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== Current topics == ==== Source modeling ==== * Implementation of a new unified minimum norm/beamformer framework (almost finished) ==== Documentation ==== * Cross-validation with MNE and FieldTrip (work in progress): <<BR>>http://martinos.org/mne/dev/auto_tutorials/plot_brainstorm_auditory.html * New tutorial: MEG resting-state / OMEGA database ==== Functional connectivity ==== * Significance thresholding of the connectivity matrices (not started) ==== Computation ==== * Move the code to GitHub (not started) * Removing the dependence to the Java interface to run in headless mode (not started) * Call MNE and FieldTrip functions from Brainstorm GUI (work in progress) <<BR>><<BR>> |
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* RAW file viewer: * '''Faster display''': Downsample time series before plotting * Pre-load next page of recordings * Keep the filter specifications in memory instead of recomputing for every page * Add field "comment" to markers: For clinicians to add notes (Marcel) * Events: Change the category of a selected event easily, instead of deleting/marking new * Events: Advanced process for recombining.<<BR>>Example: http://www.erpinfo.org/erplab/erplab-documentation/manual/Binlister.html * 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 * 2DLayout: * Overlay multiple conditions * Does not work when DC offset is not removed |
* 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) :<<BR>> * 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<<BR>>(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)<<BR>>(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<<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 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 * Add note when rejecting trials: https://neuroimage.usc.edu/forums/t/33686 * ICA: <<BR>> * Automatic classification: ICLabel: https://neuroimage.usc.edu/forums/t/automatic-eeg-ic-ica-classification-for-brainstorm/33785 * Exploration: Add window with spectral decomposition (useful for muscle artifacts) * Export IC time series (and then compute their spectrum): solves the problem above * Import ICA matrices available in EEGLAB .set files * ICA+machine learning: https://www.ncbi.nlm.nih.gov/pubmed/28497769 * Automated artifact rejection: https://arxiv.org/abs/1612.08194 * Use EYE-EEG: EEGLAB toolbox for eye-tracker guided ICA (Olaf Dimigen): http://www2.hu-berlin.de/eyetracking-eeg/ * SSP: * Display warning if changing the ChannelFlag while there is a Projector applied * File format: * Add support to read GDF file format https://github.com/donnchadh/biosig/blob/master/biosig/t200_FileAccess/sload.m * <<BR>> * == Reproducibility toolbox == * Generate fully reproducible scripts, including all the interactive/graphical parts * Record all GUI actions as script calls * Import window: Add button to create the corresponding processing pipeline (to generate script or to edit additional options) * Adding the list of plugins to the reports (optionnal or foldable) * Better provenance: History fields, uniform file names... * Improving the pipeline editor to handle loops over data files or subjects |
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* Start Brainstorm without Java (-nodesktop) * Move code to github (or https://www.dominodatalab.com ?) * Option to increase the size of all the elements of the interface (for high res laptop screens) * Allow FieldTrip functions in compiled version * Generalize the use of the units (field .DisplayUnits): Rewrite processes to save the units correctly * Colormaps: * Allow brightness/contrast manipulations on the custom colormaps * Create a colormap similar to MNE, where extrema are bright * Global colormap max: Should get the maximum across all the open files * Open new figures as tab (docked in the Figures window) * Copy figures to clipboard (with the screencapture function) * Removing all the CTRL and SHIFT in the keyboard shortcuts * Display warning before opening files that are too big * Smooth display from figure_image (ERPimage, raster plot...) * Contact sheets & movies: use average of time windows instead of single instants, for each picture. |
* 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. |
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== Database == * Save iHeadModel somewhere in the datbase structure * Generalize the use of the units (field .DisplayUnits): Save in source files |
