Differences between revisions 108 and 579 (spanning 471 versions)

What's next

A roadmap to the future developments of Brainstorm.

Contents

Recordings
ECOG/SEEG
Pre-processing
Reproducibility toolbox
Interface
Database
Connectivity
Processes
Anatomy
Forward modeling
Source modeling
Statistics
Input / output
Distribution
Documentation
Current bugs
Distributed computing
Geeky programming details

Recordings

Review signals in time-frequency space
Events processes: Select events names from a list instead of having to type them
Display CTF coils: Show discs instead of squares
Sleep scoring wish list (Emily C):
- Configurable horizontal lines (for helping detecting visually some thresholds)
- Mouse ruler: Measure amplitude by dragging the mouse.
- Automatic spindle detector
- https://neuroimage.usc.edu/forums/t/page-overlap-while-reviewing-raw-file-a-way-to-set-to-0/11229/13
RAW file viewer speed (Low priority) :
- Consider to change to a format that is faster to read
- Add parameter to make the visual downsampling more or less aggressive
- Keep the filter specifications in memory instead of recomputing for every page
  (Nice to have)
BioSemi: Add menu "Convert naming system" to rename channels into 10-10 (A1=>FPz)
Simulations: https://github.com/lrkrol/SEREEGA(Low priority)

ECOG/SEEG

https://www.sciencedirect.com/science/article/pii/S1053811922005559
Display (high-priority)(Part SEEG grant):
- Group display: Overlay multiple channel files in the same figure, coloring contacts by subject/ROI/Cluster/Electrode name
  - https://neuroimage.usc.edu/forums/t/37617
  - iEEG tab must be read-only when multiple files (hide configuration controls)
- Bad channels: Contacts greyed out instead of ignored (Marcel H, Germany)
  (To diff between band and not-recorded) > Rendering of SEEG electrodes: Full surface modelling with surface mesh (see Lead-DBS models + code that generates them?)
- Display time in H:M:S instead of S > If there is t0 in H:M:S instead of S > As an option in Display configuration button>x-axis
- view_leadfield_sensitivity: Add closing surfaces at cortex limits
Create clusters from anatomical labels (Anne So) :
- Identify contacts in a given anatomical region (volume scout, surface mesh, or label in a volume atlas) / allow extracting the signals from all the contacts in an ROI> As a process to select recordings, then Scouts from Volumen Atlas, Create cluster in channel file, then Extract time series.
- Group analysis: extract clusters across subjects, display or average signals (see MIA) (Anne So)
Spike detection (Need to check for current toolboxes from scratch)(contact Nicolas R)(Mosher J)(iEEG BIDS):
- https://iopscience.iop.org/article/10.1088/1741-2552/ac9259/pdf
Automatic segmentation of CT:
- LeGUI: https://github.com/Rolston-Lab/LeGUI/tree/main/LeGUI<<BR>>https://neuroimage.usc.edu/forums/t/automatic-localization-of-seeg-electrodes/36302/7
- GARDEL: http://meg.univ-amu.fr/wiki/GARDEL:presentation
- SEEG DEETO Arnulfo 2015: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-015-0511-6
  - Used routinely at Niguarda Hospital + other hospitals worldwide, reliable tool.
  - To be used with SEEG-assistant/3DSlicer: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-017-1545-8
- ECOG Centracchio 2021: https://link.springer.com/content/pdf/10.1007/s11548-021-02325-0.pdf
  - Classifier on thresholded CT: https://github.com/Jcentracchio/Automated-localization-of-ECoG-electrodes-in-CT-volumes
- SEEG Granados 2018 (no code shared): https://link.springer.com/content/pdf/10.1007/s11548-018-1740-8.pdf
ECOG:
- Project and display contacts on cortex surface should consider the rigidity of the grids: Contacts cannot rotate, and distance between contacts should remain constant across runs
- Method for contacts projection: https://pdfs.semanticscholar.org/f10d/6b899d851f3c4b115404298d7b997cf1d5ab.pdf
- ECOG: Brain shift: When creating contact positions on a post-implantation image, the brain shift should be taken into account for creating images of the ECOG contacts on the pre-op brain => iELVis (http://ielvis.pbworks.com/w/page/116347253/FrontPage)
  Normalization MNI? solutions with FieldTrip?
Display CT images: Better brightness/contrast adjustment: https://neuroimage.usc.edu/forums/t/automatic-localization-of-seeg-electrodes/36302/8 Range of values is way diff than ones from MRI. Current color maps are not suitable for CT, need to be improved.Together with processing of CT to get electrode positions.
Detection CCEP stim artifacts: Use ImaGIN code ImaGIN_StimDetect https://f-tract.eu/software/imagin/

Pre-processing

process_detectbad:
- Allow on raw files (for bad channels only)
- Add detection on derivative of the signal (see EEGLAB)
- Document in tutorial Bad channels
- PREP pipeline / EEGLAB (Bigdely-Shamlo 2015)
Improve bad channel/trial detection:
- ft_artifact_threshold and ft_rejectartifact
- MNE-Python
- EEGLAB
Integrate with EYE-EEG (Olaf Dimigen)
- Reproduce tutorial: https://www.eyetracking-eeg.org/tutorial.html
- Create EYE-EEG plugin + processes (Raphael Lambert)
- Process: Detect sacades (extended events) + fixations
- Improved ICA
- Eye-movement related potentials
Add note when rejecting trials: https://neuroimage.usc.edu/forums/t/33686
ICA:
- Automatic classification: ICLabel: https://neuroimage.usc.edu/forums/t/automatic-eeg-ic-ica-classification-for-brainstorm/33785
- Exploration: Add window with spectral decomposition (useful for muscle artifacts)
- Export IC time series (and then compute their spectrum): solves the problem above
- Import ICA matrices available in EEGLAB .set files
- ICA+machine learning: https://www.ncbi.nlm.nih.gov/pubmed/28497769
- Automated artifact rejection: https://arxiv.org/abs/1612.08194
- Use EYE-EEG: EEGLAB toolbox for eye-tracker guided ICA (Olaf Dimigen): http://www2.hu-berlin.de/eyetracking-eeg/
SSP:
- Display warning if changing the ChannelFlag while there is a Projector applied
File format:
- Add support to read GDF file format

https://github.com/donnchadh/biosig/blob/master/biosig/t200_FileAccess/sload.m

Reproducibility toolbox

Generate fully reproducible scripts, including all the interactive/graphical parts
Record all GUI actions as script calls
Import window: Add button to create the corresponding processing pipeline (to generate script or to edit additional options)
Adding the list of plugins to the reports (optionnal or foldable)
Better provenance: History fields, uniform file names...
Improving the pipeline editor to handle loops over data files or subjects

Interface

Add a warning when computing a forward model with > 100000 sources (check selection)
Colormaps: Global colormap max: Should get the maximum across all the open files
Snapshot:
- Save as image / all figures (similar to Movie/all figure)
- Copy figures to clipboard (with the screencapture function)
Contact sheets & movies: use average of time windows instead of single instants, for each picture.
Contact sheets: Allow explicit list of times in input (+ display as in MNE-Python with TS)

