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| == Current topics == ==== Functionnal connectivity ==== * Integration of different metrics to study the brain connectivity: <<BR>>Correlation, coherence, Granger causality, phase locking value * Development of new ways to represent the connectivity between sensors or brain regions ==== EEG / epilepsy / intra-cranial recordings ==== * Editing the position of intracranial electrodes in the MRI viewer ==== Source modeling ==== * Computation of equivalent current dipoles * Beamformers ==== Large scale analysis ==== * Parallel processing: Reduce the computation times using the parallel processing toolbox * Distributed processing: Integrate tools for sending Brainstorm processes on computation clusters <<BR>><<BR>><<BR>> |
<<TableOfContents(2,2)>> |
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| * RAW file viewer: | * Default montages for EEG (sensor selection) * Sleep scoring wish list (Emily C): * Configurable horizontal lines (for helping detecting visually some thresholds) * Mouse ruler: Measure duration and amplitude by dragging the mouse. * Automatic spindle detector * https://neuroimage.usc.edu/forums/t/page-overlap-while-reviewing-raw-file-a-way-to-set-to-0/11229/13 * RAW file viewer speed: * Downsample before filtering? (attention to the filter design) * Add parameter to make the visual downsampling more or less aggressive |
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| * Documentation: Add definition of bad segments * 2DLayout: Doesn't work when changing page => need refresh of GlobalData.Preferences.TopoLayoutOptions.TimeWindow * EEG reference/storage: * Intracranial electrodes: Define and display in the MRI viewer + 3D figures * Bad locations: indicate with [NaN NaN NaN] instead of [0 0 0] * Bad channels that can be specified at the program level (for sites that have permanently bad channels) => AS Dubarry * RAW processing: * Make it work for all the file formats (at least bandpass filter + sin removal) * Events: advanced process for recombining. Example: http://www.erpinfo.org/erplab/erplab-documentation/manual/Binlister.html |
* Keep the filter specifications in memory instead of recomputing for every page * MEG/EEG registration: Apply the same transformation to multiple runs * Create heat maps: Maybe with matlab function heatmap? * BioSemi: Add menu "Convert naming system" to rename channels into 10-10 (A1=>FPz) == 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 |
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| * Create a colormap similar to MNE, where extrema are bright * Import data: * Save properties "baseline" and "resample" at the level of the protocol (to re-use for all the files) * NIRS: * Add new data type * Display of sensors by pairs oxy/deoxy (red/blue), overlaid * Images of amplitude: [sensor x time], [trial x time], scout: [trial x time] * Can be done with Matrix > View as image: extract cluster, concatenate for all trials * 2D Layout for multiple conditions |
* Allow brightness/contrast manipulations on the custom colormaps * Global colormap max: Should get the maximum across all the open files * Copy figures to clipboard (with the screencapture function) * Contact sheets & movies: use average of time windows instead of single instants, for each picture. * Contact sheets: Allow explicit list of times in input (+ display as in MNE-Python with TS) * Display CTF coils: Show discs instead of squares * Progress bar: Add a "Cancel" button * Error message: Add a link to report directly the bug on the forum * Reorganize menus (Dannie's suggestion): {{attachment:dannie_menus.png||width="382",height="237"}} |
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| * Tutorial coherence [1xN] * t-tests on connectivity measures * Graph view: * Fixed scales for intensity sliders * Fix zoom in one region * Text bigger * Too much data in appdata * Other metrics: * Coherence by bands: bst_coherence_band_welch.m * Granger by bands: bst_granger_band.m * Inter-trial coherence * Work on progress bars |
* Thresholding and stat tests for connectivity matrices * Connectivity on unconstrained sources: "Default signal extraction for volume grids should be the time series of the first principal component of the triplet signals after each has been zero-meaned" (SB) * Connect NxN display: * Graph on sensors: does not place the sensors correctly in space * Display as image: Add legend of the elements along X and Y axis * Display as time series: Display warning before trying to open too many signals * Time-resolved correlation/coherence: Display as time bands * Weighted Phase Lag Index (WPLI) * 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: * Remove evoked * Add time integration * Unconstrained sources * Add warning when running of short windows (because of filters) |
