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|   * Update the organization of derivatives folder (same for ECOG tutorial) * Add review of literature for the resting state MEG  | 
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What's next
A roadmap to the future developments of Brainstorm.
Contents
Coregistration
Template channel file on a subject anatomy: Apply the MNI transform
- MEG/EEG registration: Apply the same transformation to multiple runs
 
Recordings
- Review signals in time-frequency space
 - 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
Project contact positions across subjects or templates (Marcel)
Right-click on channel file > Project on default anatomy- Display: 
- Bad channels: Contacts greyed out instead of ignored (Marcel)
 - Display time in H:M:S (useful for tutorial Epileptogenicity)
 - Display curved SEEG electrodes
 
 - 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
 
 - Automatic segmentation of CT: 
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?
 Detection CEEP stim artifacts: Use ImaGIN code ImaGIN_StimDetect
Pre-processing
- 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: 
- Exclude bad segments (Nathalie G)
 Add Alex's suggestions: https://neuroimage.usc.edu/forums/t/ica-on-very-long-eeg/23556/4
Automatic classification: ICLabel: https://neuroimage.usc.edu/forums/t/automatic-eeg-ic-ica-classification-for-brainstorm/33785
- Add methods: SOBI, Fastica, AMICA/CUDICA/CUDAAMICA (recommended by S Makeig)
 - 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
 - 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:
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0030135Dimension reduction with PCA adds artifacts: Not done by default in EEGLAB
Contact: Stephen Shall Jones ( shall-jones@infoscience.otago.ac.nz )
Student Carl Leichter detailed this in his thesis- Import ICA matrices available in EEGLAB .set files
 EEGLAB recommends ICA + trial rejection + ICA again: Impossible right now with Brainstorm
(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
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)
Connectivity
- Thresholding and stat tests for connectivity matrices: 
- Panel Display: Show only the top N% measures
 
 
 - 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
 - Sensitivity maps
 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-demohttp://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
 
- ft_sourceanalysis: 
 - 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/S1053811916304232Remove 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
- ICBM152 update: 
Move out default anatomy from GitHub repository:
Process with FreeSurfer 7.2 + add FS atlases (Brainnettome, Schaeffer, HCP...)
- Add volume atlases (+ reimport ASEG as volatlas)
 Add facemask => Use for defacing with any MNI registration
- Add T2?
 - Add contraleteral spheres
 
 - BEM surfaces: Deform fieldtrip BEM surfaces from ICBM152 to subject space with MNI coordinates?
 Simple-brain-plot: https://github.com/dutchconnectomelab/Simple-Brain-Plot
MRI segmentation:
- SimNIBS: Replace HEADRECO with CHARM (headreco will be removed in SimNIBS 4)
 
- MNI normalization: More options: 
- DARTEL / SHOOT
 BrainSuite (wait for Anand)
 - MRI Viewer: 
- 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 envelopeSurface>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://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/
 - Scouts: 
- Display edges in the middle of the faces instead of the vertices
 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
 Geodesic distance calculations:
https://www.mathworks.com/matlabcentral/fileexchange/6110-toolbox-fast-marching
Forward modeling
- DUNEuro/FEM: 
GeomtryAdapted: Buggy?
Display differences between leadfields: amplitude of difference (right-click > Compare)
 - 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
 Sensitivity maps: https://mne.tools/stable/auto_examples/forward/plot_forward_sensitivity_maps.html
- Point-spread and cross-talk functions (code in MNE-Python):
 - Dipoles: 
- Display dipoles in MRI viewer
 - Project individual dipoles files on a template
 - 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)
 
 - Display spectrum scouts (PSD plots when clicking on "Display scouts" on PSD/full cortex)
 
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: 
- Full support for iEEG and EEG
 - Read real fiducials (OMEGA) / transformation matrices:
 - Read associated empty room:
 
 - BIDS export: 
- Add events tsv, channel tsv, EEG, iEEG
 - BIDS-Matlab?
 
 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: 
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:
- 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/
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)
 
