= What's next = A roadmap to the future developments of Brainstorm. <> == 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 * Sleep scoring wish list (Emily C): * Configurable horizontal lines (for helping detecting visually some thresholds) * Mouse ruler: Measure 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 (Low priority) :<
> * Consider to change to a format that is faster to read * Add parameter to make the visual downsampling more or less aggressive * Keep the filter specifications in memory instead of recomputing for every page<
>(Nice to have) * BioSemi: Add menu "Convert naming system" to rename channels into 10-10 (A1=>FPz) * Simulations: https://github.com/lrkrol/SEREEGA(Low priority) == ECOG/SEEG == * https://www.sciencedirect.com/science/article/pii/S1053811922005559 * Display (high-priority)(Part SEEG grant): * Group display: Overlay multiple channel files in the same figure, coloring contacts by subject/ROI/Cluster/Electrode name * https://neuroimage.usc.edu/forums/t/37617 * iEEG tab must be read-only when multiple files (hide configuration controls) * Bad channels: Contacts greyed out instead of ignored (Marcel H, Germany)<
>(To diff between band and not-recorded) > Rendering of SEEG electrodes: Full surface modelling with surface mesh (see Lead-DBS models + code that generates them?) * Display time in H:M:S instead of S > If there is t0 in H:M:S instead of S > As an option in Display configuration button>x-axis * view_leadfield_sensitivity: Add closing surfaces at cortex limits * Create clusters from anatomical labels (Anne So) : * 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> As a process to select recordings, then Scouts from Volumen Atlas, Create cluster in channel file, then Extract time series. * Group analysis: extract clusters across subjects, display or average signals (see MIA) (Anne So) * Spike detection (Need to check for current toolboxes from scratch)(contact Nicolas R)(Mosher J)(iEEG BIDS): * 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<
>https://neuroimage.usc.edu/forums/t/automatic-localization-of-seeg-electrodes/36302/7 * GARDEL: http://meg.univ-amu.fr/wiki/GARDEL:presentation * Discussed with Samuel and Christian (ins-amu.fr) * 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 Range of values is way diff than ones from MRI. Current color maps are not suitable for CT, need to be improved.Together with processing of CT to get electrode positions. * Detection CCEP stim artifacts: Use ImaGIN code ImaGIN_StimDetect https://f-tract.eu/software/imagin/ == 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 * Use it to guide ICA: http://www2.hu-berlin.de/eyetracking-eeg/ * 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 * Spectral representation of ICs * SSP: * Display warning if changing the ChannelFlag while there is a Projector applied * File format: * Add support to read GDF file format https://github.com/donnchadh/biosig/blob/master/biosig/t200_FileAccess/sload.m * <
> * == 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 * Better provenance: History fields, uniform file names... == 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) * 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 == * Define names and unit labels for each connectivity metric * Null models: (Bratislav M) https://www.nature.com/articles/s41583-022-00601-9 * {{attachment:connect_toolboxes.jpg}} * Connect NxN display: * Graph on sensors: Place M/EEG sensors by location, not by channel order * 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 (as done in wavelet, to have same time axis as data) == Processes == * Add MNE-Python functions: * scikit-learn classifiers * BEM single layer (John wants to test it) * https://neuroimage.usc.edu/forums/t/best-way-to-export-to-mne-python/12704/3 * Reproduce tutorials / examples from FieldTrip and MNE-Python: * FieldTrip ECOG tutorial: http://www.fieldtriptoolbox.org/tutorial/human_ecog * Reproduce tutorials from MNE-Python: https://martinos.org/mne/stable/tutorials.html * Spatial resolution metrics in source space:<
