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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 ==== * New tools for exploring EEG recordings (custom montages, faster viewer) * Full EEG/epilepsy online tutorial * 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: * Pre-load next page of recordings * Allow multiple RAW windows(columns display) * Screen setups: save configuration of windows * Time scale: define in fixed s/mm (like the CTF tools) * Secondary windows: display length of time selection * If "Use SSP " option is selected, automatically select "Remove baseline" and "CTF compensations" * Documentation: Add definition of bad segments * Set the amplitude scale for the time series * 2DLayout: Doesn't work when changing page => need refresh of GlobalData.Preferences.TopoLayoutOptions.TimeWindow * EEG reference/storage:<<BR>> * Intracranial electrodes: Define and display in the MRI viewer + 3D figures * Re-reference recordings * 2D topo plots: Display bipolar montages with electrodes positions = average of the two electrodes * Bad locations: indicate with [NaN NaN NaN] instead of [0 0 0] * Location of bipolar electrodes: Save the 2 positions in the channel file, with weights=[1 -1] * 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 * Colormaps: <<BR>> * 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 |
* Review signals in time-frequency space * Events processes: Select events names from a list instead of having to type them * Display CTF coils: Show discs instead of squares * Sleep scoring wish list (Emily C): * Configurable horizontal lines (for helping detecting visually some thresholds) * Mouse ruler: Measure amplitude by dragging the mouse. * Automatic spindle detector * https://neuroimage.usc.edu/forums/t/page-overlap-while-reviewing-raw-file-a-way-to-set-to-0/11229/13 * RAW file viewer speed (Low priority) :<<BR>> * Consider to change to a format that is faster to read * Add parameter to make the visual downsampling more or less aggressive * Keep the filter specifications in memory instead of recomputing for every page<<BR>>(Nice to have) * BioSemi: Add menu "Convert naming system" to rename channels into 10-10 (A1=>FPz) * Simulations: https://github.com/lrkrol/SEREEGA(Low priority) == ECOG/SEEG == * https://www.sciencedirect.com/science/article/pii/S1053811922005559 * Display (high-priority)(Part SEEG grant): * Group display: Overlay multiple channel files in the same figure, coloring contacts by subject/ROI/Cluster/Electrode name * https://neuroimage.usc.edu/forums/t/37617 * iEEG tab must be read-only when multiple files (hide configuration controls) * Bad channels: Contacts greyed out instead of ignored (Marcel H, Germany)<<BR>>(To diff between band and not-recorded) > Rendering of SEEG electrodes: Full surface modelling with surface mesh (see Lead-DBS models + code that generates them?) * Display time in H:M:S instead of S > If there is t0 in H:M:S instead of S > As an option in Display configuration button>x-axis * view_leadfield_sensitivity: Add closing surfaces at cortex limits * Create clusters from anatomical labels (Anne So) : * Identify contacts in a given anatomical region (volume scout, surface mesh, or label in a volume atlas) / allow extracting the signals from all the contacts in an ROI> As a process to select recordings, then Scouts from Volumen Atlas, Create cluster in channel file, then Extract time series. * Group analysis: extract clusters across subjects, display or average signals (see MIA) (Anne So) * Spike detection (Need to check for current toolboxes from scratch)(contact Nicolas R)(Mosher J)(iEEG BIDS): * https://iopscience.iop.org/article/10.1088/1741-2552/ac9259/pdf * Automatic segmentation of CT: * LeGUI: https://github.com/Rolston-Lab/LeGUI/tree/main/LeGUI<<BR>>https://neuroimage.usc.edu/forums/t/automatic-localization-of-seeg-electrodes/36302/7 * GARDEL: http://meg.univ-amu.fr/wiki/GARDEL:presentation * Discussed with Samuel and Christian (ins-amu.fr) * SEEG DEETO Arnulfo 2015: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-015-0511-6 * Used routinely at Niguarda Hospital + other hospitals worldwide, reliable tool. * To be used with SEEG-assistant/3DSlicer: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-017-1545-8 * ECOG Centracchio 2021: https://link.springer.com/content/pdf/10.1007/s11548-021-02325-0.pdf * Classifier on thresholded CT: https://github.com/Jcentracchio/Automated-localization-of-ECoG-electrodes-in-CT-volumes * SEEG Granados 2018 (no code shared): https://link.springer.com/content/pdf/10.1007/s11548-018-1740-8.pdf * ECOG: * Project and display contacts on cortex surface should consider the rigidity of the grids: Contacts cannot rotate, and distance between contacts should remain constant across runs * Method for contacts projection: https://pdfs.semanticscholar.org/f10d/6b899d851f3c4b115404298d7b997cf1d5ab.pdf * ECOG: Brain shift: When creating contact positions on a post-implantation image, the brain shift should be taken into account for creating images of the ECOG contacts on the pre-op brain => iELVis (http://ielvis.pbworks.com/w/page/116347253/FrontPage) <<BR>>Normalization MNI? solutions with FieldTrip? * Display CT images: Better brightness/contrast adjustment: https://neuroimage.usc.edu/forums/t/automatic-localization-of-seeg-electrodes/36302/8 Range of values is way diff than ones from MRI. Current color maps are not suitable for CT, need to be improved.Together with processing of CT to get electrode positions. * Detection CCEP stim artifacts: Use ImaGIN code ImaGIN_StimDetect https://f-tract.eu/software/imagin/ == Pre-processing == * process_detectbad: * Allow on raw files (for bad channels only) * Add detection on derivative of the signal (see EEGLAB) * Document in tutorial Bad channels * PREP pipeline / EEGLAB (Bigdely-Shamlo 2015) * Improve bad channel/trial detection: * ft_artifact_threshold and ft_rejectartifact * MNE-Python * EEGLAB * Integrate with EYE-EEG (Olaf Dimigen) * Reproduce tutorial: https://www.eyetracking-eeg.org/tutorial.html * Create EYE-EEG plugin + processes (Raphael Lambert) * Process: Detect sacades (extended events) + fixations * Improved ICA * Eye-movement related potentials * Use it to guide ICA: http://www2.hu-berlin.de/eyetracking-eeg/ * ICA: <<BR>> * Automatic classification: ICLabel: https://neuroimage.usc.edu/forums/t/automatic-eeg-ic-ica-classification-for-brainstorm/33785 * Exploration: Add window with spectral decomposition (useful for muscle artifacts) * Export IC time series (and then compute their spectrum): solves the problem above * Import ICA matrices available in EEGLAB .set files * ICA+machine learning: https://www.ncbi.nlm.nih.gov/pubmed/28497769 * Automated artifact rejection: https://arxiv.org/abs/1612.08194 * Spectral representation of ICs * SSP: * Display warning if changing the ChannelFlag while there is a Projector applied * File format: * Add support to read GDF file format https://github.com/donnchadh/biosig/blob/master/biosig/t200_FileAccess/sload.m * <<BR>> * == Reproducibility toolbox == * Generate fully reproducible scripts, including all the interactive/graphical parts * Record all GUI actions as script calls * Import window: Add button to create the corresponding processing pipeline (to generate script or to edit additional options). * Adding the list of plugins to the reports * Better provenance: History fields, uniform file names... == Interface == * Add a warning when computing a forward model with > 100000 sources (check selection) * Colormaps: Global colormap max: Should get the maximum across all the open files * Snapshot: * Save as image / all figures (similar to Movie/all figure) * Contact sheets & movies: use average of time windows instead of single instants, for each picture. * Contact sheets: Allow explicit list of times in input (+ display as in MNE-Python with TS) == Database == * Save iHeadModel somewhere in the datbase structure * Generalize the use of the units (field .DisplayUnits): Save in source files |
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* Figures: interaction with sensor selection / scouts selections * Display NxN as 1xN * Adapt colormaps for correlation (min and max properties) * PLV: Add a time integration * Correlation with delays? * Work on progress bars * Circle plot: Display Neuromag sensors * Event-related coherence? |
* Define names and unit labels for each connectivity metric * Null models: (Bratislav M) https://www.nature.com/articles/s41583-022-00601-9 * {{attachment:connect_toolboxes.jpg}} * Connect NxN display: * Graph on sensors: Place M/EEG sensors by location, not by channel order * Display as image: Add legend of the elements along X and Y axis * Display as time series: Display warning before trying to open too many signals * Optimize display: use surface() instead of line() for links? (as in figure_3d/PlotFibers) * Time-resolved correlation/coherence: Display as time bands (as done in wavelet, to have same time axis as data) |
