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| A roadmap for the future developments of Brainstorm. == Next six months == Pre-processing * Functionnal connectivity == New interface elements == * MEG protocols: More flexible organization of the database; sub-conditions to allow different runs X different conditions. * |
A roadmap to the future developments of Brainstorm. <<TableOfContents(2,2)>> == 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)<<BR>>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: * 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) * Implement ft_artifact_threshold and ft_rejectartifact * 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/ |
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| * Make SSP projections dynamic, and keep the full list instead of always them combining them * Take the bad channels in account in the application of the SSP * Refresh display after changing the list of bad channels (imported files + raw) so the SSP are applied correctly * bst_selections: * Add user defined combinations of sensors (eg. "double banana" for EEG) * Use this to produce "inversed polarity" displayes too (useful in EEG) * Standard setups for al the EEG caps * Sources on surface: Display peak regions over time (time = color) => A.Gramfort * Homogenize a selection of several subjects/conditions * Popup menu when more than one study selected * Creation of a common channel file (match channels by names, not by order) * Register MEG runs (recompute fields for a different set of sensors, MEGCoregister from old brainstorm) * Images of amplitude: [sensor x time], [trial x time], scout: [trial x time] (similaire to erpimage in eeglab) * Simulation: synthesize pseudo data-files from a cortex patch (duration, amplitude, noise) * Interface to compute reaction times based on events: <<BR>>Input:selection of cue event + event response; Output: reation time trial by trial, average, std, distribution... => Etienne Labyt * Database navigator: F4 to switch to next sourcefile * Segmentation in microstates |
* 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 * {{attachment:connect_toolboxes.jpg}} * Connect NxN display: * Graph on sensors: does not place the sensors correctly in space * Display as image: Add legend of the elements along X and Y axis * Display as time series: Display warning before trying to open too many signals * Optimize display: use surface() instead of line() for links? (as in figure_3d/PlotFibers) * Time-resolved correlation/coherence: Display as time bands == 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:<<BR>>https://mne.tools/stable/auto_examples/inverse/plot_resolution_metrics.html#sphx-glr-auto-examples-inverse-plot-resolution-metrics-py * Change the graphic renderer from Matlab * Chronux toolbox : http://chronux.org/ * Add FieldTrip functions: * ft_sourceanalysis: * Check noise covariance * Check all the options of all the methods * Single trial reconstructions + noise covariance? * Filters?? http://www.fieldtriptoolbox.org/example/common_filters_in_beamforming * Beamformers: Save ftSource.avg.mom <<BR>>http://www.fieldtriptoolbox.org/workshop/meg-uk-2015/fieldtrip-beamformer-demo * http://www.natmeg.se/ft_beamformer/beamformer.html * http://www.fieldtriptoolbox.org/tutorial/beamformingextended * Baseline? Two inputs? * ft_prepare_heamodel: Add support from BEM surfaces from the Brainstorm database * Freqanalysis: ITC * ft_volumereslice: http://www.fieldtriptoolbox.org/faq/how_change_mri_orientation_size_fov * ft_freqanalysis * ft_combineplanar * Optimization: * Test speed for writing files: <<BR>>https://undocumentedmatlab.com/articles/improving-fwrite-performance * Use CUDA for speeding up some operations (filtering, wavelets, etc) * Use Matlab Coder to optimize: Wavelets, bandpass filter, sinusoid removal * Pipeline editor: * Bug: After "convert to continuous", the time of the following processes should change * Add loops over subjects/conditions/trial groups * Events: Allow selection from a drop-down list (similar to option "channelname" in panel_process_selection) * ITC: Inter-trial coherence (see MNE reports for group tutorial)<<BR>>http://www.sciencedirect.com/science/article/pii/S1053811916304232 * Remove line noise: http://www.nitrc.org/projects/cleanline * 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...) * Or keep existing tesselations for backward compatibility? * 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: <<BR>> * 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<<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 * 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:<<BR>>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 |