>https://mne.tools/stable/auto_examples/inverse/plot_resolution_metrics.html#sphx-glr-auto-examples-inverse-plot-resolution-metrics-py * Change the graphic renderer from Matlab * Chronux toolbox : http://chronux.org/ * Add FieldTrip functions: * ft_sourceanalysis: * Check noise covariance * Check all the options of all the methods * Single trial reconstructions + noise covariance? * Filters?? http://www.fieldtriptoolbox.org/example/common_filters_in_beamforming * Beamformers: Save ftSource.avg.mom <
>http://www.fieldtriptoolbox.org/workshop/meg-uk-2015/fieldtrip-beamformer-demo * http://www.natmeg.se/ft_beamformer/beamformer.html * http://www.fieldtriptoolbox.org/tutorial/beamformingextended * Baseline? Two inputs? * ft_prepare_heamodel: Add support from BEM surfaces from the Brainstorm database * 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 * 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 * 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. * requested feature from the forum: * * https://neuroimage.usc.edu/forums/t/event-export-and-process-find-maximum-value-amplitude/41911/2 * * https://neuroimage.usc.edu/forums/t/custom-process-that-involves-merging-of-channels/40638 * * https://neuroimage.usc.edu/forums/t/swloreta-for-source-localization/41882/4 == Anatomy == * Display parcellation values (matrices) in 3D and 2D. * https://github.com/dutchconnectomelab/Simple-Brain-Plot * Scouts * Import SimNIBS4: Use final_tissues_LUT.txt instead of fixed list of tissues: https://neuroimage.usc.edu/forums/t/removing-a-lesioned-area/38414/20 * Simple-brain-plot: https://github.com/dutchconnectomelab/Simple-Brain-Plot * MNI normalization: More options: * DARTEL / SHOOT * BrainSuite (wait for Anand) * Import from SimNIBS (Conform2MNI_nonl.nii.gz, MNI2Conform_nonl.nii.gz) * MRI Viewer: * Adjust CT contrast better: https://neuroimage.usc.edu/forums/t/automatic-localization-of-seeg-electrodes/36302/10 * Pan in zoomed view (shift + click + move?) * Zoom in/out with mouse (shift + scroll?) * Ruler tool to measure distances * Display scouts as additional volumes * Render surface envelope in the MRI as a thin line instead of the full interpolation matrix<
>Or use inpolyhedron to get a surface mask and then erode it to get the volume envelope * Surface>Volume interpolation: Use '''spm_mesh_to_grid''' instead of tess_tri_interp * Defacing: * https://afni.nimh.nih.gov/pub/dist/doc/htmldoc/tutorials/refacer/refacer_run.html * Removing MNI face mask using MNI coordinates (mask available ICMB152 2023b) * Bug import anatomy: Requested nVert > high-resolution cortex surface: Creates an empty cortex_0V * BrainSuite: * Use same colors for left and right for anatomical atlases * Use for volume coregistration (rigid / non-rigid) * USCBrain: Add default electrodes positions * Remove BrainSuite1 when not needed anymore * Brain2mesh: Add import of 10-10 positions * Templates for different ages: * MNI: https://www.bic.mni.mcgill.ca/ServicesAtlases/NIHPD-obj1 * Pediatric head atlases: https://www.pedeheadmod.net/pediatric-head-atlases-v1-2/ * https://iopscience.iop.org/article/10.1088/2057-1976/ab4c76 * https://www.biorxiv.org/content/biorxiv/early/2020/02/09/2020.02.07.939447.full.pdf * John Richards: https://www.nitrc.org/frs/?group_id=1361 * Neurodev database: https://jerlab.sc.edu/projects/neurodevelopmental-mri-database/ * https://openneuro.org/datasets/ds000256/versions/00002 * https://osf.io/axz5r/ * Scouts: * Display edges in the middle of the faces instead of the vertices * Parcellating volume grids: scikit-learn.cluster.Ward * Geodesic distance calculations:<