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| * Plugin manager: * Export all the software environment to a .zip file (brainstorm + all plugins) * Generate fully reproducible scripts, including all the interactive/graphical parts: * Saving all the interactive operations as process calls * Improving the pipeline editor to handle loops over data files or subjects * Keeping a better track of the provenance of all the data (History, uniform file names) * Add MNE-Python functions: * scikit-learn classifiers * https://neuroimage.usc.edu/forums/t/ica-on-very-long-eeg/23556/4 * https://neuroimage.usc.edu/forums/t/best-way-to-export-to-mne-python/12704/3 * Reproduce other tutorials / examples * Point-spread functions (PSFs) and cross-talk functions: https://mne.tools/stable/auto_examples/inverse/plot_psf_ctf_vertices.html#sphx-glr-auto-examples-inverse-plot-psf-ctf-vertices-py * Spatial resolution metrics in source space:<<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 * 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 * ft_freqanalysis * ft_combineplanar * Optimization: * Use CUDA for speeding up some operations (filtering, wavelets, etc) * Use Matlab Coder to optimize: Wavelets, bandpass filter, sinusoid removal * Pipeline editor: * Bug: After "convert to continuous", the time of the following processes should change * Add loops over subjects/conditions/trial groups * Events: Allow selection from a drop-down list (similar to option "channelname" in panel_process_selection) * ITC: Inter-trial coherence (see MNE reports for group tutorial)<<BR>>http://www.sciencedirect.com/science/article/pii/S1053811916304232 * ICA: * Add Alex's suggestions: https://neuroimage.usc.edu/forums/t/ica-on-very-long-eeg/23556/4 * Add methods: SOBI, Fastica, AMICA/CUDICA/CUDAAMICA (recommended by S Makeig) * Why doesn't the ICA process converge when using 25 components in the EEG tutorial? * Add an option to resample the signals before computing the ICA decomposition * Exploration: Add window with spectral decomposition (useful for muscle artifacts) * Export IC time series (and then compute their spectrum): solves the problem above * Comparison JADE/Infomax: <<BR>> http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0030135 * 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 * 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 * Use EYE-EEG: EEGLAB toolbox for eye-tracker guided ICA (Olaf Dimigen): http://www2.hu-berlin.de/eyetracking-eeg/ * SSP: * Display warning if changing the ChannelFlag while there is a Projector applied * Remove line noise: http://www.nitrc.org/projects/cleanline |
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| * Frequency bands: extended syntax (ex: [2 3 4], 10:5:90, ...) * How to combine 3 orientations for unconstrained sources * Display logs as negative * 2D Layout in spectrum * Make much faster and more memory efficient (C functions coded by Matti ?) * Smooth display of TF/PAC maps (option) * TF scouts: should display average of TF maps * Bandpass: Show warning when using inappropriate high-pass filter (precision too high) * Artifact detection: * Detection of bad segments in the RAW files * Artifact rejection like SPM: if bad in 20%, bad everywhere * Test difference between adjacent samples * Distributed processing: Brainstorm that can run without Java * 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) * Average: * Remember how many trials were used per channel * Save standard deviation * Display standard deviation as a halo around the time series * 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 * Current Source Density (CSD) => Ghislaine<<BR>>http://psychophysiology.cpmc.columbia.edu/software/CSDtoolbox/index.html * Other processes: * Detrending * Moving average * Max * Median * Significance test (Dimitrios, Leo) * Spatial smoothing: check / document parameters * Contact sheets & movies: use average of time windows instead of single instants, for each picture. * Optical flow == Database == * MEG protocols: More flexible organization of the database; sub-conditions to allow different runs X different conditions. * Group matrix files => allow to process matrix files by trial types * Add notes in the folders (text files, visible as nodes in the tree) * Screen captures: save straight to the database * Rename multiple files |
* 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. |