Database

Save iHeadModel somewhere in the datbase structure
Generalize the use of the units (field .DisplayUnits): Save in source files

Connectivity

Thresholding and stat tests for connectivity matrices:
- Panel Display: Show only the top N% measures
- Misic: https://www.nature.com/articles/s41583-022-00601-9
Connect NxN display:
- Graph on sensors: does not place the sensors correctly in space
- Display as image: Add legend of the elements along X and Y axis
- Display as time series: Display warning before trying to open too many signals
- Optimize display: use surface() instead of line() for links? (as in figure_3d/PlotFibers)
Time-resolved correlation/coherence: Display as time bands

Processes

Add MNE-Python functions:
- scikit-learn classifiers
- BEM single layer (John wants to test it)
- ICA: https://neuroimage.usc.edu/forums/t/ica-on-very-long-eeg/23556/4
- https://neuroimage.usc.edu/forums/t/best-way-to-export-to-mne-python/12704/3
- Reproduce other tutorials / examples
- Point-spread functions (PSFs) and cross-talk functions: https://mne.tools/stable/auto_examples/inverse/plot_psf_ctf_vertices.html#sphx-glr-auto-examples-inverse-plot-psf-ctf-vertices-py
- Spatial resolution metrics in source space:
  https://mne.tools/stable/auto_examples/inverse/plot_resolution_metrics.html#sphx-glr-auto-examples-inverse-plot-resolution-metrics-py
- Change the graphic renderer from Matlab
Chronux toolbox : http://chronux.org/
Add FieldTrip functions:
- ft_sourceanalysis:
  - Check noise covariance
  - Check all the options of all the methods
  - Single trial reconstructions + noise covariance?
  - Filters?? http://www.fieldtriptoolbox.org/example/common_filters_in_beamforming
  - Beamformers: Save ftSource.avg.mom
    http://www.fieldtriptoolbox.org/workshop/meg-uk-2015/fieldtrip-beamformer-demo
  - http://www.natmeg.se/ft_beamformer/beamformer.html
  - http://www.fieldtriptoolbox.org/tutorial/beamformingextended
  - Baseline? Two inputs?
- ft_prepare_heamodel: Add support from BEM surfaces from the Brainstorm database
- Freqanalysis: ITC
- ft_volumereslice: http://www.fieldtriptoolbox.org/faq/how_change_mri_orientation_size_fov
- ft_freqanalysis
- ft_combineplanar
Optimization:
- Test speed for writing files:
  https://undocumentedmatlab.com/articles/improving-fwrite-performance
- Use CUDA for speeding up some operations (filtering, wavelets, etc)
- Use Matlab Coder to optimize: Wavelets, bandpass filter, sinusoid removal
Pipeline editor:
- Bug: After "convert to continuous", the time of the following processes should change
- Add loops over subjects/conditions/trial groups
- Events: Allow selection from a drop-down list (similar to option "channelname" in panel_process_selection)
ITC: Inter-trial coherence (see MNE reports for group tutorial)
http://www.sciencedirect.com/science/article/pii/S1053811916304232
Remove line noise: http://www.nitrc.org/projects/cleanline
Time-frequency:
- Optimization: bst_timefreq (around l.136), remove evoked in source space: Average should be computed in sensor space instead of source space (requested by Dimitrios)
- Short-time Fourier transform: http://www.mikexcohen.com/lectures.html
- Hilbert with time bands very slow on very long files (eg. 3600s at 1000Hz) because the time vector is still full (10^7 values): save compressed time vector instead.
- When normalizing with baseline: Propagate with the edge effects marked in TFmask
- Allow running TF on montages
- Review continuous files in time-frequency space (for epilepsy)
- Bug when computing TF on constrained and unconstrained scouts at the same time (in mixed head models for instance): uses only the constrained information and doesn't sum the 3 orientations for the unconstrained regions.

Anatomy

Import SimNIBS4: Use final_tissues_LUT.txt instead of fixed list of tissues: https://neuroimage.usc.edu/forums/t/removing-a-lesioned-area/38414/20
Simple-brain-plot: https://github.com/dutchconnectomelab/Simple-Brain-Plot
MNI normalization: More options:
- DARTEL / SHOOT
- BrainSuite (wait for Anand)
- Import from SimNIBS (Conform2MNI_nonl.nii.gz, MNI2Conform_nonl.nii.gz)
MRI Viewer:
- Adjust CT contrast better: https://neuroimage.usc.edu/forums/t/automatic-localization-of-seeg-electrodes/36302/10
- Pan in zoomed view (shift + click + move?)
- Zoom in/out with mouse (shift + scroll?)
- Ruler tool to measure distances
- Display scouts as additional volumes
- Render surface envelope in the MRI as a thin line instead of the full interpolation matrix
  Or use inpolyhedron to get a surface mask and then erode it to get the volume envelope
- Surface>Volume interpolation: Use spm_mesh_to_grid instead of tess_tri_interp
Defacing:
- https://afni.nimh.nih.gov/pub/dist/doc/htmldoc/tutorials/refacer/refacer_run.html
- Removing MNI face mask using MNI coordinates
Atlas switch in 3D MRI figures
Bug import anatomy: Requested nVert > high-resolution cortex surface: Creates an empty cortex_0V
BrainSuite:
- Use same colors for left and right for anatomical atlases
- Use for volume coregistration (rigid / non-rigid)
- USCBrain: Add default electrodes positions
- Remove BrainSuite1 when not needed anymore
Brain2mesh: Add import of 10-10 positions
Templates for different ages:
Scouts:
- Display edges in the middle of the faces instead of the vertices
Parcellating volume grids: scikit-learn.cluster.Ward
Geodesic distance calculations:
https://www.mathworks.com/matlabcentral/fileexchange/6110-toolbox-fast-marching
Improving the registration between EEG and anatomy templates:
- Warping: Improve the basic alignment of the digitized electrodes on the templat, possibly with Cz and other anatomical landmarks
- EEG template positions: rework using a standardized Cz position (+ other landmarks)

Forward modeling

DUNEuro/FEM:
- Add lesion mask to SimNIBS: https://simnibs.github.io/simnibs/build/html/documentation/command_line/add_tissues_to_upsampled.html#add-tissues-to-upsampled-doc
- GeomtryAdapted: Buggy?
- Display differences between leadfields: amplitude of difference (right-click > Compare)
- Display sensitivity on FEM surface
OpenMEEG: Detect bad results + exclude from leadfield
BEM single sphere: Get implementation from MNE
Add eyes models to attract eye activity

