you can do a case-sensitive or a case-insensitive search (option "Match case")
It gives you the list of all the places where this text appears in the Brainstorm code. In the previous example, in tree_callbacks.m, you’d find a call to function SetDefaultSurf.
Double-click on the corresponding line to jump to the code
Right-click on "SetDefaultSurf" > Open "SetDefaultSurf"
The editor should jump to the code of function SetDefaultSurf(), and there you’d find your call to "db_surface_default"
Right-click on it > Open "db_surface_default" to open the function and read the header that should explain its usage (this example is not very detailed, sorry)
Sometimes it helps to look at other examples of calls to this function: Use the window "Find files" again to search for text "db_surface_default"
id="line-1100">
documentation 102">
Tutorial: How to write your own process
Tutorial: Java in Brainstorm

id="line-1106">
ms["form"]["comments"].value; orm"]["xYz"].value; || comments=="" || comments.length==1)) { dexOf("."); dotpos=xYz.length){ a valid e-mail address"); = '#'; ps://neuroimage.usc.edu/bst/send_feedback.php" name="form" onSubmit="return validateForm(this);"> Comments, bug reports, suggestions, questions rows="2" cols="85" name="comments"> for completing this tutorial, in minutes: gn:middle;">Email address (if you expect an answer): name="email"> type="submit" value="Send" style="width:140px"> value='Tutorials/Scripting'> id="line-1108">
#pagebox --> class="info" lang="en" dir="ltr">Tutorials/Scripting (last edited 2024-11-28 12:34:50 by RaymundoCassani)

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