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| * Stenroos 2014 paper: Include the following methods * Inner and outer skull surfaces generator from !FieldTrip (needs SPM, probably not so different from BST) * Nolte corrected-sphere model (good model re:Alex) * Fast BEM models * Dipole fitting * Visualize Beamformer results: * Read CTF SAM .svl * Display as layers in the MRI viewer |
* Unconstrained to flat: Default PCA for stat and connectivity? * Reproduce results in "Simultaneous human intracerebral stimulation and HD-EEG, ground-truth for source localization methods": https://www.nature.com/articles/s41597-020-0467-x * eLORETA instead of sLORETA? * https://neuroimage.usc.edu/forums/t/compute-eeg-sources-with-sloreta/13425/6 * "eLORETA algorithm is available in the MEG/EEG Toolbox of Hamburg (METH)": https://www.biorxiv.org/content/biorxiv/early/2019/10/17/809285.full.pdf * https://github.com/brainstorm-tools/brainstorm3/issues/114 * Sensitivity maps: https://mne.tools/stable/auto_examples/forward/plot_forward_sensitivity_maps.html * Point-spread and cross-talk functions (code in MNE-Python): * https://www.biorxiv.org/content/biorxiv/early/2019/06/18/672956.full.pdf * https://github.com/olafhauk/EEGMEGResolutionAtlas * Dipoles: * 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 * Menu Sources > Maximum value: Doesn't work with volume or mixed head models * Mixed head models: * Bug when displaying interpolated in MRI viewer * Volume grid: * Optimize: 3D display (better than 9x9 cubes) * Optimize: vol_dilate (with 26 neighbors) * Panel Get coordinates: Add button "find maximum" * BEM single sphere: Get implementation from MNE |
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| * Compute unconstrained and then project on the normal ? * Difference and stat should be: norm(A) - norm(B) |
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| * 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) * Magnetic extrapolation: Do the same thing with EEG * Noise covariance matrix: * 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 * When deploying to other conditions: Apply destination SSP (!NoiseCov = SSP . !NoiseCov . SSP' ) |
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| * Simulation: synthesize pseudo data-files from a cortex patch (duration, amplitude, noise) * Calculate !ImagingKernel * Gain for a scout * EEG Source modeling: Manage references and bipolar montages properly (maybe not necessary) * MEG source modeling: Do reconstruction only for a subset of sensors for estimating dipoles? * Processes compute head model and sources: Additional option to set the file comment |
* Process "Extract scouts time series": Add PCA option (replace isnorm with choice PCA/Norm) * Add eyes models to attract eye activity * Display spectrum scouts (PSD plots when clicking on "Display scouts" on PSD/full cortex) |
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| * FastSurfer: https://deep-mi.org/research/fastsurfer/ * '''SimNIBS''': Replace HEADRECO with CHARM (headreco will be removed in SimNIBS 4) * Infant templates: Add electrodes positions (at least 10-10) * Neurodev MRI database: https://jerlab.sc.edu/projects/neurodevelopmental-mri-database/ * 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/ * 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 * 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 * Optimize computation interpolation MRI-surface (tess_tri_interp) => spm_mesh_to_grid * BrainSuite: * Add new labels to all BrainSuite anatomy templates * Use same colors for left and right for anatomical atlases * Use for volume coregistration (rigid / non-rigid) * USCBrain: Add default electrodes positions * FEM templates for different ages: * Pediatric head atlases: https://www.pedeheadmod.net/pediatric-head-atlases-v1-2/ * https://iopscience.iop.org/article/10.1088/2057-1976/ab4c76 * https://www.biorxiv.org/content/biorxiv/early/2020/02/09/2020.02.07.939447.full.pdf * John Richards: https://www.nitrc.org/frs/?group_id=1361 |
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| * Mix constrained/unconstrained/volume sources, using the "Source model" atlas | |
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| * Project scouts betweens subjects and between hemispheres | |
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| * Sort scouts by region in process options | |
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| * Sort scouts by region in process options * Generate mixed density surfaces * Import / registration: * Major bug when importing surfaces for an MRI that was re-oriented manually * Use mid-gray instead of pial surface? |