Source modeling

Reproduce results in "Simultaneous human intracerebral stimulation and HD-EEG, ground-truth for source localization methods": https://www.nature.com/articles/s41597-020-0467-x
eLORETA instead of sLORETA?
- https://neuroimage.usc.edu/forums/t/compute-eeg-sources-with-sloreta/13425/6
- https://neuroimage.usc.edu/forums/t/loreta-and-source-localization/30525
- "eLORETA algorithm is available in the MEG/EEG Toolbox of Hamburg (METH)": https://www.biorxiv.org/content/biorxiv/early/2019/10/17/809285.full.pdf
- https://github.com/brainstorm-tools/brainstorm3/issues/114
Point-spread and cross-talk functions (code in MNE-Python):
- https://www.biorxiv.org/content/biorxiv/early/2019/06/18/672956.full.pdf
- https://github.com/olafhauk/EEGMEGResolutionAtlas
Dipoles:
- Display dipoles in MRI viewer
- panel_dipoles: Doesn't work with multiple figures
Project sources: Very poor algorithm to project sub-cortical regions and cerebellum
Maximum:
- Menu Sources > Maximum value: Doesn't work with volume or mixed head models
- Panel Get coordinates: Add button "find maximum"
- Sources on surface: Display peak regions over time (time = color) => A.Gramfort
Volume grid:
- Optimize: 3D display (better than 9x9 cubes)
- Optimize: vol_dilate (with 26 neighbors)

Statistics

Stat on unconstrained sources?
Stat/time series: Hide lines going down to zero (Dimitrios: https://neuroimage.usc.edu/forums/t/common-source-activation-across-subjects-and-conditions/1152/21)
Cluster stat: Add frequency selection option
ANOVA:
- Write panel similar to Process1 and Process2
- Output = 1 file per effect, all grouped in a node "ANOVA"
- Display several ANOVA maps (from several files) on one single figure, using a "graphic accumulator", towards which one can send any type of graphic object
Multivariate stim-response analysis: https://github.com/mickcrosse/mTRF-Toolbox

Input / output

BIDS import:
- Add option to process to specify the protocol name
- Full support for iEEG and EEG
- Disable logging of sub-processes (reloading the previous report should only show process_import_bids)
- Read real fiducials (OMEGA) / transformation matrices:
- Use BIDS-Matlab?
Test datasets:
- See list of test datasets in process_import_bids.m
- ds004085 / ds004473: Check response epoch + BUG with coordinate interpretation
BIDS export:
- EEG, iEEG: Add events.tsv, channel.tsv, electrodes.tsv
- Anatomy: Add t1w.json (including fiducials)
- Use BIDS-Matlab?
EDF+ reader: Add resampling of channels with different sampling rates
Support for OpenJData / JNIfTI: https://github.com/brainstorm-tools/brainstorm3/issues/284
DICOM converter:
- Add dcm2nii (MRICron)
- Add MRIConvert
SPM .mat/.dat: Fix the import of the EEG/SEEG coordinates
EEG File formats:
- XLTEK: https://github.com/danielmhanover/OpenXLT
- Persyst .lay: https://github.com/ieeg-portal/Persyst-Reader
- Nervus .eeg: https://github.com/ieeg-portal/Nervus-Reader
- Biopac .acq: https://github.com/ieeg-portal/Biopac-Reader
- BCI2000 Input (via EEGLAB plugin)
4D file format:
- Use reader from MNE-Python: mne.io.read_raw_kit (skip Yokogawa slow library)
- Reference gradiometers: Keep the orientation of the first or second coil?
- Reference gradiometers: Add the sensor definition from coil_def.dat
- Validate with phantom recordings that noise compensation is properly taken into account
- The noise compensation is considered to be always applied on the recordings, not sure this assumption is always correct
- 4D phantom tutorial (JM Badier?)
BST-BIN: Add compression to .bst
MINC MRI: Add support for "voxel to world" transformation (vox2ras) similarly to .nii

Distribution

Java-free Matlab: All references of functions below must be removed
- JavaFrame: screencapture.m (used for screen captures of videos)
- Actxcontrol: Used for video-EEG
  - uihtml + JavaScript callbacks?
  - ActiveX in .NET app?
  - Pure Java framce + VLC java plugin?
  - Other video player?
- Javacomponent:
  - mri_editMask
  - figure_mri
  - process_bandpass
- List .jar files used from Matlab distribution (e.g. dom) => Check all the import calls
Cleanup GitHub repository:
- https://github.com/brainstorm-tools/brainstorm3/issues/473
- Remove ICBM152 default anatomy from repo
- Move external I/O libraries as plugins:
  - mne-matlab
  - CEDS64ML
  - edfimport
  - eeprobe
  - son
  - ricoh
  - yokogawa
  - easyh5

Documentation

All tutorial datasets in BIDS (including introduction tutorials)
Deface the MRIs of all the tutorials
Count GitHub clones in the the download stats
MNE-Python 1.0: Test and update install documentation
Tutorial OMEGA/BIDS:
- Update the organization of derivatives folder (full FS folders)
- Download example datasets directly from the OMEGA repository
New tutorials:
- Other public datasets: https://github.com/INCF/BIDS-examples/tree/bep008_meg/
- EEG/research
- FieldTrip ECOG tutorial: http://www.fieldtriptoolbox.org/tutorial/human_ecog
- Reproduce tutorials from MNE-Python: https://martinos.org/mne/stable/tutorials.html
- Cam-CAN database: https://camcan-archive.mrc-cbu.cam.ac.uk/dataaccess/<<BR>>(download new datasets, including maxfiltered files and manual fiducial placements)
- MEG steady-state / high-gamma visual / frequency tagging
- Reproduce results from "Simultaneous human intracerebral stimulation and HD-EEG, ground-truth for source localization methods": https://www.nature.com/articles/s41597-020-0467-x
- Stand-alone ICA tutorial

Current bugs

Image viewer:
- Difficult to get to 100%
- Buggy on some systems
2DLayout:
- (TF) Units are weird with % values
- (TF) Difficult to navigate in frequencies: Scaling+changing frequency resets the scaling
Progress bar:
- Doesn't close properly on some Linux systems
- Focus requests change workspace when processing constantly (Linux systems)

Distributed computing

Options from FieldTrip:
- Loose collection of computers: https://github.com/fieldtrip/fieldtrip/tree/master/peer
- Single multicore machine: https://github.com/fieldtrip/fieldtrip/tree/master/engine
- Batch system: https://github.com/fieldtrip/fieldtrip/tree/master/qsub
- Documentation: https://www.fieldtriptoolbox.org/faq/what_are_the_different_approaches_i_can_take_for_distributed_computing/
PSOM: http://psom.simexp-lab.org/
Google: https://www.youtube.com/watch?v=LLMXV3o2FT0
- https://edu.google.com/why-google/case-studies/unc-chapel-hill-gcp/

Geeky programming details

Replace all calls to inpolyhd.m with inpolyhedron.m (10x faster)
Interface scaling: Rewrite class IconLoader to scale only once the icons at startup instead of at each request of an icon (might improve the speed of the rendering of the tree)
Processes with "radio" and "radio_line" options: Replace with "radio_label" and "radio_linelabel"
Interpolations: Use scatteredInterpolant, griddedInterpolant, triangulation.nearestNeighbor (2014b)

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-== Current topics ==
==== Functionnal connectivity ====
 * Integration of different metrics to study the brain connectivity: <<BR>>Correlation, coherence, Granger causality, phase locking value
 * Development of new ways to represent the connectivity between sensors or brain regions

==== EEG / epilepsy / intra-cranial recordings ====
 * Editing the position of intracranial electrodes in the MRI viewer

