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| = Tutorial 20: Advanced scripting = | = Tutorial 28: Scripting = '''[TUTORIAL UNDER DEVELOPMENT: NOT READY FOR PUBLIC USE] ''' |
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| 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. |
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 process all of them manually. Some parts of the analysis pipeline can be processed in batches with no direct supervisions, others require more attention. This tutorial introduces tools and tricks that will help you assemble an efficient analysis pipeline. |
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| == What can be automated == The list below contains all the steps of analysis that were detailed in the introduction tutorials, organized in a way that matches the actual work of the person in charge of the analyses. [Using the individual anatomy of the subjects] * Script 1: Run FreeSurfer or BrainSuite on the MRI for all the subjects. * Manual: Set the anatomical fiducials in the MRI for each subject. * Option 1: Create and import the subjects one by one. Set the fiducials at the import time. * Option 2: If you have [Using [[Tutorials/TutWarping|warped templates]]] [General pipeline] == Script generation == http://neuroimage.usc.edu/brainstorm/Tutorials/PipelineEditor == Script edition == - Add loops, load files, ... Loops: http://neuroimage.usc.edu/forums/showthread.php?2429-Problem-using-tags == File manipulation == * Modify a structure manually: Export to Matlab/Import from Matlab * File manipulation: file_short, file_fullpath, in_bst_*... * Documentation of all file structures: point at the appropriate tutorials * Select files from the database (with bst_get and processes) |
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| == 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"}} |
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| {{{ % Script generated by Brainstorm v3.2 (22-Jul-2014) % Input files sFiles = []; SubjectNames = {... 'Subject01'}; RawFiles = {... 'C:\Work\RawData\Tutorials\sample_raw\Anatomy', ... 'C:\Work\RawData\Tutorials\sample_raw\Data\subj001_somatosensory_20111109_01_AUX-f.ds'}; % Start a new report bst_report('Start', sFiles); % 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], ... 'contact_nimage', 12, ... '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 % Save and display report ReportFile = bst_report('Save', sFiles); bst_report('Open', ReportFile); }}} |
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Tutorial 28: Scripting
[TUTORIAL UNDER DEVELOPMENT: NOT READY FOR PUBLIC USE]
Authors: Francois Tadel, Elizabeth Bock, 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 process all of them manually. Some parts of the analysis pipeline can be processed in batches with no direct supervisions, others require more attention. This tutorial introduces tools and tricks that will help you assemble an efficient analysis pipeline.
What can be automated
The list below contains all the steps of analysis that were detailed in the introduction tutorials, organized in a way that matches the actual work of the person in charge of the analyses.
[Using the individual anatomy of the subjects]
Script 1: Run FreeSurfer or BrainSuite on the MRI for all the subjects.
- Manual: Set the anatomical fiducials in the MRI for each subject.
- Option 1: Create and import the subjects one by one. Set the fiducials at the import time.
- Option 2: If you have
[Using warped templates]
[General pipeline]
Script generation
http://neuroimage.usc.edu/brainstorm/Tutorials/PipelineEditor
Script edition
- Add loops, load files, ...
Loops: http://neuroimage.usc.edu/forums/showthread.php?2429-Problem-using-tags
File manipulation
- Modify a structure manually: Export to Matlab/Import from Matlab
- File manipulation: file_short, file_fullpath, in_bst_*...
- Documentation of all file structures: point at the appropriate tutorials
- Select files from the database (with bst_get and processes)
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
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.