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| A roadmap for the future developments of Brainstorm. == Next six months == == New interface elements == | A roadmap to the future developments of Brainstorm. <<TableOfContents(2,2)>> == Recordings == * 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. * Add filter option to the montage editor: This would allow splitting the signals in various frequency bands. * 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? == 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 * 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: 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 * Implement data exchange with MNE-Python: write FIF files from Brainstorm and/or pass python objects in memory instead of FIF files * https://neuroimage.usc.edu/forums/t/best-way-to-export-to-mne-python/12704/3 * SSS/tSSS cleaning * Reproduce other tutorials / examples * 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 <<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_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)<<BR>>http://www.sciencedirect.com/science/article/pii/S1053811916304232 * ICA: * 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: <<BR>> http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0030135 * Use faster methods (MNE-Python?) * 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) * 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) * ICA+machine learning: https://www.ncbi.nlm.nih.gov/pubmed/28497769 * Automated artifact rejection: https://arxiv.org/abs/1612.08194 * Save IC time series in database * 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 * 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 == * Rename protocol * Faster DB searches (for Emily) * Add buttons to sort files: by name, by comment, by date | 
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| * Functionnal connectivity (display: see eConnectome) * SSP: * Make SSP projections dynamic, and keep the full list instead of always them combining them * Take the bad channels in account in the application of the SSP * Refresh display after changing the list of bad channels (imported files + raw) so the SSP are applied correctly * bst_selections: * Add user defined combinations of sensors (eg. "double banana" for EEG) * Use this to produce "inversed polarity" displayes too (useful in EEG) * Standard setups for al the EEG caps | * 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 * 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#/ == Source modeling == * Use eLORETA instead of sLORETA? <<BR>>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 * 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) | 
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| * Homogenize a selection of several subjects/conditions * Popup menu when more than one study selected * Creation of a common channel file (match channels by names, not by order) * Register MEG runs (recompute fields for a different set of sensors, MEGCoregister from old brainstorm) * Images of amplitude: [sensor x time], [trial x time], scout: [trial x time] (similaire to erpimage in eeglab) * Simulation: synthesize pseudo data-files from a cortex patch (duration, amplitude, noise) * Interface to compute reaction times based on events: <<BR>>Input:selection of cue event + event response; Output: reation time trial by trial, average, std, distribution... => Etienne Labyt * Database navigator: F4 to switch to next sourcefile * Segmentation in microstates == Source modeling == * Inverse: * Stable LCMV Beamformer * MUSIC * sLORETA: Values are now multiplied by 1e12 at loading for display => has do to be done in another way * Unconstrained sources: * Define as default * Check all the processes * Difference and stat should be: norm(A) - norm(B) * Overlapping spheres: improve the estimation of the spheres for the frontal lobes * Volume grid: * Scouts 3D * Test volume sources with all the subsequent processes (timefreq, stat...) * Optimize: 3D display (better that 9x9 cubes) * Optimize: vol_dilate (with 26 neighbors) * Optimize: grid_interp_mri * Magnetic extrapolation: * Do the same thing with EEG * Optimize bst_extrapm.m, add waitbar * Use the noise covariance from the database instead of recomputing it * Project sources: * Adapt smooth factor to the number of vertices * Number of neighbors to consider = average number of neighbors in the target mesh. * Compute by small time blocks * Noise covariance matrix: * Save nAvg in noisecov file, to make it easier to scale to other recordings * When deploying to other conditions: Apply destination SSP (!NoiseCov = SSP . !NoiseCov . SSP' ) | * Process "Extract scouts time series": Add PCA option (replace isnorm with choice PCA/Norm) * Add eyes models to attract eye activity * Display source maps on a flat 2D cortex projection (Mollweide projection): https://neuroimage.usc.edu/forums/t/source-model-display-and-output/13940/5 | 
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| * MRI import: auto-reorientation of MRI after selected NAS / LPA / RPA. | * 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<<BR>>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 * Pediatric head atlases: https://www.pedeheadmod.net/pediatric-head-atlases-v1-2/ * 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 | 
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| * Finalize Brodmann scouts * Remove NCS/Talairach coordinate system, or fix it => Sylvain, Karim ND * Clustering cortex: Dimitrios, David, Yu-Teng == Processes == * Important new processes for a full processing pipleline: * Import, and segmentation of RAW files * Detect bad segments on RAW (then events in "bad" segments would be ignored) * Artifact detection: use other things than simple value thresholds (like variance of the sensors...) * Create events list based on thresholds on some channels (Stim, EOG, ECG...) => Etienne Labyt * Creation of SSP vectors (ex: Remove cardiac artifac) * ICA * Integration of Antoine Ducorps methods (everything in the doc of the dataHandler): * Cardiac artifact correction in MEG * PCA correction of ocular artifacts * Interpolation of missing EEG canal * Headmodel / sources / noise cov * Project sources * Delete intermediary files * Processing raw/continuous: * Process non-FIF files (need to convert the header) * Apply SSP + CTF Compensators(only if it useful - maybe create a specific process for that) * Other processes: * Bug: gradnorm crashes with bad channels * Spatial smoothing: check / document parameters * Sinusoid removal: fix new function * Time-frequency: * Write script for timefreq tutorial * Make much faster and more memory efficient (C functions coded by Matti ?) * Power spectrum: computation (FFT/welch, or average of TF) + display(f/Power, 2DLayout) * Display stat computed on time-frequency data * Display TF maps separately for the two gradiometers (if not: overlap) * Source reconstruction by frequency bands * Scouts on surface / time-freq * Process selection interface: * Bug when redimensioning window (with more than one process) * isAvgRef: warning quand process necessite des donnees en AVG REF en entree * Save "freqband" option when edited from custom processes * John's noise cancellation filters * Chain calls of similar processes (ex. bandpass+sin_remove), to avoid reading the full raw files several times | * Surface>Volume interpolation: Use spm_mesh_to_grid * Bug: Hide scouts in the preview of the grid for volume head models * Geodesic distance calculations:<<BR>>https://www.mathworks.com/matlabcentral/fileexchange/6110-toolbox-fast-marching == ECOG/SEEG == * Contact positions: Import / set / detect * New option: Align on none|inner|cortex to replace ECOG-mid * 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 * 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 | 
