Differences between revisions 419 and 576 (spanning 157 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
Default montages for EEG (sensor selection)
Sleep scoring wish list (Emily C):
- Configurable horizontal lines (for helping detecting visually some thresholds)
- Mouse ruler: Measure duration and 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:
- Downsample before filtering? (attention to the filter design)
- Add parameter to make the visual downsampling more or less aggressive
- Pre-load next page of recordings
- Keep the filter specifications in memory instead of recomputing for every page
BioSemi: Add menu "Convert naming system" to rename channels into 10-10 (A1=>FPz)
Simulations: https://github.com/lrkrol/SEREEGA

ECOG/SEEG

Display:
- 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)
- Display time in H:M:S (useful for tutorial Epileptogenicity)
- Display curved SEEG electrodes
- Rendering of SEEG electrodes: Full surface modelling with surface mesh (see Lead-DBS models + code that generates them?)
- view_leadfield_sensitivity: Add closing surfaces at cortex limits
Create clusters from anatomical labels:
- 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
- Group analysis: extract clusters across subjects, display or average signals (see MIA)
Spike detection:
- 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
Detection CEEP stim artifacts: Use ImaGIN code ImaGIN_StimDetect

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

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)

-  ⇤ ← Revision 419 as of 2019-03-20 10:43:58 → 
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  Editor: FrancoisTadel
  Comment:
+   ← Revision 576 as of 2023-09-03 10:33:43 → ⇥
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  Comment:
-Deletions are marked like this.
+Additions are marked like this.
 Line 7:
- * RAW file viewer:<<BR>>
  * Bottom bar: display extend events as segments instead of dots (to see their extension)
+ * 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
 * Default montages for EEG (sensor selection)
 * Sleep scoring wish list (Emily C):
  * Configurable horizontal lines (for helping detecting visually some thresholds)
  * Mouse ruler: Measure duration and 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:
-Line 13:
+Line 21:
-  * Add field "comment" to markers: For clinicians to add notes (Marcel)
  * Events: Change the category of a selected event easily, instead of deleting/marking new
  * Events: Advanced process for recombining.<<BR>>Example:  http://www.erpinfo.org/erplab/erplab-documentation/manual/Binlister.html
 * EEG: Laplacian montage (see doc sent by Jeremy)
 * Bad trials: When changing the status of bad to good: remove the bad segments as well, otherwise it is not processed by processes like the PSD.
 * Review clinical recordings: Reduce the dimensionality of the data with a simple inverse problem, similar to what we do for the magnetic extrapolation ("Regional sources" in BESA, cf S Rampp)
 * MEG/EEG registration: Apply the same transformation to multiple runs
 * 2DLayout:
  * Does not work when DC offset is not removed
  * Add a proper amplitude scale that gets updated when shift+scroll, to compare figures
 * Create heat maps: Maybe with matlab function heatmap?
+ * BioSemi: Add menu "Convert naming system" to rename channels into 10-10 (A1=>FPz)
 * Simulations: https://github.com/lrkrol/SEREEGA

== ECOG/SEEG ==
 * Display:
  * 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)
  * Display time in H:M:S (useful for tutorial Epileptogenicity)
  * Display curved SEEG electrodes
  * Rendering of SEEG electrodes: Full surface modelling with surface mesh (see Lead-DBS models + code that generates them?)
  * view_leadfield_sensitivity: Add closing surfaces at cortex limits
 * Create clusters from anatomical labels:
  * 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
  * Group analysis: extract clusters across subjects, display or average signals (see MIA)
 * Spike detection:
  * 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
 * Detection CEEP stim artifacts: Use ImaGIN code ImaGIN_StimDetect