==== Source modeling ====
 * Computation of equivalent current dipoles
 * Beamformers

==== Large scale analysis ====
 * Parallel processing: Reduce the computation times using the parallel processing toolbox
 * Distributed processing: Integrate tools for sending Brainstorm processes on computation clusters

<<BR>><<BR>><<BR>>
+<<TableOfContents(2,2)>>
-Line 23:
+Line 7:
- * RAW file viewer:
  * Pre-load next page of recordings
  * Documentation: Add definition of bad segments
  * 2DLayout: Doesn't work when changing page => need refresh of !GlobalData.Preferences.!TopoLayoutOptions.!TimeWindow
 * EEG reference/storage:
  * Intracranial electrodes: Define in the MRI viewer
  * Bad channels that can be specified at the program level (for sites that have permanently bad channels) => AS Dubarry
 * RAW processing:
  * Make it work for all the file formats (at least bandpass filter + sin removal)
  * Events: advanced process for recombining. Example:  http://www.erpinfo.org/erplab/erplab-documentation/manual/Binlister.html
 * Colormaps:
  * Create a colormap similar to MNE, where extrema are bright
 * Import data:
  * Save properties "baseline" and "resample" at the level of the protocol (to re-use for all the files)
 * NIRS:
  * Add new data type
  * Display of sensors by pairs oxy/deoxy (red/blue), overlaid
 * Images of amplitude: [sensor x time], [trial x time], scout: [trial x time]
  * Can be done with Matrix > View as image: extract cluster, concatenate for all trials
 * 2D Layout for multiple conditions
 * Filtering: Use short FIR filters instead of IIR for bandpass, to limit the ringing<<BR>>Or allow the users to edit the LowStop parameter in bst_bandpass.

== Display ==
 * Nicer 2D topographies, standardized
 * Copy figures to clipboard (with the screencapture function)
+ * Review signals in time-frequency space
 * Events processes: Select events names from a list instead of having to type them
 * Display CTF coils: Show discs instead of squares
 * Sleep scoring wish list (Emily C):
  * Configurable horizontal lines (for helping detecting visually some thresholds)
  * Mouse ruler: Measure amplitude by dragging the mouse.
  * Automatic spindle detector
  *
  https://neuroimage.usc.edu/forums/t/page-overlap-while-reviewing-raw-file-a-way-to-set-to-0/11229/13


 *
 RAW file viewer speed (Low priority) :<<BR>>

  * Consider to change to a format that is faster to read
  * Add parameter to make the visual downsampling more or less aggressive
  *
  Keep the filter specifications in memory instead of recomputing for every page<<BR>>(Nice to have)


 *
 BioSemi: Add menu "Convert naming system" to rename channels into 10-10 (A1=>FPz)

 *
 Simulations: https://github.com/lrkrol/SEREEGA(Low priority)


== ECOG/SEEG ==
 *
 https://www.sciencedirect.com/science/article/pii/S1053811922005559

 * Display (high-priority)(Part SEEG grant):
  * Group display: Overlay multiple channel files in the same figure, coloring contacts by subject/ROI/Cluster/Electrode name
   *
   https://neuroimage.usc.edu/forums/t/37617

   * iEEG tab must be read-only when multiple files (hide configuration controls)

  *
  Bad channels: Contacts greyed out instead of ignored (Marcel H, Germany)<<BR>>(To diff between band and not-recorded) > Rendering of SEEG electrodes: Full surface modelling with surface mesh (see Lead-DBS models + code that generates them?)

  *
  Display time in H:M:S instead of S > If there is t0 in H:M:S  instead of S > As an option in Display configuration button>x-axis

  * view_leadfield_sensitivity: Add closing surfaces at cortex limits

 * Create clusters from anatomical labels (Anne So) :
  *
  Identify  contacts in a given anatomical region (volume scout, surface mesh, or  label in a volume atlas) / allow extracting the signals from all the  contacts in an ROI> As a process to select recordings, then Scouts from Volumen Atlas, Create cluster in channel file, then Extract time series.

  * Group analysis: extract clusters across subjects, display or average signals (see MIA) (Anne So)

 * Spike detection (Need to check for current toolboxes from scratch)(contact Nicolas R)(Mosher J)(iEEG BIDS):
  *
  https://iopscience.iop.org/article/10.1088/1741-2552/ac9259/pdf


 * Automatic segmentation of CT:
  *
  LeGUI: https://github.com/Rolston-Lab/LeGUI/tree/main/LeGUI<<BR>>https://neuroimage.usc.edu/forums/t/automatic-localization-of-seeg-electrodes/36302/7

  *
  GARDEL: http://meg.univ-amu.fr/wiki/GARDEL:presentation

  *
  SEEG DEETO Arnulfo 2015: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-015-0511-6

   * Used routinely at Niguarda Hospital + other hospitals worldwide, reliable tool.
   *
   To be used with SEEG-assistant/3DSlicer: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-017-1545-8


  *
  ECOG Centracchio 2021: https://link.springer.com/content/pdf/10.1007/s11548-021-02325-0.pdf

   *
   Classifier on thresholded CT: https://github.com/Jcentracchio/Automated-localization-of-ECoG-electrodes-in-CT-volumes


  *
  SEEG Granados 2018 (no code shared): https://link.springer.com/content/pdf/10.1007/s11548-018-1740-8.pdf


 * ECOG:
  * Project  and display contacts on cortex surface should consider the rigidity of  the grids: Contacts cannot rotate, and distance between contacts should  remain constant across runs
  *
  Method for contacts projection: https://pdfs.semanticscholar.org/f10d/6b899d851f3c4b115404298d7b997cf1d5ab.pdf

  *
  ECOG:  Brain shift: When creating contact positions on a post-implantation  image, the brain shift should be taken into account for creating images  of the ECOG contacts on the pre-op brain => iELVis (http://ielvis.pbworks.com/w/page/116347253/FrontPage) <<BR>>Normalization MNI? solutions with FieldTrip?


 *
 Display CT images: Better brightness/contrast adjustment: https://neuroimage.usc.edu/forums/t/automatic-localization-of-seeg-electrodes/36302/8 Range of values is way diff than ones from MRI. Current color maps are not suitable for CT, need to be improved.Together with processing of CT to get electrode positions.