* 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:<<BR>>https://www.mathworks.com/matlabcentral/fileexchange/6110-toolbox-fast-marching * Allen Institute gene expression atlases: Import in Brainstorm as source maps and display on cortex == ECOG/SEEG == * Electrodes models: Import / export * Contact positions: Import / set / detect * New option: Align on none|inner|cortex to replace ECOG-mid * Add history: Save modifications and transformations applied to the channel files (Marcel) * Project contact positions across subjects or templates (Marcel) * Add menu to import implantation channel file in imported recordings * SEEG/ECOG: Identify contacts in resected areas / identify ROIs for each contact * SEEG/ECOG: Identify contacts in a given anatomical region (volume scout, surface mesh, or label in a volume atlas) / allow extracting the signals from all the contacts in an ROI * Automatic segmentation of CT: * GARDEL: http://meg.univ-amu.fr/wiki/GARDEL:presentation * SEEG DEETO Arnulfo 2015: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-015-0511-6 * Used routinely at Niguarda Hospital + other hospitals worldwide, reliable tool. * To be used with SEEG-assistant/3DSlicer: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-017-1545-8 * ECOG Centracchio 2021: https://link.springer.com/content/pdf/10.1007/s11548-021-02325-0.pdf * Classifier on thresholded CT: https://github.com/Jcentracchio/Automated-localization-of-ECoG-electrodes-in-CT-volumes * SEEG Granados 2018 (no code shared): https://link.springer.com/content/pdf/10.1007/s11548-018-1740-8.pdf * ECOG: * Project and display contacts on cortex surface should consider the rigidity of the grids: Contacts cannot rotate, and distance between contacts should remain constant across runs * Method for contacts projection: https://pdfs.semanticscholar.org/f10d/6b899d851f3c4b115404298d7b997cf1d5ab.pdf * ECOG: Brain shift: When creating contact positions on a post-implantation image, the brain shift should be taken into account for creating images of the ECOG contacts on the pre-op brain => iELVis (http://ielvis.pbworks.com/w/page/116347253/FrontPage) * Display: * Bad channels: Contacts greyed out instead of ignored (Marcel) * Display time in H:M:S * Display curved SEEG electrodes * 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 * http://www.adscience.fr/uploads/ckfiles/files/html_files/StatEL/statel_wilcoxon.htm * http://www.mathworks.fr/fr/help/stats/signrank.html * Less powerful than t-tests * 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 * t-test on volume sources * Paired t-test on unconstrained sources: (convert to flat + Z-score) => !AnneSo * Question of Gaussianity of the samples: take a subset of samples + Kolmogorov-Smirnov / Shapiro-Wilk test * http://fr.wikipedia.org/wiki/Test_de_Shapiro-Wilk * http://stats.stackexchange.com/questions/362/what-is-the-difference-between-the-shapiro-wilk-test-of-normality-and-the-kolmog * http://www.mathworks.fr/fr/help/symbolic/mupad_ug/perform-shapiro-wilk-test.html * http://www.mathworks.fr/fr/help/symbolic/mupad_ref/stats-swgoft.html * http://stackoverflow.com/questions/14383115/shapiro-wilk-test-in-matlab * Create icons for Stat/PAC, Stat/Sprectrum, etc. * One sample t-test across subjects |
* 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 |
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| * Bug import multiple files: use same "time" for all files * BIDS import: * Read real fiducials (OMEGA) / transformation matrices: * https://groups.google.com/g/bids-discussion/c/BeyUeuNGl7I * https://github.com/bids-standard/bids-specification/issues/752#issuecomment-795880992 * Read associated empty room * Test all the BIDS examples * BIDS Export: * Add events tsv, channel tsv, EEG, iEEG * '''XDF import''': Use FieldTRip or the EEGLAB plugin, contact Martin Bleichner (Oldenburg)<<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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| * EEG !CeeGraph | * EEG CeeGraph |
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| * !FieldTrip structures: In / Out | * 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 |
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| * Export TF maps to SPM / volumes * EEGLAB import: Selection of conditions in script mode |
* BST-BIN: Add compression to .bst * Review raw on all the file formats (ASCII EEG and Cartool missing) * SPM .mat/.dat: Fix the import of the EEG/SEEG coordinates * Get acquisition date from files: Missing for 4D * Support for OpenJData / JNIfTI: https://github.com/brainstorm-tools/brainstorm3/issues/284 |