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* Thresholding and stat tests the connectivity matrices * Connectivity on unconstrained sources: how to group the three orientations? * Display as straight lines * Review by Jan-Mathijs: http://journal.frontiersin.org/article/10.3389/fnsys.2015.00175/full * Connectivity based on band limited power (Sylvain): * Compute Hilbert/Bandpass + correlation of the envelopes * Bandpass envelopes before computing correlations? * Compute Hilbert(sensors) and then project to source space? * 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)<<BR>>Explore inter-trial approaches (Esther refers to chronux toolbox) * Granger: * Crashes sometimes: improve stability * Check for minimum time window (Esther: min around 500-1000 data points) * Re-write and optimize code * Add progress bar * PLV: * Add p-values * Remove evoked * Optimize code * Add time integration * Unconstrained sources * Add warning when running of short windows (because of filters) * PAC: * Add input TF , to disconnect TF decomposition and PAC computation (Peter) * Refine frequency vector of low frequencies * How many central frequencies to use in bst_pac? * Change filters: no chirplet functions * bst_freqfilter: Use nfcomponents like in bst_pac * Esther recommended a larger frequency binning of the PAC estimation * PAC maps: Display all sensors at once (like TF and DynamicPAC) * Hui-Ling's PAC: * https://bsp.hackpad.com/Cross-Frequency-Coupling-cChe95lhDHz * https://github.com/NCTU-BSP/MEEG |
* 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) |
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* Other metrics: * Coherence by bands: bst_coherence_band_welch.m * Granger by bands: bst_granger_band.m * Inter-trial coherence * Tutorial coherence [1xN] : Reproduce FieldTrip results? * Connect NxN: Display as time series > Display warning before trying to open too many signals |
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* Explore Matlab-Python bridge:<<BR>> https://mail.python.org/pipermail/neuroimaging/2016-June/001001.html * Allow processes in Python and Java * Add FieldTrip functions: |
* Add MNE-Python functions: * scikit-learn classifiers * BEM single layer (John wants to test it) * ICA: https://neuroimage.usc.edu/forums/t/ica-on-very-long-eeg/23556/4 * https://neuroimage.usc.edu/forums/t/best-way-to-export-to-mne-python/12704/3 * Reproduce other tutorials / examples * Point-spread functions (PSFs) and cross-talk functions: https://mne.tools/stable/auto_examples/inverse/plot_psf_ctf_vertices.html#sphx-glr-auto-examples-inverse-plot-psf-ctf-vertices-py * Spatial resolution metrics in source space:<<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 |
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* ft_volumesegment * ft_computeleadfield * ft_prepare_heamodel * Use CUDA for speeding up some operations (filtering, wavelets, etc) |
* 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 |
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* Bug: After "convert to continuous", the time of the following processes should change | |
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* ITC: Inter-trial coherence (see MNE reports for group tutorial) * PLS: * https://www.rotman-baycrest.on.ca/index.php?section=84 * meg-pls dot weebly dot com * Krishnan 2011: http://www.ncbi.nlm.nih.gov/pubmed/20656037 * Cheung 2015: http://www.sciencedirect.com/science/article/pii/S1053811915007648 * McIntosh 2012: http://www.ncbi.nlm.nih.gov/pubmed/22804773 * McIntosh 2004: http://www.ncbi.nlm.nih.gov/pubmed/15501095 * ICA: * Exploration: Add window with spectral decomposition (useful for muscle artifacts) * Export IC time series (and then compute their spectrum): solves the problem above * Comparison JADE/Infomax: <<BR>> http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0030135 * Add methods: SOBI, Fastica, AMICA/CUDICA (recommended by S Makeig) * Dimension reduction with PCA adds artifacts: Not done by default in EEGLAB<<BR>>Contact: Stephen Shall Jones ( shall-jones@infoscience.otago.ac.nz )<<BR>>Student Carl Leichter detailed this in his thesis * S Makeig: Use ICA to select the IC of interest instead of only removing artifacts * Display of spectrum for components (PSD/FFT) * Use FastICA (algo crashing) * Understand why EEG/Epilepsy tutorial data crashes if we don't limit the number of components * Add components preselection: Correlation with EOG/ECG * Import ICA matrices available in EEGLAB .set files * EEGLAB recommends ICA + trial rejection + ICA again: Impossible right now with Brainstorm<<BR>>(http://sccn.ucsd.edu/wiki/Chapter_09:_Decomposing_Data_Using_ICA) * SSP: * '''Filters are not used correctly''': The code must be updated to add the transient length to the segments that are read, then filter, then remove the transients before computing the SSP * Display warning if changing the ChannelFlag while there is a Projector applied * Show where the attenuation is projected:<<BR>>(sum(IK,2)-sum(SSP(k,:)*IK,2)./sum(IK,2) * Pipeline editor: * 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) * When computing time-frequency/hilbert/psd: Find a way not to force the user to click on Edit * SSS/tSSS: Get implementation from MNE * Bandpass: Use new filters in all the processes that use process_bandpass (now too slow)<<BR>> * process_evt_detect_badsegment * process_evt_detect * process_evt_detect_analog * process_evt_detect_threshold * process_ssp2 * bst_connectivity * Optimize computation of the filter * 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) * Use the progress bar * Allow display of Avg+StdErr * Remove line noise: http://www.nitrc.org/projects/cleanline * Use Matlab Coder to optimize some processes: Wavelets, bandpass filter, sinusoid removal * Reports: Click on link reopens exactly the figure |
