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* 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 |
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* MEG/EEG registration: Apply the same transformation to multiple runs * Create heat maps: Maybe with matlab function heatmap? |
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* Simulations: https://github.com/lrkrol/SEREEGA == ECOG/SEEG == * 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 * 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 |
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* 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 * Global colormap max: Should get the maximum across all the open files * Copy figures to clipboard (with the screencapture function) |
* 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) |
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* Display CTF coils: Show discs instead of squares * Progress bar: Add a "Cancel" button * Error message: Add a link to report directly the bug on the forum * Reorganize menus (Dannie's suggestion): {{attachment:dannie_menus.png||width="382",height="237"}} |
== Database == * Save iHeadModel somewhere in the datbase structure * Generalize the use of the units (field .DisplayUnits): Save in source files |
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* Thresholding and stat tests for 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) |
* 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}} |
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* Weighted Phase Lag Index (WPLI) * Coherence: Average cross-spectra instead of concatenating epochs (to avoid discontinuities)<<BR>>Explore inter-trial approaches (Esther refers to chronux toolbox) * Granger: Check for minimum time window (Esther: min around 500-1000 data points) * PLV: * Remove evoked * Add time integration * Unconstrained sources * Add warning when running of short windows (because of filters) |
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* Plugin manager: * Export all the software environment to a .zip file (brainstorm + all plugins) * Generate fully reproducible scripts, including all the interactive/graphical parts: * Saving all the interactive operations as process calls * Improving the pipeline editor to handle loops over data files or subjects * Keeping a better track of the provenance of all the data (History, uniform file names) |
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* https://neuroimage.usc.edu/forums/t/ica-on-very-long-eeg/23556/4 | * BEM single layer (John wants to test it) * ICA: https://neuroimage.usc.edu/forums/t/ica-on-very-long-eeg/23556/4 |
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* Chronux toolbox : http://chronux.org/ | |
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* Test speed for writing files: <<BR>>https://undocumentedmatlab.com/articles/improving-fwrite-performance | |
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* ICA: * Add Alex's suggestions: https://neuroimage.usc.edu/forums/t/ica-on-very-long-eeg/23556/4 * 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: <<BR>> http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0030135 * 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 * 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 * 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 |
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== Source modeling == * Unconstrained sources: * Unconstrained to flat: Default PCA for stat and connectivity? * Process "Scouts time series": Add PCA option (replace isnorm with radio PCA/Norm) * 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 * "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 * Sensitivity maps: https://mne.tools/stable/auto_examples/forward/plot_forward_sensitivity_maps.html * 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: * 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 * Mixed head models: Bug when displaying interpolated in MRI viewer * 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 * BEM single sphere: Get implementation from MNE * Volume grid: * Optimize: 3D display (better than 9x9 cubes) * Optimize: vol_dilate (with 26 neighbors) * Add eyes models to attract eye activity * Display spectrum scouts (PSD plots when clicking on "Display scouts" on PSD/full cortex) |
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* MRI segmentation: * Start BrainSuite * Start FreeSurfer |
* ICBM152 update: * Replace in main distribution * Move out default anatomy from GitHub repository * 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: <<BR>> |
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* FastSurfer: https://deep-mi.org/research/fastsurfer/ | |
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* Defacing: * https://afni.nimh.nih.gov/pub/dist/doc/htmldoc/tutorials/refacer/refacer_run.html * Removing MNI face mask using MNI coordinates |
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* ICBM152 update: * Process with FreeSurfer 7.1 + add FS atlases (Brainnettome, Schaeffer, HCP...) * Add volume atlases (+ reimport ASEG as volatlas) * Add facemask => Use for defacing with any MNI registration * Add T2? |
* Bug import anatomy: Requested nVert > high-resolution cortex surface: Creates an empty cortex_0V |
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* Brain2mesh: Add import of 10-10 positions | |
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* MNI: https://www.bic.mni.mcgill.ca/ServicesAtlases/NIHPD-obj1 | |
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* https://openneuro.org/datasets/ds000256/versions/00002 * https://osf.io/axz5r/ |
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* 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) | |
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== ECOG/SEEG == * Contact positions: Import / set / detect * New option: Align on none|inner|cortex to replace ECOG-mid * Project contact positions across subjects or templates (Marcel) * 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: * 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) * Display: * Bad channels: Contacts greyed out instead of ignored (Marcel) * Display time in H:M:S * Display curved SEEG electrodes * Detection CEEP stim artifacts: Use ImaGIN code ImaGIN_StimDetect |
* 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: * 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 * 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) |
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* Stat on connectivity? | |
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* 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 |
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* Multivariate stim-response analysis: https://github.com/mickcrosse/mTRF-Toolbox | |
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* Full support for iEEG and EEG | |
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* Read associated empty room | * https://github.com/brainstorm-tools/brainstorm3/issues/139 |
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* EEG File formats: * XDF: https://github.com/sccn/xdf |
* EEG File formats:<<BR>> |
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== Distribution & documentation == |
* 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 == |
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* Deface the MRIs of all the tutorials | |
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* Deface the MRIs of all the tutorials | * MNE-Python 1.0: Test and update install documentation |
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* Update the organization of derivatives folder (same for ECOG tutorial) * Add review of literature for the resting state MEG |
* Update the organization of derivatives folder (full FS folders) |
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* MacOS 10.14.5 (Mojave): * Toggle buttons do not show their status * Panel Record: Text is too large for text boxes * 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 |
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* Google: https://www.youtube.com/watch?v=LLMXV3o2FT0 * https://edu.google.com/why-google/case-studies/unc-chapel-hill-gcp/ |
What's next
A roadmap to the future developments of Brainstorm.
Contents
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:
- 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
- Group analysis: extract clusters across subjects, display or average signals (see MIA)
- Spike detection:
- 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?
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
- 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-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:
- Replace in main distribution
Move out default anatomy from GitHub repository
- 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
- 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:
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
- Point-spread and cross-talk functions (code in MNE-Python):
- 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:
- Full support for iEEG and EEG
- Read real fiducials (OMEGA) / transformation matrices:
- 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)