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| * Add Help buttons and menus (in popups, dialog windows...) => Links to the website. * Introduction tutorials: * Processes: Describe all the processes * Clusters * First steps: Brainstorm preferences * Headmodel: explain the fields + how to get the constrained leadfield * Sources: Modelized data * Sources: theshold min. size (not documented yet) * Import raw recordings: Add "detect bad trials/channels" in the pipeline * Temporary folder |
* Tutorial OMEGA/BIDS: * Update the organization of derivatives folder (same for ECOG tutorial) * Add review of literature for the resting state MEG * Download example datasets directly from the OMEGA repository * New tutorials: <<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 * 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 * 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 * 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 |
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| * Import anatomy folder menu crashes on MacOSX 10.8.5 / Matlab 2013b * Record tab: Text of epoch number is too big on MacOS * Menu "Use default EEG cap" doesn't work for a multiple selection (setting the same EEG cap for several subjects) * in_bst_data_multi: If trials have different sizes, output is random (the one of the first file) * 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 * Image viewer has some bugs on some systems * Screen capture for reports never works: Find another solution * Screen capture when there is a fading effect in the window manager: captures the window * Close figure with coherence results should hide the "frequency" slider * Problems growing scouts on merged surfaces (Emily) * Edit scout in MRI: small modifications cause huge increase of the scout size |
* MacOS 10.14.5 (Mojave): * Toggle buttons do not show their status * Panel Record: Text is too large for text boxes * Image viewer: * Difficult to get to 100% * Buggy on some systems * 2DLayout: * (TF) Units are weird with % values * (TF) Difficult to navigate in frequencies: Scaling+changing frequency resets the scaling * Progress bar: * Doesn't close properly on some Linux systems * Focus requests change workspace when processing constantly (Linux systems) * MacOS bugs: * Buttons {Yes,No,Cancel} listed backwards * Record tab: Text of epoch number is too big * Colormap menus: Do not work well on compiled MacOSX 10.9.5 and 10.10 * Canolty maps computation: Fix progress bar == 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/ |
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| * Use Matlab Coder to optimize some processes: Bandpass filter, sinusoid removal * Hide Java panels instead of deleting them * mri2scs: convert arguments to meters |
* Replace all calls to inpolyhd.m with inpolyhedron.m (10x faster) * 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) * Processes with "radio" and "radio_line" options: Replace with "radio_label" and "radio_linelabel" * Interpolations: Use scatteredInterpolant, griddedInterpolant, triangulation.nearestNeighbor (2014b) |
| Line 217: | Line 333: |
| * Shared kernels: do the "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 * Line smoothing / anti-aliasing (time series figures) * Fix all the 'todo dba' in the code |
* Shared kernels: "get bad channels" operation in a different way (reading all the files is too slow) |
What's next
A roadmap to the future developments of Brainstorm.
Contents
Recordings
- Default montages for EEG (sensor selection)
- Sleep scoring wish list (Emily C):
- Configurable horizontal lines (for helping detecting visually some thresholds)
- Mouse ruler: Measure duration and amplitude by dragging the mouse.
- Automatic spindle detector
https://neuroimage.usc.edu/forums/t/page-overlap-while-reviewing-raw-file-a-way-to-set-to-0/11229/13
- RAW file viewer speed:
- Downsample before filtering? (attention to the filter design)
- Add parameter to make the visual downsampling more or less aggressive
- Pre-load next page of recordings
- Keep the filter specifications in memory instead of recomputing for every page
- MEG/EEG registration: Apply the same transformation to multiple runs
- Create heat maps: Maybe with matlab function heatmap?
BioSemi: Add menu "Convert naming system" to rename channels into 10-10 (A1=>FPz)
Interface
Add a warning when computing a forward model with > 100000 sources (check selection)
- Snapshot: Save as image / all figures (similar to Movie/all figure)
Generalize the use of the units (field .DisplayUnits): Rewrite processes to save the units correctly
- Colormaps:
- Allow brightness/contrast manipulations on the custom colormaps
- Global colormap max: Should get the maximum across all the open files
- Copy figures to clipboard (with the screencapture function)
Contact sheets & movies: use average of time windows instead of single instants, for each picture.