* 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 |
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* Multi-tapers * 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 |
* 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 |
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* Extend clusters tab to display of TF to overlay TF signals (Svet) | |
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* Artifact detection: * Artifact rejection like SPM: if bad in 20%, bad everywhere * Test difference between adjacent samples * Events detection: Add option "std" vs "amplitude" * Co-registration of MEG runs: * SSP: Group projectors coming from different files * Finish validation of the method * Apply to continuous recordings for correcting head movements * Other processes: * Moving average * Max * Median * Simulation: * Fix units in simulation processes => no *1e-9 in "simulate recordings" * Use "add noise" process from Hui-Ling (in Work/Dev/Divers) * Use field process field "Group" to separate Input/Processing/Output options * Use new Matlab functions: movmean, movsum, movmedian, movmax, movmin, movvar, movstd == Database == * Add buttons to sort files: by name, by comment, by date * MEG protocols: More flexible organization of the database; sub-conditions to allow different runs X different conditions. * Navigator: Use F2/F3 to explore the entire database (right now F2 works in a weird way) * Matrix files: Allow to be dependent from other files * Add notes in the folders (text files, visible as nodes in the tree) * Screen captures: save straight to the database * Rename multiple files * Default headmodel lost when reloaded: Keep selection on the hard drive (in brainstormstudy.mat) * protocol.mat can be too big: do not store the results links in it (and recreate when loading) == Distributed computing == * Options from FieldTrip: * Loose collection of computers: https://github.com/fieldtrip/fieldtrip/tree/master/peer * Alternative, with less limitations: http://research.cs.wisc.edu/htcondor/ * Single multicore machine: https://github.com/fieldtrip/fieldtrip/tree/master/engine * Batch system: https://github.com/fieldtrip/fieldtrip/tree/master/qsub * Documentation: http://fieldtrip.fcdonders.nl/faq#distributed_computing_with_fieldtrip_and_matlab * PSOM: http://psom.simexp-lab.org/ * Various initiatives: http://samirdas.github.io/Data_sharing.html#/ |
== Anatomy == * 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<<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 * Parcellating volume grids: scikit-learn.cluster.Ward * Geodesic distance calculations:<<BR>>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 * Add eyes models to attract eye activity |
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* Mixed head models: * Create scout form maximum doesn't work (menu Sources > Max value) * Set loose parameter from the interface |
* Reproduce results in "Simultaneous human intracerebral stimulation and HD-EEG, ground-truth for source localization methods": https://www.nature.com/articles/s41597-020-0467-x * eLORETA instead of sLORETA? * https://neuroimage.usc.edu/forums/t/compute-eeg-sources-with-sloreta/13425/6 * https://neuroimage.usc.edu/forums/t/loreta-and-source-localization/30525 * "eLORETA algorithm is available in the MEG/EEG Toolbox of Hamburg (METH)": https://www.biorxiv.org/content/biorxiv/early/2019/10/17/809285.full.pdf * https://github.com/brainstorm-tools/brainstorm3/issues/114 * Point-spread and cross-talk functions (code in MNE-Python): * https://www.biorxiv.org/content/biorxiv/early/2019/06/18/672956.full.pdf * https://github.com/olafhauk/EEGMEGResolutionAtlas * Dipoles: * Display dipoles in MRI viewer * panel_dipoles: Doesn't work with multiple figures * Project sources: Very poor algorithm to project sub-cortical regions and cerebellum * Maximum: * Menu Sources > Maximum value: Doesn't work with volume or mixed head models * Panel Get coordinates: Add button "find maximum" * Sources on surface: Display peak regions over time (time = color) => A.Gramfort |
