= 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: * 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 * Bad trials: When changing the status of bad to good: remove the bad segments as well, otherwise it is not processed by processes like the PSD. * Review clinical recordings: Reduce the dimensionality of the data with a simple inverse problem, similar to what we do for the magnetic extrapolation ("Regional sources" in BESA, cf S Rampp) * 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) == 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) * Smooth display from figure_image (ERPimage, raster plot...) * 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 * Use boundary() instead of conhull() in all the display functions (ie. 2DDisc) * 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 the 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) * Display of connectivity graphs: * Display as straight lines * Recode 2D graphs * 3D display with anatomical constrains * Display using real position of EEG electrodes * Use new band-pass filters in bst_connectivity ('bst-hfilter' instead of 'bst-fft-fir') * Matrix view of NxN graphs: Add legend of the elements along X and Y axis * Weighted Phase Lag Index (WPLI) * Graph view: * Does not display negative values correctly (correlation or difference of coherence) * Re-write using pure Matlab code and smoothed graphics * Fixed scales for intensity sliders * Text bigger * Too much data in appdata * Fixed scales for intensity sliders * Add "=" shortcut for having graphs with similar configurations * Disable zoom in one region (serious bugs) * NxN on sensors: does not place the sensors correctly in space * 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: * Add p-values * Remove evoked * Optimize code * Add time integration * Unconstrained sources * Add warning when running of short windows (because of filters) * Time-resolved correlation/coherence: Display as time bands * Tutorial coherence [1xN] : Reproduce FieldTrip results? * Connect NxN: Display as time series > Display warning before trying to open too many signals == Processes == * Decoding/Classifiers: Implement Dimitrios and scikit-learn algorithms * Allow processes in Python and Java * Add MNE-Python functions: * scikit-learn classifiers * 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_sourcemodel: Compute MNI transformation (linear and non-linear) => Peter * ft_prepare_heamodel: Add support from BEM surfaces from the Brainstorm database * Freqanalysis: ITC * ft_read_atlas('TTatlas+tlrc.BRICK'); * 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) * When computing sources from the pipeline editor: doesn't reselect the options if you click twice on "edit" (works for minnorm, but not for lcmv) * ITC: Inter-trial coherence (see MNE reports for group tutorial)<
>http://www.sciencedirect.com/science/article/pii/S1053811916304232 * ICA: * 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 * Use faster methods (MNE-Python?) * 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 * S Makeig: Use ICA to select the IC of interest instead of only removing artifacts * Display of spectrum for components (PSD/FFT) * 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/ * Other EEGLAB functions: * Step function detection: https://github.com/lucklab/erplab/wiki/Artifact-Detection:-Tutorial * SSP: * Display warning if changing the ChannelFlag while there is a Projector applied * Spectral flattening (John): * ARIMA(5,0,1): Apply on the signal before any frequency/connectivity/PAC analysis * PSD: * Rewrite to have the same input as coherence (frequency resolution instead of window length) * Allow display of Avg+StdErr * 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 * Matching pursuit: http://m.jneurosci.org/content/36/12/3399.abstract?etoc * Bug: Display logs as negative * Bug: 3D figures: Colormaps with "log" option doesn't work * Bug: Difference of power displayed in log: problems (Soheila) * 2D Layout in spectrum * Make much faster and more memory efficient (C functions coded by Matti ?) * TF scouts: should display average of TF maps * Impossible to keep complex values for unconstrained sources * Pad short epochs with zero values for getting lower frequencies * 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. * Extend clusters tab to display of TF to overlay TF signals (Svet) * When normalizing with baseline: Propagate with the edge effects marked in TFmask * Allow baseline normalization of files computed with time bands * 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. * Artifact detection: * Artifact rejection like SPM: if bad in 20%, bad everywhere * Test difference between adjacent samples * Events detection: Add option "std" vs "amplitude" * Simulation: * EEGSourceSim: https://www.sciencedirect.com/science/article/pii/S0165027019302341 * Use field process field "Group" to separate Input/Processing/Output options * Use new Matlab functions: movmean, movsum, movmedian, movmax, movmin, movvar, movstd == Database == * MEG protocols: More flexible organization of the database; sub-conditions to allow different runs X different conditions. * Matrix files: Allow to be dependent from other files * Rename multiple files * Default headmodel lost when reloaded: Keep selection on the hard drive (in brainstormstudy.mat) * Auto-save: * protocol.mat can be too big: do not store the results links in it (and recreate when loading)- http://neuroimage.usc.edu/forums/t/abnormally-slow-behavior/2065/10 * Improve auto-save: add tracking file next to protocol.mat, do not save all the time, only when closing app, and reload protocol at stratup if tracking file is still there == 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/ == Source modeling == * Unconstrained to flat: Default PCA for stat and connectivity? * Sensitivity maps: https://mne.tools/stable/auto_examples/forward/plot_forward_sensitivity_maps.html * 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 * Use 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 * 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 (algorithm to fit surfaces should be imrpoved) * Menu head model > Copy to other conditions/subjects (check if applicable first) * Menu Sources > Maximum value: Doesn't work with volume or mixed head models * Mixed head models: * Set loose parameter from the interface * Bug when displaying interpolated in MRI viewer * Volume grid: * Optimize: 3D display (better than 9x9 cubes) * Optimize: vol_dilate (with 26 neighbors) * Menu Sources > Simulate recordings: * Do not close the 3D figures after generating a new file * Add a process equivalent to this menu * Panel Get coordinates: Add button "find maximum" * BEM single sphere: Get implementation from MNE * Unconstrained sources: * Stat and connectivity: what to do? (re-send email John+Sylvain) * Sources on surface: Display peak regions over time (time = color) => A.Gramfort * Process "Extract scouts time series": Add PCA option (replace isnorm with choice PCA/Norm) * Add eyes models to attract eye activity == Anatomy == * Keep ASEG volume + display region name in MRI viewer * '''SimNIBS''': Replace HEADRECO with CHARM (headreco will be removed in SimNIBS 4) * Infant templates: Add electrodes positions (at least 10-10) * Multi-Scale Brain Parcellator (Lausanne2008): * [[https://github.com/sebastientourbier/multiscalebrainparcellatorhttps://hub.docker.com/r/sebastientourbier/multiscalebrainparcellator|https://github.com/sebastientourbier/multiscalebrainparcellator]] * [[https://github.com/sebastientourbier/multiscalebrainparcellatorhttps://hub.docker.com/r/sebastientourbier/multiscalebrainparcellator|https://hub.docker.com/r/sebastientourbier/multiscalebrainparcellator]] * https://multiscalebrainparcellator.readthedocs.io/en/latest/ * MNI transformation: Use SPM non-linear MNI transformation y_... * Registration: * Getting electrode positions from 3D scanners: https://sccn.ucsd.edu/wiki/Get_chanlocs * GARDEL: http://meg.univ-amu.fr/wiki/GARDEL:presentation * Use the same registration for multiple recording sessions that have already re-registered previously (eg. with MaxFilter) * When linking multiple EEG recordings including 3D positions, do the registration only once and copy it to all the runs * Compute non-linear MNI registration instead of linear * Select and remove bad digitized head points before automatic coregistration * Load the MNE -transf.fif: http://neuroimage.usc.edu/forums/showthread.php?2830 * 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 * Edit fiducials: Replace 6 text boxes with 1 for easy copy-paste (see fiducials.m) * Optimize computation interpolation MRI-surface (tess_tri_interp) => spm_mesh_to_grid * BrainSuite: * Add new labels to all BrainSuite anatomy templates * Use same colors for left and right for anatomical atlases * Use for volume coregistration (rigid / non-rigid) * USCBrain: Add default electrodes positions * Lists on lead-dbs website: * https://www.lead-dbs.org/helpsupport/knowledge-base/atlasesresources/atlases/ * https://www.lead-dbs.org/helpsupport/knowledge-base/atlasesresources/cortical-atlas-parcellations-mni-space/ * FEM 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 * Scouts: * Display edges in the middle of the faces instead of the vertices * Display scouts in a tree: hemisphere, region, subregion * Sort scouts by region in process options * Downsample to atlas: allow on timefreq/connect files * 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 * Major bug when importing surfaces for an MRI that was re-oriented manually * Surface>Volume interpolation: Use spm_mesh_to_grid * Bug: Hide scouts in the preview of the grid for volume head models * Geodesic distance calculations:<