- Contact sheets: Allow explicit list of times in input (+ display as in MNE-Python with TS)
- Display CTF coils: Show discs instead of squares
- Progress bar: Add a "Cancel" button
- Error message: Add a link to report directly the bug on the forum
Reorganize menus (Dannie's suggestion):
Connectivity
- Thresholding and stat tests for connectivity matrices
- Connectivity on unconstrained sources: "Default signal extraction for volume grids should be the time series of the first principal component of the triplet signals after each has been zero-meaned" (SB)
- Connect NxN display:
- Graph on sensors: does not place the sensors correctly in space
- Display as image: Add legend of the elements along X and Y axis
- Display as time series: Display warning before trying to open too many signals
- Time-resolved correlation/coherence: Display as time bands
- Weighted Phase Lag Index (WPLI)
Coherence: Average cross-spectra instead of concatenating epochs (to avoid discontinuities)
Explore inter-trial approaches (Esther refers to chronux toolbox)- Granger: Check for minimum time window (Esther: min around 500-1000 data points)
- PLV:
- Remove evoked
- Add time integration
- Unconstrained sources
- Add warning when running of short windows (because of filters)
Processes
- Plugin manager:
- Export all the software environment to a .zip file (brainstorm + all plugins)
- Generate fully reproducible scripts, including all the interactive/graphical parts:
- Saving all the interactive operations as process calls
- Improving the pipeline editor to handle loops over data files or subjects
- Keeping a better track of the provenance of all the data (History, uniform file names)
- Add MNE-Python functions:
- scikit-learn classifiers
https://neuroimage.usc.edu/forums/t/ica-on-very-long-eeg/23556/4
https://neuroimage.usc.edu/forums/t/best-way-to-export-to-mne-python/12704/3
- Reproduce other tutorials / examples
Point-spread functions (PSFs) and cross-talk functions: https://mne.tools/stable/auto_examples/inverse/plot_psf_ctf_vertices.html#sphx-glr-auto-examples-inverse-plot-psf-ctf-vertices-py
Spatial resolution metrics in source space:
https://mne.tools/stable/auto_examples/inverse/plot_resolution_metrics.html#sphx-glr-auto-examples-inverse-plot-resolution-metrics-py- Change the graphic renderer from Matlab
Add FieldTrip functions:
- ft_sourceanalysis:
- Check noise covariance
- Check all the options of all the methods
- Single trial reconstructions + noise covariance?
Filters?? http://www.fieldtriptoolbox.org/example/common_filters_in_beamforming
Beamformers: Save ftSource.avg.mom
http://www.fieldtriptoolbox.org/workshop/meg-uk-2015/fieldtrip-beamformer-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:
- Use CUDA for speeding up some operations (filtering, wavelets, etc)
- Use Matlab Coder to optimize: Wavelets, bandpass filter, sinusoid removal
- Pipeline editor:
- Bug: After "convert to continuous", the time of the following processes should change
- Add loops over subjects/conditions/trial groups
- Events: Allow selection from a drop-down list (similar to option "channelname" in panel_process_selection)
ITC: Inter-trial coherence (see MNE reports for group tutorial)
http://www.sciencedirect.com/science/article/pii/S1053811916304232- ICA:
Add Alex's suggestions: https://neuroimage.usc.edu/forums/t/ica-on-very-long-eeg/23556/4
- Add methods: SOBI, Fastica, AMICA/CUDICA/CUDAAMICA (recommended by S Makeig)
- Why doesn't the ICA process converge when using 25 components in the EEG tutorial?