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* 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" * Dipoles: * Project individual dipoles files on a template * panel_dipoles: Doesn't work with multiple figures * BEM single sphere: Get implementation from MNE * Stenroos 2014 paper: Include the following methods * Inner and outer skull surfaces generator from FieldTrip (needs SPM) * Nolte corrected-sphere model (good model re:Alex) * Fast BEM models * Visualize Beamformer results: * Read CTF SAM .svl * Display as layers in the MRI viewer * Unconstrained sources: * Stat and connectivity: what to do? (re-send email John+Sylvain) * Overlapping spheres: improve the estimation of the spheres for the frontal lobes * Magnetic extrapolation: Do the same thing with EEG * Noise covariance matrix: * Display with figure_image() * Storage of multiple noise covariance matrices (just like the head models) * Always save as full, then at inversion time, we can decide between full, heteroskedastic (diagonal) or homoskedastic (i.i.d, scalar) * Problem of having inividual trials + averages in the condition => Display warning or not? * Save nAvg in noisecov file, to make it easier to scale to other recordings * Sources on surface: Display peak regions over time (time = color) => A.Gramfort * Calculate ImagingKernel * Gain for a scout * Beamformers from FieldTrip (LCMV, SAM) * Time-frequency beamformers: * Band-pass everything in different frequency bands + Source estimation + TF * Ask data to Sarang where he sees effects that cannot be extracted with MN followed by TF * Process "Extract scouts time series": Add PCA option (replace isnorm with choice PCA/Norm) * BEM: Fix unstable results when one vertex is too close from the layers (5mm ?) * Hui-Ling beamformers: * More explanations about what is in NAI and Spatial filters * Explain that is this is better to study effects extended in time (Ntime > Nsensors) * Group LCMV+MCB * Condition LEFT median nerve: very bad results * Keep options for inverse computation * OpenMEEG: Post example datasets for the remaining issues: * https://github.com/openmeeg/openmeeg/issues/64 * https://github.com/openmeeg/openmeeg/issues/68 * Example protocol ECOG: doesn't work == Anatomy == * MNI coordinates: * Compute with FieldTrip: ft_prepare_sourcemodel (linear and non-linear) => Peter * FreeSurfer: * Do not save "mid" surface unless specified explicitely with the process version * Add cerebellum to default model generated with "Import FS anatomy" * Edit fiducials: Replace 6 text boxes with 1 for easy copy-paste (see fiducials.m) * BrainVISA: Add support for MarsAtlas (Guillaume A) * BrainSuite: * Use BrainSuite inner skull for surface generation * Use same colors for left and right for anatomical atlases * Warping: Scale option has to be fixed, it is currently very unstable * Scouts: * Display edges in the middle of the faces instead of the vertices * Display scouts in a tree: hemisphere, region, subregion * Downsample to atlas: allow on timefreq/connect files * Sort scouts by region in process options * Menu head model > Copy to other conditions/subjects (check if applicable first) * Generate mixed density surfaces * Optimize computation interpolation MRI-surface (tess_tri_interp) * Render surface envelope in the MRI as a thin line instead of the full interpolation matrix * Major bug when importing surfaces for an MRI that was re-oriented manually * Smooth surface: Fix little spikes due to irregularities in the mesh * Add eyes models to attract eye activity * tess_mrimask: Not robust enough to major holes in the brain * Bug: Hide scouts in the preview of the grid for volume head models == ECOG/SEEG == * Contact positions: Import / set / detect * Import/export electrodes positions in MNI/SCS/MRI coordinates * Co-register MRI and CT for electrodes marking in the MRI Viewer<<BR>>=> Mutual information: BrainVISA > Outils > Recalage rigide * Automatic segmentation of CT scans: See project of Rodrigo Paz (Marseille/Timone) * Import from FreeSurfer/FreeView: Problem of difference between RAS and TkRegRAS: http://neuroimage.usc.edu/forums/showthread.php?1958-SEEG-electrodes-and-subject-s-anatomy-are-not-alligned * Add history: Save modifications and transformations applied to the channel files (Marcel) * ECOG: How to handle cases where not all the grid contacts are in the channel file? (Marcel) * Project contact positions across subjects or templates (Marcel) * Display: * Display SEEG+ECOG contacts at the same time * Better way to represent ECOG strips that are not in contact with the skull (new type?) * SEEG length: count from the most superficial contact * SEEG default view: transparent cortex instead of MRI viewer (Marcel) * ECOG: Project on cortex instead of inner skull, just for display (Marcel) * Color each strip/grid differently * Bad channels: Contacts greyed out instead of ignored (Marcel) * ECOG: Topography display without the 3D coordinates (Marcel) * 2DLayout: Should not try to use the actual position of the sensors, just the grids/strips. * Display time in H:M:S * Alternatives to OpenMEEG: SimBio/FieldTrip? Matti Stenroos? NFT/NIST? * Prepare tutorial with public dataset (Marcel) |