 *
 Detection CCEP stim artifacts: Use ImaGIN code ImaGIN_StimDetect https://f-tract.eu/software/imagin/


== Pre-processing ==
 * process_detectbad:
  * Allow on raw files (for bad channels only)
  * Add detection on derivative of the signal (see EEGLAB)
  * Document in tutorial Bad channels
  * PREP pipeline / EEGLAB (Bigdely-Shamlo 2015)

 * Improve bad channel/trial detection:
  * ft_artifact_threshold and ft_rejectartifact
  * MNE-Python
  * EEGLAB

 * Integrate with EYE-EEG (Olaf Dimigen)
  *
  Reproduce tutorial: https://www.eyetracking-eeg.org/tutorial.html

  * Create EYE-EEG plugin + processes  (Raphael Lambert)
  * Process: Detect sacades (extended events) + fixations
  * Improved ICA
  * Eye-movement related potentials

 *
 Add note when rejecting trials: https://neuroimage.usc.edu/forums/t/33686


 *
 ICA: <<BR>>

  *
  Automatic classification: ICLabel: https://neuroimage.usc.edu/forums/t/automatic-eeg-ic-ica-classification-for-brainstorm/33785

  * Exploration: Add window with spectral decomposition (useful for muscle artifacts)
  * Export IC time series (and then compute their spectrum): solves the problem above
  * Import ICA matrices available in EEGLAB .set files
  *
  ICA+machine learning: https://www.ncbi.nlm.nih.gov/pubmed/28497769

  *
  Automated artifact rejection: https://arxiv.org/abs/1612.08194

  *
  Use EYE-EEG: EEGLAB toolbox for eye-tracker guided ICA (Olaf Dimigen): http://www2.hu-berlin.de/eyetracking-eeg/


 * SSP:
  *
  Display warning if changing the ChannelFlag while there is a Projector applied


 * File format:
  * Add support to read GDF file format
https://github.com/donnchadh/biosig/blob/master/biosig/t200_FileAccess/sload.m
 * <<BR>>
  *


== Reproducibility toolbox ==
 * Generate fully reproducible scripts, including all the interactive/graphical parts
 * Record all GUI actions as script calls
 * Import window: Add button to create the corresponding processing pipeline (to generate script or to edit additional options)
 * Adding the list of plugins to the reports (optionnal or foldable)
 * Better provenance: History fields, uniform file names...
 * Improving the pipeline editor to handle loops over data files or subjects

== Interface ==
 *
 Add a warning when computing a forward model with > 100000 sources (check selection)

 * Colormaps: Global colormap max: Should get the maximum across all the open files

 * Snapshot:
  * Save as image / all figures (similar to Movie/all figure)
  * Copy figures to clipboard (with the screencapture function)

 *
 Contact sheets & movies: use average of time windows instead of single instants, for each picture.

 * Contact sheets: Allow explicit list of times in input (+ display as in MNE-Python with TS)

== Database ==
 * Save iHeadModel somewhere in the datbase structure
 *
 Generalize the use of the units (field .DisplayUnits): Save in source files
-Line 50:
+Line 192:
- * Tutorial coherence [1xN]
 * t-tests on connectivity measures
 * Graph view:
  * Fixed scales for intensity sliders
  * Fix zoom in one region
  * Text bigger
  * Too much data in appdata
 * Other metrics:
  * Coherence by bands: bst_coherence_band_welch.m
  * Granger by bands: bst_granger_band.m
  * Inter-trial coherence
 * Work on progress bars
+ * Thresholding and stat tests for connectivity matrices:
  * Panel Display: Show only the top N% measures
  *
  Misic: https://www.nature.com/articles/s41583-022-00601-9

  *
  {{attachment:connect_toolboxes.jpg}}


 * Connect NxN display:
  * Graph on sensors: does not place the sensors correctly in space
  * Display as image: Add legend of the elements along X and Y axis
  * Display as time series: Display warning before trying to open too many signals
  * Optimize display: use surface() instead of line() for links? (as in figure_3d/PlotFibers)

 * Time-resolved correlation/coherence: Display as time bands
-Line 64:
+Line 210:
- * Use Matlab Coder to optimize some processes: Wavelets, bandpass filter, sinusoid removal
+ * Add MNE-Python functions:
  * scikit-learn classifiers
  * BEM single layer (John wants to test it)
  *
  ICA: https://neuroimage.usc.edu/forums/t/ica-on-very-long-eeg/23556/4

  *
  https://neuroimage.usc.edu/forums/t/best-way-to-export-to-mne-python/12704/3

  * Reproduce other tutorials / examples
  *
  Point-spread functions (PSFs) and cross-talk functions: https://mne.tools/stable/auto_examples/inverse/plot_psf_ctf_vertices.html#sphx-glr-auto-examples-inverse-plot-psf-ctf-vertices-py

  *
  Spatial resolution metrics in source space:<<BR>>https://mne.tools/stable/auto_examples/inverse/plot_resolution_metrics.html#sphx-glr-auto-examples-inverse-plot-resolution-metrics-py

  * Change the graphic renderer from Matlab

 *
 Chronux toolbox : http://chronux.org/

 *
 Add FieldTrip functions:

  * ft_sourceanalysis:
   * Check noise covariance
   * Check all the options of all the methods
   * Single trial reconstructions + noise covariance?
   *
   Filters?? http://www.fieldtriptoolbox.org/example/common_filters_in_beamforming

   *
   Beamformers: Save ftSource.avg.mom <<BR>>http://www.fieldtriptoolbox.org/workshop/meg-uk-2015/fieldtrip-beamformer-demo

   *
   http://www.natmeg.se/ft_beamformer/beamformer.html

   *
   http://www.fieldtriptoolbox.org/tutorial/beamformingextended

   * Baseline? Two inputs?

  * ft_prepare_heamodel: Add support from BEM surfaces from the Brainstorm database
  * Freqanalysis: ITC
  *
  ft_volumereslice: http://www.fieldtriptoolbox.org/faq/how_change_mri_orientation_size_fov

  * ft_freqanalysis
  * ft_combineplanar

 * Optimization:
  *
  Test speed for writing files: <<BR>>https://undocumentedmatlab.com/articles/improving-fwrite-performance

  * Use CUDA for speeding up some operations (filtering, wavelets, etc)
  * Use Matlab Coder to optimize: Wavelets, bandpass filter, sinusoid removal

 * Pipeline editor:
  * Bug: After "convert to continuous", the time of the following processes should change
  * Add loops over subjects/conditions/trial groups
  * Events: Allow selection from a drop-down list (similar to option "channelname" in panel_process_selection)

 *
 ITC: Inter-trial coherence (see MNE reports for group tutorial)<<BR>>http://www.sciencedirect.com/science/article/pii/S1053811916304232

 *
 Remove line noise: http://www.nitrc.org/projects/cleanline
-Line 66:
+Line 279:
-  * Frequency bands: extended syntax (ex: [2 3 4], 10:5:90, ...)
  * How to combine 3 orientations for unconstrained sources
  * Display logs as negative
  * 2D Layout in spectrum
  * Make much faster and more memory efficient (C functions coded by Matti ?)
  * Smooth display of TF/PAC maps (option)
  * TF scouts: should display average of TF maps
 * Bandpass: Show warning when using inappropriate high-pass filter (precision too high)
 * Artifact detection:
  * Detection of bad segments in the RAW files (Beth)
  * Artifact rejection like SPM: if bad in 20%, bad everywhere
  * Test difference between adjacent samples
 * Distributed processing: Brainstorm that can run without Java
 * SSP:
  * Display warning if changing the !ChannelFlag while there is a Projector applied
  * Show where the attenuation is projected:<<BR>>(sum(IK,2)-sum(SSP(k,:)*IK,2)./sum(IK,2)
 * Average:
  * Remember how many trials were used per channel
  * Save standard deviation
  * Display standard deviation as a halo around the time series
 * Co-registration of MEG runs:
  * SSP: Group projectors coming from different files
  * Finish validation of the method
  * Apply to continuous recordings for correcting head movements
 * Current Source Density (CSD) => Ghislaine<<BR>>http://psychophysiology.cpmc.columbia.edu/software/CSDtoolbox/index.html
 * Other processes:
  * Detrending
  * Moving average
  * Max
  * Median
  * Significance test (Dimitrios, Leo)
  * Spatial smoothing: check / document parameters
 * Contact sheets & movies: use average of time windows instead of single instants, for each picture.
 * Optical flow