- Add an option to resample the signals before computing the ICA decomposition
- Exploration: Add window with spectral decomposition (useful for muscle artifacts)
- Export IC time series (and then compute their spectrum): solves the problem above
Comparison JADE/Infomax:
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0030135Dimension reduction with PCA adds artifacts: Not done by default in EEGLAB
Contact: Stephen Shall Jones ( shall-jones@infoscience.otago.ac.nz )
Student Carl Leichter detailed this in his thesis- Import ICA matrices available in EEGLAB .set files
EEGLAB recommends ICA + trial rejection + ICA again: Impossible right now with Brainstorm
(http://sccn.ucsd.edu/wiki/Chapter_09:_Decomposing_Data_Using_ICA)ICA+machine learning: https://www.ncbi.nlm.nih.gov/pubmed/28497769
Automated artifact rejection: https://arxiv.org/abs/1612.08194
Use EYE-EEG: EEGLAB toolbox for eye-tracker guided ICA (Olaf Dimigen): http://www2.hu-berlin.de/eyetracking-eeg/
- SSP:
Display warning if changing the ChannelFlag while there is a Projector applied
Remove line noise: http://www.nitrc.org/projects/cleanline
- Time-frequency:
- Optimization: bst_timefreq (around l.136), remove evoked in source space: Average should be computed in sensor space instead of source space (requested by Dimitrios)
Short-time Fourier transform: http://www.mikexcohen.com/lectures.html
- Hilbert with time bands very slow on very long files (eg. 3600s at 1000Hz) because the time vector is still full (10^7 values): save compressed time vector instead.
- When normalizing with baseline: Propagate with the edge effects marked in TFmask
- Allow running TF on montages
- Review continuous files in time-frequency space (for epilepsy)
- Bug when computing TF on constrained and unconstrained scouts at the same time (in mixed head models for instance): uses only the constrained information and doesn't sum the 3 orientations for the unconstrained regions.
Source modeling
- Unconstrained to flat: Default PCA for stat and connectivity?
Reproduce results in "Simultaneous human intracerebral stimulation and HD-EEG, ground-truth for source localization methods": https://www.nature.com/articles/s41597-020-0467-x
- eLORETA instead of sLORETA?
https://neuroimage.usc.edu/forums/t/compute-eeg-sources-with-sloreta/13425/6
"eLORETA algorithm is available in the MEG/EEG Toolbox of Hamburg (METH)": https://www.biorxiv.org/content/biorxiv/early/2019/10/17/809285.full.pdf
Sensitivity maps: https://mne.tools/stable/auto_examples/forward/plot_forward_sensitivity_maps.html
- 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
Menu Sources > Maximum value: Doesn't work with volume or mixed head models
- Mixed head models:
- Bug when displaying interpolated in MRI viewer
- Volume grid:
- Optimize: 3D display (better than 9x9 cubes)
- Optimize: vol_dilate (with 26 neighbors)
- 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 spectrum scouts (PSD plots when clicking on "Display scouts" on PSD/full cortex)
Anatomy
FastSurfer: https://deep-mi.org/research/fastsurfer/
SimNIBS: Replace HEADRECO with CHARM (headreco will be removed in SimNIBS 4)
- Infant templates: Add electrodes positions (at least 10-10)
Neurodev MRI database: https://jerlab.sc.edu/projects/neurodevelopmental-mri-database/
- Multi-Scale Brain Parcellator (Lausanne2008):
- 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
- 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 envelopeOptimize computation interpolation MRI-surface (tess_tri_interp) => spm_mesh_to_grid
BrainSuite:
Add new labels to all BrainSuite anatomy templates
- Use same colors for left and right for anatomical atlases
- Use for volume coregistration (rigid / non-rigid)
- USCBrain: Add default electrodes positions
- FEM templates for different ages:
- 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- Allen Institute gene expression atlases: Import in Brainstorm as source maps and display on cortex
ECOG/SEEG
- Electrodes models: Import / export
- Contact positions: Import / set / detect
- New option: Align on none|inner|cortex to replace ECOG-mid
- Add history: Save modifications and transformations applied to the channel files (Marcel)
- Project contact positions across subjects or templates (Marcel)
- Add menu to import implantation channel file in imported recordings
- SEEG/ECOG: Identify contacts in resected areas / identify ROIs for each contact
- SEEG/ECOG: Identify contacts in a given anatomical region (volume scout, surface mesh, or label in a volume atlas) / allow extracting the signals from all the contacts in an ROI
- Automatic segmentation of CT:
SEEG DEETO Arnulfo 2015: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-015-0511-6
- Used routinely at Niguarda Hospital + other hospitals worldwide, reliable tool.