== 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

== 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
-Line 27:
+Line 94:
- * Multiple screens: Add option to set on which display the main bst window should be
 * File filters: Add boolean logic: https://github.com/brainstorm-tools/brainstorm3/issues/68
 * Snapshot: Save as image / all figures (similar to Movie/all figure)
 * Generalize the use of the units (field .DisplayUnits): Rewrite processes to save the units correctly
 * Colormaps:
  * Allow brightness/contrast manipulations on the custom colormaps
  * Create a colormap similar to MNE, where extrema are bright
  * Global colormap max: Should get the maximum across all the open files
  * Set parula (or others) as the default, not jet: https://bids.github.io/colormap/
  * https://jakevdp.github.io/blog/2014/10/16/how-bad-is-your-colormap/
  * https://www.youtube.com/watch?v=xAoljeRJ3lU
 * Open new figures as tab (docked in the Figures window)
 * Copy figures to clipboard (with the screencapture function)
 * Display warning before opening files that are too big
 * Smooth display from figure_image (ERPimage, raster plot...)
+ * 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)
-Line 44:
+Line 101:
- * Display CTF coils: Show discs instead of squares
 * Use boundary() instead of conhull() in all the display functions (ie. 2DDisc)
+== Database ==
 * Save iHeadModel somewhere in the datbase structure
 * Generalize the use of the units (field .DisplayUnits): Save in source files
-Line 48:
+Line 107:
- * Thresholding and stat tests the connectivity matrices
 * Connectivity on unconstrained sources: "Default signal extraction for volume grids should be the time series of  the first principal component of the triplet signals after each has  been zero-meaned" (SB)
 * Display of connectivity graphs:
  * Display as straight lines
  * Recode 2D graphs
  * 3D display with anatomical constrains
  * Display using real position of EEG electrodes
 * Use new band-pass filters in bst_connectivity ('bst-hfilter' instead of 'bst-fft-fir')
 * Review by Jan-Mathijs: http://journal.frontiersin.org/article/10.3389/fnsys.2015.00175/full
 * Connectivity based on band limited power (Sylvain):
  * Compute Hilbert/Bandpass + correlation of the envelopes
  * Bandpass envelopes before computing correlations?
  * Compute Hilbert(sensors) and then project to source space?
 * Matrix view of NxN graphs: Add legend of the elements along X and Y axis
 * Graph view:
  * Does not display negative values correctly (correlation or difference of coherence)
  * Re-write using pure Matlab code and smoothed graphics
  * Fixed scales for intensity sliders
  * Text bigger
  * Too much data in appdata
  * Fixed scales for intensity sliders
  * Add "=" shortcut for having graphs with similar configurations
  * Disable zoom in one region (serious bugs)
  * NxN on sensors: does not place the sensors correctly in space
 * Coherence:
  * Average cross-spectra instead of concatenating epochs (to avoid discontinuities)<<BR>>Explore inter-trial approaches (Esther refers to chronux toolbox)
 * Granger:
  * Crashes sometimes: improve stability
  * Check for minimum time window (Esther: min around 500-1000 data points)
  * Re-write and optimize code
  * Add progress bar
 * PLV:
  * Add p-values
  * Remove evoked
  * Optimize code
  * Add time integration
  * Unconstrained sources
  * Add warning when running of short windows (because of filters)
 * PAC:
  * Add input TF , to disconnect TF decomposition and PAC computation (Peter)
  * Refine frequency vector of low frequencies
  * How many central frequencies to use in bst_pac?
  * Change filters: no chirplet functions
  * bst_freqfilter: Use nfcomponents like in bst_pac
  * Esther recommended a larger frequency binning of the PAC estimation
  * PAC maps: Display all sensors at once (like TF and DynamicPAC)
 * Hui-Ling's PAC:
  * https://bsp.hackpad.com/Cross-Frequency-Coupling-cChe95lhDHz
  * https://github.com/NCTU-BSP/MEEG
+ * 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)
-Line 98:
+Line 117:
- * Other metrics:
  * Coherence by bands: bst_coherence_band_welch.m
  * Granger by bands: bst_granger_band.m
  * Inter-trial coherence
 * Tutorial coherence [1xN] : Reproduce FieldTrip results?
 * Connect NxN: Display as time series > Display warning before trying to open too many signals
-Line 106:
+Line 119:
- * Use CUDA for speeding up some operations (filtering, wavelets, etc)
 * Allow processes in Python and Java
-Line 109:
+Line 120:
-  * scikit-learn classifiers: S Marti / G Dehaene
  * Implement data exchange with MNE-Python: write FIF files from Brainstorm and/or pass python objects in memory instead of FIF files
  * SSS/tSSS cleaning
+  * 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
-Line 113:
+Line 125:
+  * 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
-Line 114:
+Line 128:
+ * Chronux toolbox : http://chronux.org/
-Line 124:
+Line 139:
-  * ft_prepare_sourcemodel: Compute MNI transformation (linear and non-linear) => Peter
+  * ft_prepare_heamodel: Add support from BEM surfaces from the Brainstorm database
-Line 126:
+Line 141:
-  * ft_read_atlas('TTatlas+tlrc.BRICK');
-Line 130:
+Line 144:
- * Decoding/Classifiers: Faster algorithms (MNE-Python?)
+ * 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
-Line 136:
+Line 153:
- * ICA:
  * Why doesn't the ICA process converge when using 25 components in the EEG tutorial?
  * Add an option to resample the signals before computing the ICA decomposition
  * Add a stand-alone tutorial
  * Exploration: Add window with spectral decomposition (useful for muscle artifacts)
  * Export IC time series (and then compute their spectrum): solves the problem above
  * Comparison JADE/Infomax: <<BR>> http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0030135
  * Use faster methods (MNE-Python?)
  * Add methods: SOBI, Fastica, AMICA/CUDICA (recommended by S Makeig)
  * Dimension reduction with PCA adds artifacts: Not done by default in EEGLAB<<BR>>Contact: Stephen Shall Jones ( shall-jones@infoscience.otago.ac.nz )<<BR>>Student Carl Leichter detailed this in his thesis
  * S Makeig: Use ICA to select the IC of interest instead of only removing artifacts
  * Display of spectrum for components (PSD/FFT)
  * Use FastICA (algo crashing)
  * Add components preselection: Correlation with EOG/ECG
  * Import ICA matrices available in EEGLAB .set files
  * EEGLAB recommends ICA + trial rejection + ICA again: Impossible right now with Brainstorm<<BR>>(http://sccn.ucsd.edu/wiki/Chapter_09:_Decomposing_Data_Using_ICA)
  * ICA+machine learning: https://www.ncbi.nlm.nih.gov/pubmed/28497769
  * Automated artifact rejection: https://arxiv.org/abs/1612.08194
  * Save IC time series in database
  * Use EYE-EEG: EEGLAB toolbox for eye-tracker guided ICA (Olaf Dimigen): http://www2.hu-berlin.de/eyetracking-eeg/
 * Other EEGLAB functions:
  * Step function detection: https://github.com/lucklab/erplab/wiki/Artifact-Detection:-Tutorial
 * 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)
 * Pipeline editor:
  * When computing sources from the pipeline editor: doesn't reselect the options if you click twice on "edit" (works  for minnorm, but not for lcmv)
  * When computing time-frequency/hilbert/psd: Find a way not to force the user to click on Edit
 * Bandpass:
  * Use new filters in all the functions using a bandpass  ('bst-hfilter' instead of 'bst-fft-fir'): process_evt_detect_threshold
  * Weird bug: Filter(import) != Import(Filter) in the HCP tutorial... to investigate
 * Bandpass
 * Spectral flattening (John):
  * ARIMA(5,0,1): Apply on the signal before any frequency/connectivity/PAC analysis