== Database ==
 * MEG protocols: More flexible organization of the database; sub-conditions to allow different runs X different conditions.
 * Group matrix files => allow to process matrix files by trial types

 * Add notes in the folders (text files, visible as nodes in the tree)

 * Screen captures: save straight to the database

 * Rename multiple files

== Source modeling ==
 * Compare: dSPM vs. wMNE+zscore
 * Finish dipole scanning
 * Dipole fitting
 * Stenroos 2014 paper: Include the following methods
  * Inner and outer skull surfaces generator from !FieldTrip (needs SPM, probably not so different from BST)
  * Nolte corrected-sphere model (good model re:Alex)
  * Fast BEM models
 * Visualize Beamformer results:
  * Read CTF SAM .svl
  * Display as layers in the MRI viewer
 * Unconstrained sources:
  * Compute unconstrained and then project on the normal ?
  * Difference and stat should be: norm(A) - norm(B)
  * Stat and connectivity: what to do? (re-send email John+Sylvain)
 * Overlapping spheres: improve the estimation of the spheres for the frontal lobes
 * Volume grid:
  * Scouts 3D
  * Test volume sources with all the subsequent processes (timefreq, stat...)
  * Optimize: 3D display (better that 9x9 cubes)
  * Optimize: vol_dilate (with 26 neighbors)
 * Magnetic extrapolation: Do the same thing with EEG
 * Noise covariance matrix:
  * Display with figure_image()
  * Storage of multiple noise covariance matrices (just like the head models)
  * Always save as full, then at inversion time, we can decide between full, heteroskedastic (diagonal) or homoskedastic (i.i.d, scalar)
  * Problem of having inividual trials + averages in the condition => Display warning or not?
  * Save nAvg in noisecov file, to make it easier to scale to other recordings
  * When deploying to other conditions: Apply destination SSP (!NoiseCov = SSP . !NoiseCov . SSP' )
 * Sources on surface: Display peak regions over time (time = color) => A.Gramfort
 * Simulation: synthesize pseudo data-files from a cortex patch (duration, amplitude, noise)
 * Calculate !ImagingKernel * Gain for a scout
 * EEG Source modeling: Manage references and bipolar montages properly (maybe not necessary)
 * MEG source modeling: Do reconstruction only for a subset of sensors for estimating dipoles?
 * Processes compute head model and sources: Additional option to set the file comment
+  * Optimization: bst_timefreq (around l.136),  remove evoked in source space: Average should be computed in sensor  space instead of source space (requested by Dimitrios)
  *
  Short-time Fourier transform: http://www.mikexcohen.com/lectures.html

  * Hilbert with time bands very slow on very long files (eg. 3600s at 1000Hz) because the time vector is still full (10^7 values): save compressed time vector instead.
  * When normalizing with baseline: Propagate with the edge effects marked in TFmask
  * Allow running TF on montages
  * Review continuous files in time-frequency space (for epilepsy)
  * Bug when computing TF on constrained and unconstrained scouts at the same time (in mixed head models for instance): uses only the constrained information and doesn't sum the 3 orientations for the unconstrained regions.
-Line 148:
+Line 291:
+ *
 Import SimNIBS4: Use final_tissues_LUT.txt instead of fixed list of tissues: https://neuroimage.usc.edu/forums/t/removing-a-lesioned-area/38414/20

 *
 Simple-brain-plot: https://github.com/dutchconnectomelab/Simple-Brain-Plot


 * MNI normalization: More options:
  * DARTEL / SHOOT
  *
  BrainSuite (wait for Anand)

  * Import from SimNIBS (Conform2MNI_nonl.nii.gz, MNI2Conform_nonl.nii.gz)


 * MRI Viewer:
  *
  Adjust CT contrast better: https://neuroimage.usc.edu/forums/t/automatic-localization-of-seeg-electrodes/36302/10

  * Pan in zoomed view (shift + click + move?)
  * Zoom in/out with mouse (shift + scroll?)
  * Ruler tool to measure distances
  * Display scouts as additional volumes
  *
  Render surface envelope in the MRI as a thin line instead of the full interpolation matrix<<BR>>Or use inpolyhedron to get a surface mask and then erode it to get the volume envelope

  *
  Surface>Volume interpolation: Use '''spm_mesh_to_grid''' instead of tess_tri_interp


 * Defacing:
  *
  https://afni.nimh.nih.gov/pub/dist/doc/htmldoc/tutorials/refacer/refacer_run.html

  * Removing MNI face mask using MNI coordinates

 * Atlas switch in 3D MRI figures
 *
 Bug import anatomy: Requested nVert > high-resolution cortex surface: Creates an empty cortex_0V

 *
 BrainSuite:

  * Use same colors for left and right for anatomical atlases
  * Use for volume coregistration (rigid / non-rigid)
  * USCBrain: Add default electrodes positions
  *
  Remove BrainSuite1 when not needed anymore


 * Brain2mesh: Add import of 10-10 positions
 * Templates for different ages:
  *
  MNI: https://www.bic.mni.mcgill.ca/ServicesAtlases/NIHPD-obj1

  *
  Pediatric head atlases: https://www.pedeheadmod.net/pediatric-head-atlases-v1-2/


  *
  https://iopscience.iop.org/article/10.1088/2057-1976/ab4c76

  *
  https://www.biorxiv.org/content/biorxiv/early/2020/02/09/2020.02.07.939447.full.pdf

  *
  John Richards: https://www.nitrc.org/frs/?group_id=1361

  *
  Neurodev database: https://jerlab.sc.edu/projects/neurodevelopmental-mri-database/

  *
  https://openneuro.org/datasets/ds000256/versions/00002

  *
  https://osf.io/axz5r/
-Line 150:
+Line 372:
-  * Project scouts betweens subjects and between hemispheres
  * Display scouts in a tree: hemisphere, region, subregion
  * Downsample to atlas: allow on timefreq/connect files
  * Sort scouts by region in process options
 * Generate mixed density surfaces
 * Import / registration:
  * Major bug when importing surfaces for an MRI that was re-oriented manually
 * Use mid-gray instead of pial surface?
+ * Parcellating volume grids: scikit-learn.cluster.Ward
 *
 Geodesic distance calculations:<<BR>>https://www.mathworks.com/matlabcentral/fileexchange/6110-toolbox-fast-marching

 * Improving the registration between EEG and anatomy templates:
  * Warping: Improve the basic alignment of the digitized electrodes on the templat, possibly with Cz and other anatomical landmarks
  * EEG template positions: rework using a standardized Cz position (+ other landmarks)


== Forward modeling ==
 * DUNEuro/FEM:
  *
  Add lesion mask to SimNIBS: https://simnibs.github.io/simnibs/build/html/documentation/command_line/add_tissues_to_upsampled.html#add-tissues-to-upsampled-doc

  *
  GeomtryAdapted: Buggy?