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| * ANOVA: Use LENA functions | * ANOVA: * Which functions to use? * Write panel similar to Process1 and Process2 to allow the | 
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| * Permutation tests: * t-test only (wilcoxon? sign-test?): paired, equal var, unequal var * nb permutations ~ 1000 * maximum statistic over "time" or "time and space" * Permutations / clustering: cf fieldtrip * http://fieldtrip.fcdonders.nl/tutorial/cluster_permutation_timelock * http://fieldtrip.fcdonders.nl/tutorial/cluster_permutation_freq * Threshold in time: keep only the regions that are significative for contiguous blocks of time, or over a certain number of time points<<BR>> => Process that creates a static representation of a temporal window == Display == * OpenGL options: {none, software, hardware} * Colormap: Set colormap max with right-click + move on the colorbar * Bug: Mixing 2 views MRI/3d, white cuts appear after !SetCurrentFigure * Bug: Scout without overlay, adapt scale for each graph when "Uniformize" option is unchecked (mixing sources + zscores) * Waitbars: * Replace old waitbars with java ones * Add a "Cancel" button on waitbars when the bounds are defined (ie. when bst controls the process) * Contact sheets & movies: use average of time windows instead of single instants, for each picture. == I/O == | * 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 * Export to R or SPSS for advanced stat == Input / output == * '''XDF import''': Use FieldTRip or the EEGLAB plugin, contact Martin Bleichner (Oldenburg)<<BR>>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?) | 
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| * Nihon Kohden * EDF+ * !BrainVision / !BrainAmp: Get functions from EEGLAB * EEG !CeeGraph * NEUROFILE = COHERENCE EEG/video !LongTerm Monitoring => Manfred Spueler | * EEG CeeGraph | 
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| * Other file formats * MEG160 (KIT) * CTF: * Read continuous RAW files split in several .meg4 files ( > 2 Go) * Read STIM channel and generate !MarkerFile * EEGLAB: Apply ICA matrices, get number of trials for AVG files * !FieldTrip structures: In / Out * Gzipped Nifti (new BrainVISA standard) * Analyze / Nifti:<<BR>> * Fix output function (output MRIs cannot be imported in SPM) * Use correctly field "orient" to align automatically MRI when importing * Define scouts from SPM / Analyze 3D masks * Files > 2Gb: display warnings == Programming details == * Double-click doesn't work well on some Linux workstations * Bug: Menu "Use default EEG cap" doesn't work for a multiple selection (setting the same EEG cap for several subjects) * Bug node selection: click on sources > TF: select node-source, not node-condition * Bug tree_dependencies: sources files, reprojected on default anatomy; If based on data files that are bad trials, they should be ignored by tree_dependencies, and they are not | * 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 == Distribution & documentation == * Tutorial OMEGA/BIDS: * Add review of literature for the resting state MEG * 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/]] * Rat PAC + high gamma (Soheila) * 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/<<BR>>(download new datasets, including maxfiltered files and manual fiducial placements) * MEG steady-state / high-gamma visual / frequency tagging * BIDS-EEG example datasets * 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 == * 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 * in_bst_data_multi: If trials have different sizes, output is random (the one of the first file) * Canolty maps computation: Fix progress bar == Geeky programming details == * 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) | 
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| * Testing functions: test_ctf "folder" / test_neuromag "folder" / test "folder" => Alex * Bug in_bst_data_multi: If trials have different sizes, output is random (the one of the first file)... * Shared kernels: do the "get bad channels" operation in a different way (reading all the files is too slow) * Rewrite all GUI functions with gui_component * Remove field "!BrainStormSubject" in the studies file: force same folder name for anat & data * Allow protocols with same folder for anat and data * Ensure that all the loaded and saved filenames are in "unix" format * Use parfor: When not available, replace directly all the "parfor" with "for" in file.m * Use Matlab GPU toolbox * Re-use panels instead of delete+create again * Optimize bst_read_events_track * Write shepards.m with new algorithm for nearest neighbors * Use tesselations_stat and tesselations_outwards to clean surfaces * Movies: Use JAVE (Java) * Screen captures: Use Yair Altman functions (in Matlab Central) == Distribution & documentation == * Compile stand-alone version: Linux, MacOS * Version with big fonts for live demos * Add Help buttons and menus (in popups, dialog windows...) => Links to the website. * Send email to registered users to anounce major improvements * Script tutorials: * Update them to reflect all the recent changes * Script for the time-frequency computation * Introduction tutorials: * Estimate time to complete each tutorial * Clusters * Anatomy: Segmentation with !FreeSurfer * First steps: Brainstorm preferences * Headmodel: explain the fields + how to get the constrained leadfield * Coordinate sytems: How to convert between the different coordinates systems in scripts * Sources: Modelized data * Sources: theshold min. size (not documented yet) * Scouts: Atlases of Tzourio-Mazoyer and Brodman * Processes: Describe all the processes * Processes: How to write your own processes (user folder for processes) * Processes: Processing RAW files * Import raw recordings: Add "detect bad trials/channels" in the pipeline * Advanced tutorials: * MNE sample dataset * EEG (How to import an EEG cap) * MRI segmentation with !FreeSurfer => David Wheland * How to make and compress a movie (Brainstorm + !VirtualDub + XVid) * Display the "What's new" page after downloading new version of brainstorm * Ask users to send their channel files, align on Colin, distribute == Unsolved problems == * Surfaces: * Influence of the software used to extract surfaces (!BrainVisa, !BrainSuite, !FreeSurfer) * Type of cortex surface to use: grey/white, grey/csf, midsurface ? * How to get good surfaces for BEM ? * Group analysis: * 1) localization on individual brain + interpolation on MNI brain ? * 2) localization directly on MNI brain ? * Normalize amplitudes across different subjects / runs ? * Online documentation of forward and inverse methods | * 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 | 
What's next
A roadmap to the future developments of Brainstorm.
Contents
Recordings
- 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.
- Add filter option to the montage editor: This would allow splitting the signals in various frequency bands.
- 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?
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):   
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
- 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
- Implement data exchange with MNE-Python: write FIF files from Brainstorm and/or pass python objects in memory instead of FIF files
- https://neuroimage.usc.edu/forums/t/best-way-to-export-to-mne-python/12704/3 
- SSS/tSSS cleaning
- Reproduce other tutorials / examples
- 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.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
 