 * PSD:
  * Rewrite to have the same input as coherence (frequency resolution instead of window length)

  * Use the progress bar

  * Allow display of Avg+StdErr
-Line 179:
+Line 154:
- * Use Matlab Coder to optimize some processes: Wavelets, bandpass filter, sinusoid removal
 * Reports: Click on link reopens exactly the figure
-Line 184:
+Line 157:
-  * Matching pursuit: http://m.jneurosci.org/content/36/12/3399.abstract?etoc
  * Bug: Display logs as negative
  * Bug: 3D figures: Colormaps with "log" option doesn't work
  * Bug: Difference of power displayed in log: problems (Soheila)
  * 2D Layout in spectrum
  * Make much faster and more memory efficient (C functions coded by Matti ?)
  * TF scouts: should display average of TF maps
  * Impossible to keep complex values for unconstrained sources
  * Pad short epochs with zero values for getting lower frequencies
-Line 194:
+Line 158:
-  * Extend clusters tab to display of TF to overlay TF signals (Svet)
-Line 196:
+Line 159:
-  * Allow baseline normalization of files computed with time bands
-Line 200:
+Line 162:
- * Artifact detection:
  * Artifact rejection like SPM: if bad in 20%, bad everywhere
  * Test difference between adjacent samples
 * Events detection: Add option "std" vs "amplitude"
 * 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
 * Simulation:
  * Fix units in simulation processes => no *1e-9 in "simulate recordings"
  * Use "add noise" process from Hui-Ling (in Work/Dev/Divers)
 * Use field process field "Group" to separate Input/Processing/Output options
 * Use new Matlab functions: movmean, movsum, movmedian, movmax, movmin, movvar, movstd
 * Process ft_prepare_heamodel: Add support from BEM surfaces from the Brainstorm database