  *
  Display differences between leadfields: amplitude of difference (right-click > Compare)

  * Display sensitivity on FEM surface

 * OpenMEEG: Detect bad results + exclude from leadfield
 * BEM single sphere: Get implementation from MNE
 * Add eyes models to attract eye activity

== Source modeling ==
 *
 Reproduce results in "Simultaneous human intracerebral stimulation and HD-EEG, ground-truth for source localization methods": https://www.nature.com/articles/s41597-020-0467-x

 * eLORETA instead of sLORETA?
  *
  https://neuroimage.usc.edu/forums/t/compute-eeg-sources-with-sloreta/13425/6

  *
  https://neuroimage.usc.edu/forums/t/loreta-and-source-localization/30525

  *
  "eLORETA  algorithm  is  available  in  the  MEG/EEG Toolbox of Hamburg (METH)": https://www.biorxiv.org/content/biorxiv/early/2019/10/17/809285.full.pdf

  *
  https://github.com/brainstorm-tools/brainstorm3/issues/114


 * Point-spread and cross-talk functions (code in MNE-Python):
  *
  https://www.biorxiv.org/content/biorxiv/early/2019/06/18/672956.full.pdf

  *
  https://github.com/olafhauk/EEGMEGResolutionAtlas


 * Dipoles:
  * Display dipoles in MRI viewer
  * panel_dipoles: Doesn't work with multiple figures

 * Project sources: Very poor algorithm to project sub-cortical regions and cerebellum
 * Maximum:
  *
  Menu Sources > Maximum value: Doesn't work with volume or mixed head models

  * Panel Get coordinates: Add button "find maximum"
  *
  Sources on surface: Display peak regions over time (time = color) => A.Gramfort


 * Volume grid:
  * Optimize: 3D display (better than 9x9 cubes)
  * Optimize: vol_dilate (with 26 neighbors)
-Line 160:
+Line 445:
- * ANOVA: Use LENA functions
+ * Stat on unconstrained sources?
 *
 Stat/time series: Hide lines going down to zero (Dimitrios: https://neuroimage.usc.edu/forums/t/common-source-activation-across-subjects-and-conditions/1152/21)

 * Cluster stat: Add frequency selection option
 * ANOVA:
  * Write panel similar to Process1 and Process2
-Line 163:
+Line 454:
- * Permutation tests:
  * t-test only (wilcoxon? sign-test?): paired, equal var, unequal var
   * http://www.adscience.fr/uploads/ckfiles/files/html_files/StatEL/statel_wilcoxon.htm
   * http://www.mathworks.fr/fr/help/stats/signrank.html
   * Less powerful than t-tests
  * nb permutations ~ 1000
  * maximum statistic over "time" or "time and space"
 * Permutations / clustering: cf fieldtrip
  * http://fieldtrip.fcdonders.nl/tutorial/cluster_permutation_timelock
  * http://fieldtrip.fcdonders.nl/tutorial/cluster_permutation_freq
 * Threshold  in time: keep only the regions that are significative for contiguous  blocks of time, or over a certain number of time points<<BR>> => Process that creates a static representation of a temporal window
 * t-test on volume sources
 * Paired t-test on unconstrained sources: (convert to flat + Z-score) => !AnneSo
  * Question of Gaussianity of the samples: take a subset of samples + Kolmogorov-Smirnov / Shapiro-Wilk test
  * http://fr.wikipedia.org/wiki/Test_de_Shapiro-Wilk
  * http://stats.stackexchange.com/questions/362/what-is-the-difference-between-the-shapiro-wilk-test-of-normality-and-the-kolmog
  * http://www.mathworks.fr/fr/help/symbolic/mupad_ug/perform-shapiro-wilk-test.html
  * http://www.mathworks.fr/fr/help/symbolic/mupad_ref/stats-swgoft.html
  * http://stackoverflow.com/questions/14383115/shapiro-wilk-test-in-matlab
 * Create icons for Stat/PAC, Stat/Sprectrum, etc.
 * One sample t-test across subjects
+ *
 Multivariate stim-response analysis: https://github.com/mickcrosse/mTRF-Toolbox
-Line 186:
+Line 460:
- * Finish MINC/CIVET integration (finir lecture MINC2: P Bellec)
  * Send email to CIVET mailing list when done
 * !FieldTrip structures: In / Out (see fieldtrip/utilities/ft_datatype_*)
 * EEG File formats:
  * EEG !CeeGraph
  * EGI: Finish support for epoched files (formats 3,5,7)
 * BCI2000 Input (via EEGLAB plugin)
 * EEGLAB import: Selection of conditions in script mode

== Distribution & documentation ==
 * Add Help buttons and menus (in popups, dialog windows...) => Links to the website.


 * Publication list: Folder by years
 * Finish existing tutorials:
  * Dipoles
  * FieldTrip/Auditory: Extend to MNE/EEGLAB/SPM
 * New tutorials:
  * MEG connectome
  * Describe all the processes
  * Statistics
  * Coherence (cortico-muscular ?)
  * Intra-cranial recordings (Average ref by groups using Comment field)
  * Co-register MEG runs (Beth)
 * Missing in the introduction tutorials:<<BR>>
  * First steps: Brainstorm preferences
  * First steps: Temporary folder
  * Exploration: Clusters
  * Headmodel: explain the fields + how to get the constrained leadfield
  * Sources: Model evaluation (by simulating recordings)
  * Sources: Theshold min. size (not documented yet)
  * Time-frequency: Description of "log freq scale" option
 * Missing in tutorial "Export to SPM": Add section "Compare with Brainstorm"
 * Missing in page "Cite Brainstorm": Add all the methods used in the software
 * Rewrite basic 12+3 tutorials: group in one series
+ * BIDS import:
  * Add option to process to specify the protocol name
  * Full support for iEEG and EEG
  * Disable logging of sub-processes (reloading the previous report should only show process_import_bids)
  * Read real fiducials (OMEGA) / transformation matrices:
   *
   https://groups.google.com/g/bids-discussion/c/BeyUeuNGl7I

   *
   https://github.com/bids-standard/bids-specification/issues/752#issuecomment-795880992

   *
   https://github.com/brainstorm-tools/brainstorm3/issues/139


  * Use BIDS-Matlab?

 * Test datasets:
  * See list of test datasets in process_import_bids.m
  * ds004085 / ds004473: Check response epoch + BUG with coordinate interpretation

 * BIDS export:
  * EEG, iEEG: Add events.tsv, channel.tsv, electrodes.tsv
  * Anatomy: Add t1w.json (including fiducials)
  * Use BIDS-Matlab?