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| * Inverse: * Stable LCMV Beamformer * MUSIC * sLORETA: Values are now multiplied by 1e12 at loading for display => has do to be done in another way * Unconstrained sources: * Define as default * Check all the processes * Difference and stat should be: norm(A) - norm(B) * Overlapping spheres: improve the estimation of the spheres for the frontal lobes |
* 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 * 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: * 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 |
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| * Scouts 3D * Test volume sources with all the subsequent processes (timefreq, stat...) * Optimize: 3D display (better that 9x9 cubes) |
* Optimize: 3D display (better than 9x9 cubes) |
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| * Optimize: grid_interp_mri * Magnetic extrapolation: * Do the same thing with EEG * Optimize bst_extrapm.m, add waitbar * Use the noise covariance from the database instead of recomputing it * Project sources: * Adapt smooth factor to the number of vertices * Number of neighbors to consider = average number of neighbors in the target mesh. * Compute by small time blocks * Noise covariance matrix: * Save nAvg in noisecov file, to make it easier to scale to other recordings * When deploying to other conditions: Apply destination SSP (!NoiseCov = SSP . !NoiseCov . SSP' ) == Anatomy == * MRI import: auto-reorientation of MRI after selected NAS / LPA / RPA. * Major bug when importing surfaces for an MRI that was re-oriented manually * Finalize Brodmann scouts * Remove NCS/Talairach coordinate system, or fix it => Sylvain, Karim ND * Clustering cortex: Dimitrios, David, Yu-Teng == Processes == * Important new processes for a full processing pipleline: * Import, and segmentation of RAW files * Detect bad segments on RAW (then events in "bad" segments would be ignored) * Artifact detection: use other things than simple value thresholds (like variance of the sensors...) * Create events list based on thresholds on some channels (Stim, EOG, ECG...) => Etienne Labyt * Creation of SSP vectors (ex: Remove cardiac artifac) * ICA * Integration of Antoine Ducorps methods (everything in the doc of the dataHandler): * Cardiac artifact correction in MEG * PCA correction of ocular artifacts * Interpolation of missing EEG canal * Headmodel / sources / noise cov * Project sources * Delete intermediary files * Processing raw/continuous: * Process non-FIF files (need to convert the header) * Apply SSP + CTF Compensators(only if it useful - maybe create a specific process for that) * Other processes: * Bug: gradnorm crashes with bad channels * Spatial smoothing: check / document parameters * Sinusoid removal: fix new function * Time-frequency: * Write script for timefreq tutorial * Make much faster and more memory efficient (C functions coded by Matti ?) * Power spectrum: computation (FFT/welch, or average of TF) + display(f/Power, 2DLayout) * Display stat computed on time-frequency data * Display TF maps separately for the two gradiometers (if not: overlap) * Source reconstruction by frequency bands * Scouts on surface / time-freq * Process selection interface: * Bug when redimensioning window (with more than one process) * isAvgRef: warning quand process necessite des donnees en AVG REF en entree * Save "freqband" option when edited from custom processes * John's noise cancellation filters * Chain calls of similar processes (ex. bandpass+sin_remove), to avoid reading the full raw files several times |
* Display spectrum scouts (PSD plots when clicking on "Display scouts" on PSD/full cortex) |
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| * ANOVA: Use LENA functions | * Stat on unconstrained sources? * Stat/time series: Hide lines going down to zero (Dimitrios: https://neuroimage.usc.edu/forums/t/common-source-activation-across-subjects-and-conditions/1152/21) * Cluster stat: Add frequency selection option * ANOVA: * Write panel similar to Process1 and Process2 |