== Database ==
 * Faster DB searches (for Emily)
 * Add buttons to sort files: by name, by comment, by date
 * MEG protocols: More flexible organization of the database; sub-conditions to allow different runs X different conditions.
 * Matrix files: Allow to be dependent from other files

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

 * Screen captures: save straight to the database

 * Rename multiple files

 * Default headmodel lost when reloaded: Keep selection on the hard drive (in brainstormstudy.mat)

 * Auto-save:
  * protocol.mat can be too big: do not store the results links in it (and recreate when loading)- http://neuroimage.usc.edu/forums/t/abnormally-slow-behavior/2065/10

  * Improve auto-save: add tracking file next to protocol.mat, do not save all the time, only when closing app, and reload protocol at stratup if tracking file is still there

== Distributed computing ==
 * Options from FieldTrip:
  * Loose collection of computers: https://github.com/fieldtrip/fieldtrip/tree/master/peer
  * Alternative, with less limitations: http://research.cs.wisc.edu/htcondor/
  * Single multicore machine: https://github.com/fieldtrip/fieldtrip/tree/master/engine
  * Batch system: https://github.com/fieldtrip/fieldtrip/tree/master/qsub
  * Documentation: http://fieldtrip.fcdonders.nl/faq#distributed_computing_with_fieldtrip_and_matlab
 * PSOM: http://psom.simexp-lab.org/
 * Various initiatives: http://samirdas.github.io/Data_sharing.html#/
+== 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<<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/

 * Scouts:
  * Display edges in the middle of the faces instead of the vertices
 * 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
-Line 245:
+Line 221:
+ * 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
-Line 246:
+Line 231:
-  * Project individual dipoles files on a template
+  * Display dipoles in MRI viewer
-Line 248:
+Line 233:
- * Project sources: Very poor algorithm to project sub-cortical regions and cerebellum (algorithm to fit surfaces should be imrpoved)
 * Menu head model > Copy to other conditions/subjects (check if applicable first)
 * Menu Sources > Maximum value: Doesn't work with volume or mixed head models
 * Mixed head models: <<BR>>
  * Set loose parameter from the interface
+ * 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
-Line 256:
+Line 241:
- * Menu Sources > Simulate recordings:
  * Do not close the 3D figures after generating a new file
  * Add a process equivalent to this menu
 * Panel Get coordinates: Add button "find maximum"
 * BEM single sphere: Get implementation from MNE
 * Visualize Beamformer results:
  * Read CTF SAM .svl
  * Display as layers in the MRI viewer
 * Unconstrained sources:
  * Stat and connectivity: what to do? (re-send email John+Sylvain)
 * Overlapping spheres: improve the estimation of the spheres for the frontal lobes
 * 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
 * Sources on surface: Display peak regions over time (time = color) => A.Gramfort
 * Calculate ImagingKernel * Gain for a scout
 * Time-frequency beamformers:
  * Band-pass everything in different frequency bands + Source estimation + TF
  * Ask data to Sarang where he sees effects that cannot be extracted with MN followed by TF
 * Process "Extract scouts time series": Add PCA option (replace isnorm with choice PCA/Norm)
 * BEM: Fix unstable results when one vertex is too close from the layers (5mm ?)
 * Hui-Ling beamformers:
  * More explanations about what is in NAI and Spatial filters
  * Explain that is this is better to study effects extended in time (Ntime > Nsensors)
  * Group LCMV+MCB
  * Condition LEFT median nerve: very bad results
 * Keep options for inverse computation
 * OpenMEEG: Post example datasets for the remaining issues:
  * https://github.com/openmeeg/openmeeg/issues/64
  * https://github.com/openmeeg/openmeeg/issues/68
  * Example protocol ECOG: doesn't work
 * Add eyes models to attract eye activity