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* 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 |
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* Use LENA functions(?) | * Write panel similar to Process1 and Process2 |
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* New process to test for Gaussianity using swtest * PLS: Partial Least Squares * Simulate recordings with specific properties, for stat validation * Quality control before statistics, on condition averages across subjects:<<BR>>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 |
* Multivariate stim-response analysis: https://github.com/mickcrosse/mTRF-Toolbox |
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* '''XDF import''': Use the EEGLAB plugin, contact Martin Bleichner (Oldenburg) | * BIDS import: * Add option to process to specify the protocol name * Full support for iEEG and EEG * Disable logging of sub-processes (reloading the previous report should only show process_import_bids) * 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:<<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) |
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* Use reader from MNE-Python: mne.io.read_raw_kit (doesn't require Yokogawa slow library) | * Use reader from MNE-Python: mne.io.read_raw_kit (skip Yokogawa slow library) |
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* References at too far from the head sensors in Marseille 4D system | |
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* Export to EDF * EEG File formats: * Nihon Koden * Nicolet EEG: Get from from MNE * EEG CeeGraph * EGI: Finish support for epoched files (formats 3,5,7) * BCI2000 Input (via EEGLAB plugin) * EEGLAB import: * Support for binary AND epoched files (now it's one or the other) * Allow epoched files with recordings saved in external files * BST-BIN: Add compressionto .bst * BIDS-MEG: Automatic loading of BIDS-structured databases * Review raw on all the file formats (ASCII EEG and Cartool missing) * gTec EEG recordings: Read directly from the HDF5 files instead of the Matlab exports. * Use new Matlab functions readtable/writetable (2006b): for Excel and text files == Distribution & documentation == * Account creation: Send authenticated emails: * https://support.google.com/mail/answer/81126 * https://support.google.com/mail/answer/180707 * Workflows FieldTrip: http://www.fieldtriptoolbox.org/faq/what_types_of_datasets_and_their_respective_analyses_are_used_on_fieldtrip * Reference tutorials on Google scholar + ResearchGate * Google Analytics: Create template and update the section of the Community page * New tutorials: * MEG steady-state / high-gamma visual * MEG resting state + OMEGA (Guoimar, Jeremy, Beth) * Intra-cranial recordings (Marcel) * Connectivity: Cortico-muscular coherence * Co-register MEG runs (Beth) * Missing in page "Cite Brainstorm": Add all the methods used in the software * Brainstorm File Exchange: Distribute scripts that users would like to share, but that are too specific to be included in the Brainstorm distribution. => On GitHub |
* 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) |
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* Compiled R2016b: Color picker doesn't work (for changing surface color for instance) | * 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 |
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* Screen capture: * Bug on Win8/Win10: doesn't capture the correct part of the screen * Window managers with fading effect: captures the top window |
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* 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 * Matlab bugs: * Interface looks small on screens with very high resolutions: Reduce the resolution * Event markers are not visible anymore with the sequence: Open MEG, open EOG, close MEG * in_bst_data_multi: If trials have different sizes, output is random (the one of the first file) * Edit scout in MRI: small modifications cause huge increase of the scout size * Canolty maps computation: Fix progress bar |
== 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/ |
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* 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. * Hide Java panels instead of deleting them |
* 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) |
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* 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 * Progress bar: * Add different levels (to handle sub-processes) * Make work correctly with RAW on resting tutorial * Uniformize calls in bst_process/Run * Add a "Cancel" button * Fix all the 'todo' blocks in the code * Error message: Add a link to report directly the bug on the forum |
What's next
A roadmap to the future developments of Brainstorm.