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| * Permutation tests: * t-test only (wilcoxon? sign-test?): paired, equal var, unequal var * nb permutations ~ 1000 * maximum statistic over "time" or "time and space" * Permutations / clustering: cf fieldtrip * http://fieldtrip.fcdonders.nl/tutorial/cluster_permutation_timelock * http://fieldtrip.fcdonders.nl/tutorial/cluster_permutation_freq * Threshold in time: keep only the regions that are significative for contiguous blocks of time, or over a certain number of time points<<BR>> => Process that creates a static representation of a temporal window == Display == * OpenGL options: {none, software, hardware} * Colormap: Set colormap max with right-click + move on the colorbar * Bug: Mixing 2 views MRI/3d, white cuts appear after !SetCurrentFigure * Bug: Scout without overlay, adapt scale for each graph when "Uniformize" option is unchecked (mixing sources + zscores) * Waitbars: * Replace old waitbars with java ones * Add a "Cancel" button on waitbars when the bounds are defined (ie. when bst controls the process) * Contact sheets & movies: use average of time windows instead of single instants, for each picture. == I/O == * EEG File formats: * Nihon Kohden * EDF+ * !BrainVision / !BrainAmp: Get functions from EEGLAB * EEG !CeeGraph * NEUROFILE = COHERENCE EEG/video !LongTerm Monitoring => Manfred Spueler * EGI: Finish support for epoched files (formats 3,5,7) * Other file formats * MEG160 (KIT) * CTF: * Read continuous RAW files split in several .meg4 files ( > 2 Go) * Read STIM channel and generate !MarkerFile * EEGLAB: Apply ICA matrices, get number of trials for AVG files * !FieldTrip structures: In / Out * Gzipped Nifti (new BrainVISA standard) * Analyze / Nifti:<<BR>> * Fix output function (output MRIs cannot be imported in SPM) * Use correctly field "orient" to align automatically MRI when importing * Define scouts from SPM / Analyze 3D masks * Files > 2Gb: display warnings == Programming details == * Double-click doesn't work well on some Linux workstations * Bug: Menu "Use default EEG cap" doesn't work for a multiple selection (setting the same EEG cap for several subjects) * Bug node selection: click on sources > TF: select node-source, not node-condition * Bug tree_dependencies: sources files, reprojected on default anatomy; If based on data files that are bad trials, they should be ignored by tree_dependencies, and they are not * bst_warp and channel_project: Use tess_parametrize_new instead of tess_parametrize * Testing functions: test_ctf "folder" / test_neuromag "folder" / test "folder" => Alex * Bug in_bst_data_multi: If trials have different sizes, output is random (the one of the first file)... * Shared kernels: do the "get bad channels" operation in a different way (reading all the files is too slow) * Rewrite all GUI functions with gui_component * Remove field "!BrainStormSubject" in the studies file: force same folder name for anat & data * Allow protocols with same folder for anat and data * Ensure that all the loaded and saved filenames are in "unix" format * Use parfor: When not available, replace directly all the "parfor" with "for" in file.m * Use Matlab GPU toolbox * Re-use panels instead of delete+create again * Optimize bst_read_events_track * Write shepards.m with new algorithm for nearest neighbors * Use tesselations_stat and tesselations_outwards to clean surfaces * Movies: Use JAVE (Java) * Screen captures: Use Yair Altman functions (in Matlab Central) == Distribution & documentation == * Compile stand-alone version: Linux, MacOS * Version with big fonts for live demos * Add Help buttons and menus (in popups, dialog windows...) => Links to the website. * Send email to registered users to anounce major improvements * Script tutorials: * Update them to reflect all the recent changes * Script for the time-frequency computation * Introduction tutorials: * Estimate time to complete each tutorial * Clusters * Anatomy: Segmentation with !FreeSurfer * First steps: Brainstorm preferences * Headmodel: explain the fields + how to get the constrained leadfield * Coordinate sytems: How to convert between the different coordinates systems in scripts * Sources: Modelized data * Sources: theshold min. size (not documented yet) * Scouts: Atlases of Tzourio-Mazoyer and Brodman * Processes: Describe all the processes * Processes: How to write your own processes (user folder for