To be used with SEEG-assistant/3DSlicer: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-017-1545-8
ECOG Centracchio 2021: https://link.springer.com/content/pdf/10.1007/s11548-021-02325-0.pdf
Classifier on thresholded CT: https://github.com/Jcentracchio/Automated-localization-of-ECoG-electrodes-in-CT-volumes
SEEG Granados 2018 (no code shared): https://link.springer.com/content/pdf/10.1007/s11548-018-1740-8.pdf
- ECOG:
- Project and display contacts on cortex surface should consider the rigidity of the grids: Contacts cannot rotate, and distance between contacts should remain constant across runs
Method for contacts projection: https://pdfs.semanticscholar.org/f10d/6b899d851f3c4b115404298d7b997cf1d5ab.pdf
ECOG: Brain shift: When creating contact positions on a post-implantation image, the brain shift should be taken into account for creating images of the ECOG contacts on the pre-op brain => iELVis (http://ielvis.pbworks.com/w/page/116347253/FrontPage)
- Display:
- Bad channels: Contacts greyed out instead of ignored (Marcel)
- Display time in H:M:S
- Display curved SEEG electrodes
Export list of contacts with a probability of anatomical regions from various atlases: https://neuroimage.usc.edu/forums/t/seeg-contacts-anatomical-location/14756
Detection CEEP stim artifacts: Use ImaGIN code ImaGIN_StimDetect
Statistics
- ANOVA:
- Which functions to use?
- Write panel similar to Process1 and Process2 to allow the
- Output = 1 file per effect, all grouped in a node "ANOVA"
- Display several ANOVA maps (from several files) on one single figure, using a "graphic accumulator", towards which one can send any type of graphic object
Quality control before statistics, on condition averages across subjects:
mean(baseline)/std(baseline): shows bad subject quickly.Use SurfStat: Impements interesting things, like an analytical cluster-based p-value correction (Random-field theory which is used in SPM) - Peter
- Export to R or SPSS for advanced stat
Input / output
- Bug import multiple files: use same "time" for all files
- BIDS import:
- Read real fiducials (OMEGA) / transformation matrices:
- Read associated empty room
- Test all the BIDS examples
- BIDS Export:
- Add events tsv, channel tsv, EEG, iEEG
XDF import: Use FieldTRip or the EEGLAB plugin, contact Martin Bleichner (Oldenburg)
https://github.com/sccn/xdf/blob/master/xdf_sample.xdf- DICOM converter:
- Add dcm2nii (MRICron)
- Add MRIConvert
FieldTrip: Import/Export time-frequency:
- 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
- BCI2000 Input (via EEGLAB plugin)
- BST-BIN: Add compression to .bst
- Review raw on all the file formats (ASCII EEG and Cartool missing)
- SPM .mat/.dat: Fix the import of the EEG/SEEG coordinates
- Get acquisition date from files: Missing for 4D
Support for OpenJData / JNIfTI: https://github.com/brainstorm-tools/brainstorm3/issues/284
Distribution & documentation
- Tutorial OMEGA/BIDS:
- Update the organization of derivatives folder (same for ECOG tutorial)
- Add review of literature for the resting state MEG
- Download example datasets directly from the OMEGA repository
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
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
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
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
Current bugs
- MacOS 10.14.5 (Mojave):
- Toggle buttons do not show their status
- Panel Record: Text is too large for text boxes
- Image viewer:
- Difficult to get to 100%
- Buggy on some systems
- 2DLayout:
- (TF) Units are weird with % values
- (TF) Difficult to navigate in frequencies: Scaling+changing frequency resets the scaling
- Progress bar:
- Doesn't close properly on some Linux systems
- Focus requests change workspace when processing constantly (Linux systems)
- MacOS bugs:
- Buttons {Yes,No,Cancel} listed backwards
- Record tab: Text of epoch number is too big
- Colormap menus: Do not work well on compiled MacOSX 10.9.5 and 10.10
- Canolty maps computation: Fix progress bar
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)
- 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)
- 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)