Contents
Recordings
- Review signals in time-frequency space
- Events processes: Select events names from a list instead of having to type them
- Display CTF coils: Show discs instead of squares
- 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
- 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
- Group display: Overlay multiple channel files in the same figure, coloring contacts by subject/ROI/Cluster/Electrode name
- 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):
- 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 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
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
- 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 (optionnal or foldable)
- Better provenance: History fields, uniform file names...
- Improving the pipeline editor to handle loops over data files or subjects
Interface
Add a warning when computing a forward model with > 100000 sources (check selection)
- Colormaps: Global colormap max: Should get the maximum across all the open files
- Snapshot:
- Save as image / all figures (similar to Movie/all figure)
- Copy figures to clipboard (with the screencapture function)
Contact sheets & movies: use average of time windows instead of single instants, for each picture.
- Contact sheets: Allow explicit list of times in input (+ display as in MNE-Python with TS)
Database
- Save iHeadModel somewhere in the datbase structure
Generalize the use of the units (field .DisplayUnits): Save in source files
Connectivity
- Thresholding and stat tests for connectivity matrices:
- Panel Display: Show only the top N% measures
- Connect NxN display:
- Graph on sensors: does not place the sensors correctly in space
- Display as image: Add legend of the elements along X and Y axis
- Display as time series: Display warning before trying to open too many signals
- Optimize display: use surface() instead of line() for links? (as in figure_3d/PlotFibers)
- Time-resolved correlation/coherence: Display as time bands
Processes
- Add MNE-Python functions:
- scikit-learn classifiers
- BEM single layer (John wants to test it)
ICA: https://neuroimage.usc.edu/forums/t/ica-on-very-long-eeg/23556/4
https://neuroimage.usc.edu/forums/t/best-way-to-export-to-mne-python/12704/3
- Reproduce other tutorials / examples
Point-spread functions (PSFs) and cross-talk functions: https://mne.tools/stable/auto_examples/inverse/plot_psf_ctf_vertices.html#sphx-glr-auto-examples-inverse-plot-psf-ctf-vertices-py
Spatial resolution metrics in source space:
https://mne.tools/stable/auto_examples/inverse/plot_resolution_metrics.html#sphx-glr-auto-examples-inverse-plot-resolution-metrics-py- Change the graphic renderer from Matlab
Chronux toolbox : http://chronux.org/
Add FieldTrip functions:
- ft_sourceanalysis:
- Check noise covariance
- Check all the options of all the methods
- Single trial reconstructions + noise covariance?
Filters?? http://www.fieldtriptoolbox.org/example/common_filters_in_beamforming
Beamformers: Save ftSource.avg.mom
http://www.fieldtriptoolbox.org/workshop/meg-uk-2015/fieldtrip-beamformer-demohttp://www.fieldtriptoolbox.org/tutorial/beamformingextended
- Baseline? Two inputs?
- ft_prepare_heamodel: Add support from BEM surfaces from the Brainstorm database
- Freqanalysis: ITC
ft_volumereslice: http://www.fieldtriptoolbox.org/faq/how_change_mri_orientation_size_fov
- ft_freqanalysis
- ft_combineplanar
- ft_sourceanalysis:
- Optimization:
Test speed for writing files:
https://undocumentedmatlab.com/articles/improving-fwrite-performance- Use CUDA for speeding up some operations (filtering, wavelets, etc)
- Use Matlab Coder to optimize: Wavelets, bandpass filter, sinusoid removal
- Pipeline editor:
- Bug: After "convert to continuous", the time of the following processes should change
- Add loops over subjects/conditions/trial groups
- Events: Allow selection from a drop-down list (similar to option "channelname" in panel_process_selection)
ITC: Inter-trial coherence (see MNE reports for group tutorial)
http://www.sciencedirect.com/science/article/pii/S1053811916304232Remove line noise: http://www.nitrc.org/projects/cleanline
- Time-frequency:
- Optimization: bst_timefreq (around l.136), remove evoked in source space: Average should be computed in sensor space instead of source space (requested by Dimitrios)
Short-time Fourier transform: http://www.mikexcohen.com/lectures.html
- Hilbert with time bands very slow on very long files (eg. 3600s at 1000Hz) because the time vector is still full (10^7 values): save compressed time vector instead.