== Anatomy ==
 * BrainVISA: Add support for MarsAtlas
 * MNI transformation: Use non-linear MNI transformation y_...
 * Registration:<<BR>>
  * Getting electrode positions from 3D scanners: https://sccn.ucsd.edu/wiki/Get_chanlocs
  * GARDEL: http://meg.univ-amu.fr/wiki/GARDEL:presentation
  * Use the same registration for multiple recording sessions that have already re-registered previously (eg. with MaxFilter)
  * When linking multiple EEG recordings including 3D positions, do the registration only once and copy it to all the runs
  * Check templates: MNI transformation and volume atlases for ICBM152 vs Colin27 (loading the AAL atlas as surface or voume scouts do not align well on the ICBM152)
  * Compute non-linear MNI registration instead of linear
  * Select and remove bad digitized head points before automatic coregistration
  * Load the MNE -transf.fif: http://neuroimage.usc.edu/forums/showthread.php?2830
 * MRI Viewer:
  * Add display of "world coordinates" when "vox2ras" is available
  * Pan in zoomed view (shift + click + move?)
  * Zoom in/out with mouse (shift + scroll?)
  * Ruler tool to measure distances
  * Add keyboard shortcuts to scroll in the three orientations (same in MRI 3D)
  * Display scouts as additional volumes
  * Render surface envelope in the MRI as a thin line instead of the full interpolation matrix
  * Edit fiducials: Replace 6 text boxes with 1 for easy copy-paste (see fiducials.m)
  * Optimize computation interpolation MRI-surface (tess_tri_interp) => spm_mesh_to_grid
 * BrainSuite:
  * Add new labels to all BrainSuite anatomy templates
  * Use BrainSuite inner skull for surface generation
  * Use same colors for left and right for anatomical atlases
 * Scouts:
  * Display edges in the middle of the faces instead of the vertices
  * Display scouts in a tree: hemisphere, region, subregion
  * Sort scouts by region in process options
  * Downsample to atlas: allow on timefreq/connect files
  * Project from one hemisphere to the other using registered spheres/squares (http://neuroimage.usc.edu/forums/t/how-to-create-mirror-roi-in-the-other-hemisphere/5910/8)
 * Parcellating volume grids: scikit-learn.cluster.Ward
 * Major bug when importing surfaces for an MRI that was re-oriented manually
 * Smooth surface: Fix little spikes due to irregularities in the mesh
 * Surface>Volume interpolation: Use spm_mesh_to_grid
 * Bug: Hide scouts in the preview of the grid for volume head models

== ECOG/SEEG ==
 * Electrode models: Better way for managing/updating/adding electrode models
 * SEEG: Project contacts to SEEG / Compare with IntrAnat
 * Contact positions: Import / set / detect<<BR>>
  * New option: Align on none|inner|cortex to replace ECOG-mid
  * Add history: Save modifications and transformations applied to the channel files (Marcel)
  * ECOG: How to handle cases where not all the grid contacts are in the channel file? (Marcel)
  * Project contact positions across subjects or templates (Marcel)
  * ECOG: Default names of contacts?
  * Add menu to import implantation channel file in imported recordings
 * Automatic segmentation of CT:
  * GARDEL: http://meg.univ-amu.fr/wiki/GARDEL:presentation
  * Arnulfo: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-015-0511-6
  * MAP07 / SPM: https://www.epi.ch/_files/Artikel_Epileptologie/Huppertz_2_13.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)
 * Display:
  * Bad channels: Contacts greyed out instead of ignored (Marcel)
  * Display time in H:M:S
  * Display curved SEEG electrodes
  * Display wires for ECOG?
 * Re-referencing:
  * Create new average reference montages with a specific list of channels, with the possibility to edit the order of the channels (for Jeremy)
  * Closest white reference (Arnulfo)
 * Detection CEEP stim artifacts: Use ImaGIN code ImaGIN_StimDetect
 * Alternatives to OpenMEEG: SimBio/FieldTrip? Matti Stenroos? NFT/NIST?
-Line 361:
+Line 243:
+ * 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
-Line 362:
+Line 247:
-  * Use LENA functions(?)
+  * Write panel similar to Process1 and Process2
-Line 365:
+Line 250:
- * New process to test for Gaussianity using swtest
 * Simulate recordings with specific properties, for stat validation
 * Quality control before statistics, on condition averages across subjects:<<BR>>mean(baseline)/std(baseline): shows bad subject quickly.
 * Use SurfStat: Impements interesting things, like an analytical  cluster-based p-value correction (Random-field theory which is used in  SPM) - Peter
+ * Multivariate stim-response analysis: https://github.com/mickcrosse/mTRF-Toolbox
-Line 372:
+Line 253:
- * '''XDF import''': Use the EEGLAB plugin, contact Martin Bleichner (Oldenburg)
 * Output .nii have incorrect sform/qform when using the options to downsample the volume of cut the empty slices
+ * 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
-Line 377:
+Line 274:
- * FieldTrip: Import/Export time-frequency:
  * Export: http://neuroimage.usc.edu/forums/t/export-time-frequency-to-fieldtrip/1968
  * Import: http://neuroimage.usc.edu/forums/t/import-time-frequency-data-from-fieldtrip/2644
 * 4D file format:
  * Use reader from MNE-Python: mne.io.read_raw_kit  (doesn't require 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
  * References at too far from the head sensors in Marseille 4D system
  * The noise compensation is considered to be always applied on the recordings, not sure this assumption is always correct
  * 4D phantom tutorial (JM Badier?)
 * EEG File formats:
  * EEG CeeGraph
  * EGI: Finish support for epoched files (formats 3,5,7)
+ * SPM .mat/.dat: Fix the import of the EEG/SEEG coordinates
 * EEG File formats:<<BR>>
-Line 395:
+Line 280:
-  * gTec EEG recordings: Read directly from the HDF5 files instead of the Matlab exports.
 * BCI2000 Input (via EEGLAB plugin)
 * EEGLAB import:
  * Support for binary AND epoched files (now it's one or the other)
  * Allow epoched files with recordings saved in external files
 * BST-BIN: Add compressionto .bst
 * Review raw on all the file formats (ASCII EEG and Cartool missing)
 * SPM .mat/.dat: Fix the import of the EEG/SEEG coordinates
 * Get acquisition date from files: Missing for 4D