 * EDF+ reader: Add resampling of channels with different sampling rates
 *
 Support for OpenJData / JNIfTI: https://github.com/brainstorm-tools/brainstorm3/issues/284

 * DICOM converter:
  * Add dcm2nii (MRICron)
  * Add MRIConvert

 * SPM .mat/.dat: Fix the import of the EEG/SEEG coordinates
 *
 EEG File formats:<<BR>>

  *
  XLTEK: https://github.com/danielmhanover/OpenXLT

  *
  Persyst .lay: https://github.com/ieeg-portal/Persyst-Reader

  *
  Nervus .eeg: https://github.com/ieeg-portal/Nervus-Reader

  *
  Biopac .acq: https://github.com/ieeg-portal/Biopac-Reader

  * BCI2000 Input (via EEGLAB plugin)

 * 4D file format:
  * Use reader from MNE-Python: mne.io.read_raw_kit  (skip Yokogawa slow library)
  * Reference gradiometers: Keep the orientation of the first or second coil?
  * Reference gradiometers: Add the sensor definition from coil_def.dat
  * Validate with phantom recordings that noise compensation is properly taken into account
  * The noise compensation is considered to be always applied on the recordings, not sure this assumption is always correct
  * 4D phantom tutorial (JM Badier?)

 * BST-BIN: Add compression to .bst
 * MINC MRI: Add support for "voxel to world" transformation (vox2ras) similarly to .nii

== Distribution ==
 * Java-free Matlab: All references of functions below must be removed
  *
  '''JavaFrame''': screencapture.m (used for screen captures of videos)

  *
  '''Actxcontrol''': Used for video-EEG

   *
   uihtml + JavaScript callbacks?

   * ActiveX in .NET app?
   * Pure Java framce + VLC java plugin?
   * Other video player?

  *
  '''Javacomponent''':

   * mri_editMask
   * figure_mri
   * process_bandpass

  *
  List .jar files used from Matlab distribution (e.g. dom) => Check all the import calls


 *
 Cleanup GitHub repository:

  *
  https://github.com/brainstorm-tools/brainstorm3/issues/473

  * Remove ICBM152 default anatomy from repo
  * Move external I/O libraries as plugins:
   * mne-matlab
   * CEDS64ML
   * edfimport
   * eeprobe
   * son
   * ricoh
   * yokogawa
   * easyh5



== Documentation ==
 * All tutorial datasets in BIDS (including introduction tutorials)
 * Deface the MRIs of all the tutorials
 *
 Count GitHub clones in the the download stats

 * MNE-Python 1.0: Test and update install documentation
 * Tutorial OMEGA/BIDS:
  * Update the organization of derivatives folder (full FS folders)
  * Download example datasets directly from the OMEGA repository

 *
 New tutorials: <<BR>>

  *
  Other public datasets: [[https://github.com/INCF/BIDS-examples/tree/bep008_meg|https://github.com/INCF/BIDS-examples/tree/bep008_meg/]]

  * EEG/research
  *
  FieldTrip ECOG tutorial: http://www.fieldtriptoolbox.org/tutorial/human_ecog

  *
  Reproduce tutorials from MNE-Python: https://martinos.org/mne/stable/tutorials.html

  *
  Cam-CAN database: https://camcan-archive.mrc-cbu.cam.ac.uk/dataaccess/<<BR>>(download new datasets, including maxfiltered files and manual fiducial placements)

  * MEG steady-state / high-gamma visual / frequency tagging
  *
  Reproduce results from "Simultaneous human intracerebral stimulation and HD-EEG, ground-truth for source localization methods": https://www.nature.com/articles/s41597-020-0467-x

  * Stand-alone ICA tutorial
-Line 223:
+Line 603:
- * Import anatomy folder menu freezes Matlab on MacOS 10.9.3 / Matlab 2014a
 * Import anatomy folder menu crashes on MacOSX 10.8.5 / Matlab 2013b
 * Record tab: Text of epoch number is too big on MacOS
 * Menu "Use default EEG cap" doesn't work for a multiple selection (setting the same EEG cap for several subjects)
 * in_bst_data_multi: If trials have different sizes, output is random (the one of the first file)
 * tree_dependencies: sources files, reprojected on default anatomy; If  based on data files that are bad trials, they should be ignored by  tree_dependencies, and they are not
 * Image viewer has some bugs on some systems
 * Screen capture for reports never works: Find another solution
 * Screen capture when there is a fading effect in the window manager: captures the window
 * Close figure with coherence results should hide the "frequency" slider
 * Problems growing scouts on merged surfaces (Emily)
 * Edit scout in MRI: small modifications cause huge increase of the scout size
+ * Image viewer:
  * Difficult to get to 100%
  * Buggy on some systems

 * 2DLayout:
  * (TF) Units are weird with % values
  * (TF) Difficult to navigate in frequencies: Scaling+changing frequency resets the scaling

 * Progress bar:
  * Doesn't close properly on some Linux systems
  * Focus requests change workspace when processing constantly (Linux systems)


== Distributed computing ==
 *
 Options from FieldTrip:

  *
  Loose collection of computers: https://github.com/fieldtrip/fieldtrip/tree/master/peer

  *
  Single multicore machine: https://github.com/fieldtrip/fieldtrip/tree/master/engine

  *
  Batch system: https://github.com/fieldtrip/fieldtrip/tree/master/qsub

  *
  Documentation: https://www.fieldtriptoolbox.org/faq/what_are_the_different_approaches_i_can_take_for_distributed_computing/


 *
 PSOM: http://psom.simexp-lab.org/

 *
 Google: https://www.youtube.com/watch?v=LLMXV3o2FT0

  *
  https://edu.google.com/why-google/case-studies/unc-chapel-hill-gcp/
-Line 237:
+Line 645:
- * Hide Java panels instead of deleting them
 * mri2scs: convert arguments to meters
 * Interpolations: Use scatteredInterpolant, griddedInterpolant, triangulation.nearestNeighbor (Matlab 2014b)
 * bst_warp and channel_project: Use tess_parametrize_new instead of tess_parametrize
 * Shared kernels: do the "get bad channels" operation in a different way (reading all the files is too slow)
 * Optimize bst_get:
  * Now study and subject have necessarily the same folder name
  * Replace big switch with separate functions
 * Progress bar:
  * Add different levels (to handle sub-processes)
  * Make work correctly with RAW on resting tutorial
  * Uniformize calls in bst_process/Run
  * Add a "Cancel" button
 * Line smoothing / anti-aliasing (time series figures)
 * Fix all the 'todo' blocks in the code
 * Replace handle "0" with bst_get('groot')
 * At the end of bst_startup in compiled mode, replace loop with waitfor(jFrame)
+ * Replace all calls to inpolyhd.m with inpolyhedron.m (10x faster)
 *
 Interface scaling: Rewrite class IconLoader to scale only once the icons at startup instead of at each request of an icon (might improve the speed of the rendering of the tree)

 * Processes with "radio" and "radio_line" options: Replace with "radio_label" and "radio_linelabel"
 * Interpolations: Use scatteredInterpolant, griddedInterpolant, triangulation.nearestNeighbor (2014b)

Software

Users

Development

What's next

Recordings

ECOG/SEEG

Pre-processing

Reproducibility toolbox

Interface

Database

Connectivity

Processes

Anatomy

Forward modeling

Source modeling

Statistics

Input / output

Distribution

Documentation

Current bugs

Distributed computing

Geeky programming details