processes) * Processes: Processing RAW files * Import raw recordings: Add "detect bad trials/channels" in the pipeline * Advanced tutorials: * MNE sample dataset * EEG (How to import an EEG cap) * MRI segmentation with !FreeSurfer => David Wheland * How to make and compress a movie (Brainstorm + !VirtualDub + XVid) * Display the "What's new" page after downloading new version of brainstorm * Ask users to send their channel files, align on Colin, distribute == Unsolved problems == * Surfaces: * Influence of the software used to extract surfaces (!BrainVisa, !BrainSuite, !FreeSurfer) * Type of cortex surface to use: grey/white, grey/csf, midsurface ? * How to get good surfaces for BEM ? * Group analysis: * 1) localization on individual brain + interpolation on MNI brain ? * 2) localization directly on MNI brain ? * Normalize amplitudes across different subjects / runs ? * Online documentation of forward and inverse methods |
* 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: * 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 * Read associated empty room: * https://github.com/brainstorm-tools/brainstorm3/issues/138 * 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:<<BR>> * XLTEK: https://github.com/danielmhanover/OpenXLT * Persyst .lay: https://github.com/ieeg-portal/Persyst-Reader * Nervus .eeg: https://github.com/ieeg-portal/Nervus-Reader * Biopac .acq: https://github.com/ieeg-portal/Biopac-Reader * BCI2000 Input (via EEGLAB plugin) * 4D file format: * Use reader from MNE-Python: mne.io.read_raw_kit (skip Yokogawa slow library) * Reference gradiometers: Keep the orientation of the first or second coil? * Reference gradiometers: Add the sensor definition from coil_def.dat * Validate with phantom recordings that noise compensation is properly taken into account * The noise compensation is considered to be always applied on the recordings, not sure this assumption is always correct * 4D phantom tutorial (JM Badier?) * BST-BIN: Add compression to .bst * MINC MRI: Add support for "voxel to world" transformation (vox2ras) similarly to .nii == Distribution == * Java-free Matlab: All references of functions below must be removed * '''JavaFrame''': screencapture.m (used for screen captures of videos) * '''Actxcontrol''': Used for video-EEG * uihtml + JavaScript callbacks? * ActiveX in .NET app? * Pure Java framce + VLC java plugin? * Other video player? * '''Javacomponent''': * mri_editMask * figure_mri * process_bandpass * List .jar files used from Matlab distribution (e.g. dom) => Check all the import calls * Cleanup GitHub repository: * https://github.com/brainstorm-tools/brainstorm3/issues/473 * Remove ICBM152 default anatomy from repo * Move external I/O libraries as plugins: * mne-matlab * CEDS64ML * edfimport * eeprobe * son * ricoh * yokogawa * easyh5 == Documentation == * All tutorial datasets in BIDS (including introduction tutorials) * Deface the MRIs of all the tutorials * Count GitHub clones in the the download stats * MNE-Python 1.0: Test and update install documentation * Tutorial OMEGA/BIDS: * Update the organization of derivatives folder (full FS folders) * Download example datasets directly from the OMEGA repository * New tutorials: <<BR>> * Other public datasets: [[https://github.com/INCF/BIDS-examples/tree/bep008_meg|https://github.com/INCF/BIDS-examples/tree/bep008_meg/]] * EEG/research * FieldTrip ECOG tutorial: http://www.fieldtriptoolbox.org/tutorial/human_ecog * Reproduce tutorials from MNE-Python: https://martinos.org/mne/stable/tutorials.html * Cam-CAN database: https://camcan-archive.mrc-cbu.cam.ac.uk/dataaccess/<<BR>>(download new datasets, including maxfiltered files and manual fiducial placements) * MEG steady-state / high-gamma visual / frequency tagging * Reproduce results from "Simultaneous human intracerebral stimulation and HD-EEG, ground-truth for source localization methods": https://www.nature.com/articles/s41597-020-0467-x * Stand-alone ICA tutorial == 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) |
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?
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)
- Implement ft_artifact_threshold and ft_rejectartifact
- 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
- 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...)
- Or keep existing tesselations for backward compatibility?
- 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)