- When normalizing with baseline: Propagate with the edge effects marked in TFmask
- Allow running TF on montages
- Review continuous files in time-frequency space (for epilepsy)
- Bug when computing TF on constrained and unconstrained scouts at the same time (in mixed head models for instance): uses only the constrained information and doesn't sum the 3 orientations for the unconstrained regions.
Anatomy
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 envelopeSurface>Volume interpolation: Use spm_mesh_to_grid instead of tess_tri_interp
- Defacing:
https://afni.nimh.nih.gov/pub/dist/doc/htmldoc/tutorials/refacer/refacer_run.html
- Removing MNI face mask using MNI coordinates
- Atlas switch in 3D MRI figures
Bug import anatomy: Requested nVert > high-resolution cortex surface: Creates an empty cortex_0V
BrainSuite:
- Use same colors for left and right for anatomical atlases
- Use for volume coregistration (rigid / non-rigid)
- USCBrain: Add default electrodes positions
Remove BrainSuite1 when not needed anymore
- Brain2mesh: Add import of 10-10 positions
- Templates for different ages:
MNI: https://www.bic.mni.mcgill.ca/ServicesAtlases/NIHPD-obj1
Pediatric head atlases: https://www.pedeheadmod.net/pediatric-head-atlases-v1-2/
https://www.biorxiv.org/content/biorxiv/early/2020/02/09/2020.02.07.939447.full.pdf
John Richards: https://www.nitrc.org/frs/?group_id=1361
Neurodev database: https://jerlab.sc.edu/projects/neurodevelopmental-mri-database/
- Scouts:
- Display edges in the middle of the faces instead of the vertices
- Parcellating volume grids: scikit-learn.cluster.Ward
Geodesic distance calculations:
https://www.mathworks.com/matlabcentral/fileexchange/6110-toolbox-fast-marching- Improving the registration between EEG and anatomy templates:
- Warping: Improve the basic alignment of the digitized electrodes on the templat, possibly with Cz and other anatomical landmarks
- EEG template positions: rework using a standardized Cz position (+ other landmarks)
Forward modeling
- DUNEuro/FEM:
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
- Add eyes models to attract eye activity
Source modeling
Reproduce results in "Simultaneous human intracerebral stimulation and HD-EEG, ground-truth for source localization methods": https://www.nature.com/articles/s41597-020-0467-x
- eLORETA instead of sLORETA?
https://neuroimage.usc.edu/forums/t/compute-eeg-sources-with-sloreta/13425/6
https://neuroimage.usc.edu/forums/t/loreta-and-source-localization/30525
"eLORETA algorithm is available in the MEG/EEG Toolbox of Hamburg (METH)": https://www.biorxiv.org/content/biorxiv/early/2019/10/17/809285.full.pdf
- Point-spread and cross-talk functions (code in MNE-Python):
- Dipoles:
- Display dipoles in MRI viewer
- panel_dipoles: Doesn't work with multiple figures
- Project sources: Very poor algorithm to project sub-cortical regions and cerebellum
- Maximum:
Menu Sources > Maximum value: Doesn't work with volume or mixed head models
- Panel Get coordinates: Add button "find maximum"
Sources on surface: Display peak regions over time (time = color) => A.Gramfort
- Volume grid:
- Optimize: 3D display (better than 9x9 cubes)
- Optimize: vol_dilate (with 26 neighbors)
Statistics
- Stat on unconstrained sources?
Stat/time series: Hide lines going down to zero (Dimitrios: https://neuroimage.usc.edu/forums/t/common-source-activation-across-subjects-and-conditions/1152/21)
- Cluster stat: Add frequency selection option
- ANOVA:
- Write panel similar to Process1 and Process2
- Output = 1 file per effect, all grouped in a node "ANOVA"
- Display several ANOVA maps (from several files) on one single figure, using a "graphic accumulator", towards which one can send any type of graphic object
Multivariate stim-response analysis: https://github.com/mickcrosse/mTRF-Toolbox
Input / output
- BIDS import:
- Add option to process to specify the protocol name
- Full support for iEEG and EEG
- Disable logging of sub-processes (reloading the previous report should only show process_import_bids)
- Read real fiducials (OMEGA) / transformation matrices:
- 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:
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)