= What's next = A roadmap to the future developments of Brainstorm. <> == Recordings == * 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 * MEG/EEG registration: Apply the same transformation to multiple runs * Create heat maps: Maybe with matlab function heatmap? * BioSemi: Add menu "Convert naming system" to rename channels into 10-10 (A1=>FPz) * Simulations: https://github.com/lrkrol/SEREEGA * Integrate with EYE-EEG (Olaf Dimigen) * Reproduce tutorial: https://www.eyetracking-eeg.org/tutorial.html == Interface == * Add a warning when computing a forward model with > 100000 sources (check selection) * 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) * 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) * 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"}} == Connectivity == * 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) * 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 * Weighted Phase Lag Index (WPLI) * Coherence: Average cross-spectra instead of concatenating epochs (to avoid discontinuities)<
>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) == Processes == * 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) * Add MNE-Python functions: * scikit-learn classifiers * 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 * Add FieldTrip functions: * ft_sourceanalysis: * Check noise covariance * Check all the options of all the methods * Single trial reconstructions + noise covariance? * Filters?? http://www.fieldtriptoolbox.org/example/common_filters_in_beamforming * Beamformers: Save ftSource.avg.mom <
>http://www.fieldtriptoolbox.org/workshop/meg-uk-2015/fieldtrip-beamformer-demo * http://www.natmeg.se/ft_beamformer/beamformer.html * http://www.fieldtriptoolbox.org/tutorial/beamformingextended * Baseline? Two inputs? * ft_prepare_heamodel: Add support from BEM surfaces from the Brainstorm database * Freqanalysis: ITC * ft_volumereslice: http://www.fieldtriptoolbox.org/faq/how_change_mri_orientation_size_fov * ft_freqanalysis * ft_combineplanar * Optimization: * Use CUDA for speeding up some operations (filtering, wavelets, etc) * Use Matlab Coder to optimize: Wavelets, bandpass filter, sinusoid removal * Pipeline editor: * Bug: After "convert to continuous", the time of the following processes should change * Add loops over subjects/conditions/trial groups * Events: Allow selection from a drop-down list (similar to option "channelname" in panel_process_selection) * ITC: Inter-trial coherence (see MNE reports for group tutorial)<
>http://www.sciencedirect.com/science/article/pii/S1053811916304232 * 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: <
> http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0030135 * Dimension 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 * 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. == 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: * 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 * 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) == Anatomy == * 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: * Start BrainSuite * Start FreeSurfer * SimNIBS: Replace HEADRECO with CHARM (headreco will be removed in SimNIBS 4) * FastSurfer: https://deep-mi.org/research/fastsurfer/ * 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 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 * 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? * 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 * Templates for different ages: * 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/ * 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 == 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 == Statistics == * Stat on connectivity? * Stat on unconstrained sources? * 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: * 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 * 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: * XDF: https://github.com/sccn/xdf * 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 == Distribution & documentation == * All tutorial datasets in BIDS (including introduction tutorials) * Count GitHub clones in the the download stats * Deface the MRIs of all the tutorials * Tutorial OMEGA/BIDS: * Update the organization of derivatives folder (same for ECOG tutorial) * Add review of literature for the resting state MEG * Download example datasets directly from the OMEGA repository * New tutorials: <
> * 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/<
>(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) * 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 == 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/ == 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)