>https://www.mathworks.com/matlabcentral/fileexchange/6110-toolbox-fast-marching == ECOG/SEEG == * Electrodes models: Import / export * Contact positions: Import / set / detect * New option: Align on none|inner|cortex to replace ECOG-mid * Add history: Save modifications and transformations applied to the channel files (Marcel) * Project contact positions across subjects or templates (Marcel) * Add menu to import implantation channel file in imported recordings * SEEG/ECOG: Identify contacts in resected areas / identify ROIs for each contact * SEEG/ECOG: Identify contacts in a give 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 * Arnulfo: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-015-0511-6 * MAP07 / SPM: https://www.epi.ch/_files/Artikel_Epileptologie/Huppertz_2_13.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 * Export list of contacts with a probability of anatomical regions from various atlases: https://neuroimage.usc.edu/forums/t/seeg-contacts-anatomical-location/14756 * Detection CEEP stim artifacts: Use ImaGIN code ImaGIN_StimDetect == Statistics == * ANOVA: * Which functions to use? * Write panel similar to Process1 and Process2 to allow the * 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 * Quality control before statistics, on condition averages across subjects:<
>mean(baseline)/std(baseline): shows bad subject quickly. * Use SurfStat: Impements interesting things, like an analytical cluster-based p-value correction (Random-field theory which is used in SPM) - Peter * Export to R or SPSS for advanced stat == Input / output == * Bug import multiple files: use same "time" for all files * BIDS import: * Read real fiducials (OMEGA) * Read associated empty room * Test all the BIDS examples * BIDS Export: * Add events tsv, channel tsv, EEG, iEEG * '''XDF import''': Use FieldTRip or the EEGLAB plugin, contact Martin Bleichner (Oldenburg)<
>https://github.com/sccn/xdf/blob/master/xdf_sample.xdf * DICOM converter: * Add dcm2nii (MRICron) * Add MRIConvert * FieldTrip: Import/Export time-frequency: * Export: http://neuroimage.usc.edu/forums/t/export-time-frequency-to-fieldtrip/1968 * Import: http://neuroimage.usc.edu/forums/t/import-time-frequency-data-from-fieldtrip/2644 * 4D file format: * Use reader from MNE-Python: mne.io.read_raw_kit (doesn't require 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?) * EEG File formats: * EEG CeeGraph * EGI: Finish support for epoched files (formats 3,5,7) * 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 * gTec EEG recordings: Read directly from the HDF5 files instead of the Matlab exports. * BCI2000 Input (via EEGLAB plugin) * BST-BIN: Add compression to .bst * Review raw on all the file formats (ASCII EEG and Cartool missing) * SPM .mat/.dat: Fix the import of the EEG/SEEG coordinates * Get acquisition date from files: Missing for 4D * Support for OpenJData / JNIfTI: https://github.com/brainstorm-tools/brainstorm3/issues/284 == Distribution & documentation == * 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 * Tutorial iEEG: * Rename _coordsystem/_electrodes => space_other * 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 * FieldTrip cortico-muscular coherence tutorial: http://www.fieldtriptoolbox.org/tutorial/coherence * 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 * BIDS-EEG example datasets * 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 * Move all the files to download to the cloud for faster download everywhere in the world * Provide secure way of sending password over HTTPS for: * Account creation * Forum exchanges * org.brainstorm.dialog.CloneControl * Workflows FieldTrip: http://www.fieldtriptoolbox.org/faq/what_types_of_datasets_and_their_respective_analyses_are_used_on_fieldtrip * Count GitHub clones in the the download stats * Deface the MRIs of all the tutorials * Clean up the wiki: * Remove all the wiki pages that are not used * Check all the links in all the pages * Check that all the TODO blocks have been properly handled * Remove useless images from all tutorials * Update page count on the main tutorials page == Current bugs == * MacOS 10.14.5 (Mojave): * Toggle buttons do not show their status * Panel Record: Text is too large for text boxes * 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 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 * Canolty maps computation: Fix progress bar == Geeky programming details == * Replace all calls to inpolyhd.m with inpolyhedron.m * bst_bsxfun: After 2016b, we can use directly the scalar operators (./ .* ...) instead of bsxfun. Update bst_bsxfun to skip the use of bsxfun when possible. * 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) * Hide Java panels instead of deleting them * Processes with "radio" and "radio_line" options: Replace with "radio_label" and "radio_linelabel" * Interpolations: Use scatteredInterpolant, griddedInterpolant, triangulation.nearestNeighbor (2014b) * bst_warp and channel_project: Use tess_parametrize_new instead of tess_parametrize * Shared kernels: "get bad channels" operation in a different way (reading all the files is too slow) * Optimize bst_get: * Now study and subject have necessarily the same folder name * Replace big switch with separate functions * Fix all the 'todo' blocks in the code