>https://www.mathworks.com/matlabcentral/fileexchange/6110-toolbox-fast-marching * Improving the registration between EEG and anatomy templates: * Warping: Improve the basic alignment of the digitized electrodes on the templat, possibly with Cz and other anatomical landmarks * EEG template positions: rework using a standardized Cz position (+ other landmarks) == Forward modeling == * DUNEuro/FEM: * Add lesion mask to SimNIBS: https://simnibs.github.io/simnibs/build/html/documentation/command_line/add_tissues_to_upsampled.html#add-tissues-to-upsampled-doc * GeomtryAdapted: Buggy? * Display differences between leadfields: amplitude of difference (right-click > Compare) * Display sensitivity on FEM surface * OpenMEEG: Detect bad results + exclude from leadfield * BEM single sphere: Get implementation from MNE-Python (John Mosher) * Add eyes models to attract eye activity (Put a dipole in each eye) == 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 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 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 (SOLVED?) * 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 3x3 cubes) * Optimize: vol_dilate (with 26 neighbors) == Statistics == * Stat on unconstrained sources? * Stat/time series: Hide lines going down to zero (Dimitrios: https://neuroimage.usc.edu/forums/t/common-source-activation-across-subjects-and-conditions/1152/21) * Cluster stat: Add frequency selection option * ANOVA: * Write panel similar to Process1 and Process2 * Output = 1 file per effect, all grouped in a node "ANOVA" * Display several ANOVA maps (from several files) on one single figure, using a "graphic accumulator", towards which one can send any type of graphic object * Multivariate stim-response analysis: https://github.com/mickcrosse/mTRF-Toolbox == Input / output == * BIDS import: * Add option to process to specify the protocol name * Disable logging of sub-processes (reloading the previous report should only show process_import_bids) * 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 * Use BIDS-Matlab? * Test datasets: * See list of test datasets in process_import_bids.m * ds004085 / ds004473: Check response epoch + BUG with coordinate interpretation * BIDS export: * EEG, iEEG: Add events.tsv, channel.tsv, electrodes.tsv * Anatomy: Add t1w.json (including fiducials) * Use BIDS-Matlab? * EDF+ reader: Add resampling of channels with different sampling rates * Support for OpenJData / JNIfTI: https://github.com/brainstorm-tools/brainstorm3/issues/284 * DICOM converter: * Add dcm2nii (MRICron) * Add MRIConvert * SPM .mat/.dat: Fix the import of the EEG/SEEG coordinates * EEG File formats:<
> * XLTEK: https://github.com/danielmhanover/OpenXLT * Persyst .lay: https://github.com/ieeg-portal/Persyst-Reader * Nervus .eeg: https://github.com/ieeg-portal/Nervus-Reader * Biopac .acq: https://github.com/ieeg-portal/Biopac-Reader * BCI2000 Input (via EEGLAB plugin) * 4D file format: * Use reader from MNE-Python: mne.io.read_raw_kit (skip Yokogawa slow library) * Reference gradiometers: Keep the orientation of the first or second coil? * Reference gradiometers: Add the sensor definition from coil_def.dat * Validate with phantom recordings that noise compensation is properly taken into account * The noise compensation is considered to be always applied on the recordings, not sure this assumption is always correct * 4D phantom tutorial (JM Badier?) * BST-BIN: Add compression to .bst * MINC MRI: Add support for "voxel to world" transformation (vox2ras) similarly to .nii == Distribution == * Java-free Matlab: All references of functions below must be removed * '''JavaFrame''': screencapture.m (used for screen captures of videos) * '''Actxcontrol''': Used for video-EEG * uihtml + JavaScript callbacks? * ActiveX in .NET app? * Pure Java framce + VLC java plugin? * Other video player? * '''Javacomponent''': * mri_editMask * figure_mri * process_bandpass * List .jar files used from Matlab distribution (e.g. dom) => Check all the import calls * Cleanup GitHub repository: * https://github.com/brainstorm-tools/brainstorm3/issues/473 * Move external I/O libraries as plugins: * mne-matlab * CEDS64ML * edfimport * eeprobe * son * ricoh * yokogawa == 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|https://github.com/INCF/BIDS-examples/tree/bep008_meg/]] * EEG/research * 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 (SOLVED?) * Focus requests change workspace when processing constantly (Linux systems) (SOLVED?) == 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"