- ft_sourceanalysis: 
- 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: - 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?)
- Add methods: SOBI, Fastica, AMICA/CUDICA (recommended by S Makeig)
- 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 
- Save IC time series in database
- 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 
- 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
- Rename protocol
- Faster DB searches (for Emily)
- 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.
- 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 
- 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 
 
- Various initiatives: http://samirdas.github.io/Data_sharing.html#/ 
Source modeling
- 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):
- 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
 
- 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
- Display source maps on a flat 2D cortex projection (Mollweide projection): https://neuroimage.usc.edu/forums/t/source-model-display-and-output/13940/5 
Anatomy
- Multi-Scale Brain Parcellator (Lausanne2008):
- MNI transformation: Use SPM non-linear MNI transformation y_...
- Registration: - Getting electrode positions from 3D scanners: https://sccn.ucsd.edu/wiki/Get_chanlocs 
- 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
 
- Pediatric head atlases: https://www.pedeheadmod.net/pediatric-head-atlases-v1-2/ 
- 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
- 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
 
- Automatic segmentation of CT:
- 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
- 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: 
- 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)
- 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
Distribution & documentation
- Tutorial OMEGA/BIDS: - Add review of literature for the resting state MEG
- Download example datasets directly from the OMEGA repository
 
- New tutorials: 
 - Other public datasets: https://github.com/INCF/BIDS-examples/tree/bep008_meg/ 
- Rat PAC + high gamma (Soheila)
- 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/<<BR>>(download new datasets, including maxfiltered files and manual fiducial placements) 
- MEG steady-state / high-gamma visual / frequency tagging
- BIDS-EEG example datasets
 
- 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
- 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
 
- in_bst_data_multi: If trials have different sizes, output is random (the one of the first file)
- Canolty maps computation: Fix progress bar
Geeky programming details
- 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