== Distribution & documentation ==
 * Add tags to the forum posts for easier listing by topic
+  * 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
-Line 409:
+Line 323:
-  * Add review of literature for the resting state MEG
+  * Update the organization of derivatives folder (full FS folders)
-Line 413:
+Line 327:
-  * Rat PAC + high gamma (Soheila)
-Line 416:
+Line 329:
-  * FieldTrip cortico-muscular coherence tutorial: http://www.fieldtriptoolbox.org/tutorial/coherence
-Line 419:
+Line 331:
- * MEG steady-state / high-gamma visual / frequency tagging
 * BIDS-EEG example datasets
 * Stand-alone ICA tutorial

 * Move all the files to download on the cloud for faster download everywhere in the world
 * Provide secure way of sending password over HTTPS for:
  * Account creation
  * Forum exchanges
  * org.brainstorm.dialog.CloneControl
 * Workflows FieldTrip: http://www.fieldtriptoolbox.org/faq/what_types_of_datasets_and_their_respective_analyses_are_used_on_fieldtrip
 * Count GitHub clones in the the download stats
 * Google Analytics: Create template and update the section of the Community page
 * Deface the MRIs of all the tutorials
 * Compiled R2016b: Color picker doesn't work (for changing surface color for instance)
 * Clean up the wiki:
  * Remove all the wiki pages that are not used
  * Check all the links in all the pages
  * Check that all the TODO blocks have been properly handled
  * Remove useless images from all tutorials
  * Update page count on the main tutorials page
+  * 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 442:
+Line 336:
- * Screen capture:
  * Bug on Win8/Win10: doesn't capture the correct part of the screen
  * Window managers with fading effect: captures the top window
-Line 454:
+Line 345:
- * MacOS bugs:
  * Buttons {Yes,No,Cancel} listed backwards
  * Record tab: Text of epoch number is too big
  * Colormap menus: Do not work well on compiled MacOSX 10.9.5 and 10.10
 * Matlab bugs:
  * Interface looks small on screens with very high resolutions: Reduce the resolution
 * Event markers are not visible anymore with the sequence: Open MEG, open EOG, close MEG
 * in_bst_data_multi: If trials have different sizes, output is random (the one of the first file)
 * Edit scout in MRI: small modifications cause huge increase of the scout size
 * Canolty maps computation: Fix progress bar
+== 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 466:
+Line 357:
- * bst_bsxfun: After 2016b, we can use directly the scalar operators (./ .* ...) instead of bsxfun. Update bst_bsxfun to skip the use of bsxfun when possible.
+ * Replace all calls to inpolyhd.m with inpolyhedron.m (10x faster)
-Line 468:
+Line 359:
- * Hide Java panels instead of deleting them
-Line 471:
+Line 361:
- * bst_warp and channel_project: Use tess_parametrize_new instead of tess_parametrize
 * Shared kernels: "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
 * Fix all the 'todo' blocks in the code
 * Error message: Add a link to report directly the bug on the forum

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