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* Add MNE-Python functions: * scikit-learn classifiers * BEM single layer (John wants to test it) * https://neuroimage.usc.edu/forums/t/best-way-to-export-to-mne-python/12704/3 * Reproduce tutorials / examples from FieldTrip and MNE-Python: * FieldTrip ECOG tutorial: http://www.fieldtriptoolbox.org/tutorial/human_ecog * Reproduce tutorials from MNE-Python: https://martinos.org/mne/stable/tutorials.html * Spatial resolution metrics in source space:<<BR>>https://mne.tools/stable/auto_examples/inverse/plot_resolution_metrics.html#sphx-glr-auto-examples-inverse-plot-resolution-metrics-py * Change the graphic renderer from Matlab * Chronux toolbox : http://chronux.org/ * Add FieldTrip functions: * ft_sourceanalysis: * Check noise covariance * Check all the options of all the methods * Single trial reconstructions + noise covariance? * Filters?? http://www.fieldtriptoolbox.org/example/common_filters_in_beamforming * Beamformers: Save ftSource.avg.mom <<BR>>http://www.fieldtriptoolbox.org/workshop/meg-uk-2015/fieldtrip-beamformer-demo * http://www.natmeg.se/ft_beamformer/beamformer.html * http://www.fieldtriptoolbox.org/tutorial/beamformingextended * Baseline? Two inputs? * ft_prepare_heamodel: Add support from BEM surfaces from the Brainstorm database * 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 * Remove line noise: http://www.nitrc.org/projects/cleanline |
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* Frequency bands: extended syntax (ex: [2 3 4], 10:5:90, ...) * Scouts values for timefreq on surfaces * 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 * When processing multiple files: waitbar is not behaving well * Improve interface for SSP on imported recordings * Define SSP from one time point * 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 * Spectrum figure: use bst_selection == 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 |
* Optimization: bst_timefreq (around l.136), remove evoked in source space: Average should be computed in sensor space instead of source space (requested by Dimitrios) * Short-time Fourier transform: http://www.mikexcohen.com/lectures.html * Hilbert with time bands very slow on very long files (eg. 3600s at 1000Hz) because the time vector is still full (10^7 values): save compressed time vector instead. * When normalizing with baseline: Propagate with the edge effects marked in TFmask * Allow running TF on montages * Bug when computing TF on constrained and unconstrained scouts at the same time (in mixed head models for instance): uses only the constrained information and doesn't sum the 3 orientations for the unconstrained regions. * requested feature from the forum: * * https://neuroimage.usc.edu/forums/t/event-export-and-process-find-maximum-value-amplitude/41911/2 * * https://neuroimage.usc.edu/forums/t/custom-process-that-involves-merging-of-channels/40638 * * https://neuroimage.usc.edu/forums/t/swloreta-for-source-localization/41882/4 == Anatomy == * Display parcellation values (matrices) in 3D and 2D. * https://github.com/dutchconnectomelab/Simple-Brain-Plot * Scouts * Import SimNIBS4: Use final_tissues_LUT.txt instead of fixed list of tissues: https://neuroimage.usc.edu/forums/t/removing-a-lesioned-area/38414/20 * Simple-brain-plot: https://github.com/dutchconnectomelab/Simple-Brain-Plot * MNI normalization: More options: * DARTEL / SHOOT * BrainSuite (wait for Anand) * Import from SimNIBS (Conform2MNI_nonl.nii.gz, MNI2Conform_nonl.nii.gz) * MRI Viewer: * Adjust CT contrast better: https://neuroimage.usc.edu/forums/t/automatic-localization-of-seeg-electrodes/36302/10 * Pan in zoomed view (shift + click + move?) * Zoom in/out with mouse (shift + scroll?) * Ruler tool to measure distances * Display scouts as additional volumes * Render surface envelope in the MRI as a thin line instead of the full interpolation matrix<<BR>>Or use inpolyhedron to get a surface mask and then erode it to get the volume envelope * Surface>Volume interpolation: Use '''spm_mesh_to_grid''' instead of tess_tri_interp * Defacing: * https://afni.nimh.nih.gov/pub/dist/doc/htmldoc/tutorials/refacer/refacer_run.html * Removing MNI face mask using MNI coordinates (mask available ICMB152 2023b) * Bug import anatomy: Requested nVert > high-resolution cortex surface: Creates an empty cortex_0V * BrainSuite: * Use same colors for left and right for anatomical atlases * Use for volume coregistration (rigid / non-rigid) * USCBrain: Add default electrodes positions * Remove BrainSuite1 when not needed anymore * Brain2mesh: Add import of 10-10 positions * Templates for different ages: * MNI: https://www.bic.mni.mcgill.ca/ServicesAtlases/NIHPD-obj1 * Pediatric head atlases: https://www.pedeheadmod.net/pediatric-head-atlases-v1-2/ * https://iopscience.iop.org/article/10.1088/2057-1976/ab4c76 * https://www.biorxiv.org/content/biorxiv/early/2020/02/09/2020.02.07.939447.full.pdf * John Richards: https://www.nitrc.org/frs/?group_id=1361 * Neurodev database: https://jerlab.sc.edu/projects/neurodevelopmental-mri-database/ * https://openneuro.org/datasets/ds000256/versions/00002 * https://osf.io/axz5r/ * Scouts: * Display edges in the middle of the faces instead of the vertices * Parcellating volume grids: scikit-learn.cluster.Ward * Geodesic distance calculations:<<BR>>https://www.mathworks.com/matlabcentral/fileexchange/6110-toolbox-fast-marching * Improving the registration between EEG and anatomy templates: * Warping: Improve the basic alignment of the digitized electrodes on the templat, possibly with Cz and other anatomical landmarks * EEG template positions: rework using a standardized Cz position (+ other landmarks) == Forward modeling == * DUNEuro/FEM: * Add lesion mask to SimNIBS: https://simnibs.github.io/simnibs/build/html/documentation/command_line/add_tissues_to_upsampled.html#add-tissues-to-upsampled-doc * GeomtryAdapted: Buggy? * Display differences between leadfields: amplitude of difference (right-click > Compare) * Display sensitivity on FEM surface * OpenMEEG: Detect bad results + exclude from leadfield * BEM single sphere: Get implementation from MNE-Python (John Mosher) * Add eyes models to attract eye activity (Put a dipole in each eye) |
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* Dipole fitting * EEG Source modeling: Manage references and bipolar montages properly * Visualize Beamformer results (contact Zainab Fatima): * Read CTF SAM .svl * Create new file type in the database * Display as layers in the MRI viewer * Unconstrained sources: * Compute unconstrained and then project on the normal ? * Difference and stat should be: norm(A) - norm(B) * Stat and connectivity: what to do? (re-send email John+Sylvain) * Overlapping spheres: improve the estimation of the spheres for the frontal lobes |
* Reproduce results in "Simultaneous human intracerebral stimulation and HD-EEG, ground-truth for source localization methods": https://www.nature.com/articles/s41597-020-0467-x * eLORETA instead of sLORETA? * https://neuroimage.usc.edu/forums/t/compute-eeg-sources-with-sloreta/13425/6 * https://neuroimage.usc.edu/forums/t/loreta-and-source-localization/30525 * "eLORETA algorithm is available in the MEG/EEG Toolbox of Hamburg (METH)": https://www.biorxiv.org/content/biorxiv/early/2019/10/17/809285.full.pdf * https://github.com/brainstorm-tools/brainstorm3/issues/114 * Point-spread functions (PSFs) and cross-talk functions: https://mne.tools/stable/auto_examples/inverse/plot_psf_ctf_vertices.html#sphx-glr-auto-examples-inverse-plot-psf-ctf-vertices-py https://www.biorxiv.org/content/biorxiv/early/2019/06/18/672956.full.pdf * https://github.com/olafhauk/EEGMEGResolutionAtlas * Dipoles: * Display dipoles in MRI viewer * panel_dipoles: Doesn't work with multiple figures (SOLVED?) * Project sources: Very poor algorithm to project sub-cortical regions and cerebellum * Maximum: * Menu Sources > Maximum value: Doesn't work with volume or mixed head models * Panel Get coordinates: Add button "find maximum" * Sources on surface: Display peak regions over time (time = color) => A.Gramfort |
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* Scouts 3D * Test volume sources with all the subsequent processes (timefreq, stat...) * Optimize: 3D display (better that 9x9 cubes) |
* Optimize: 3D display (better than 3x3 cubes) |
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* 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' ) * Sources on surface: Display peak regions over time (time = color) => A.Gramfort * Simulation: synthesize pseudo data-files from a cortex patch (duration, amplitude, noise) * Calculate !ImagingKernel * Gain for a scout == Anatomy == * Scouts: * Mix constrained/unconstrained/volume sources, using the "Source model" atlas * Display edges in the middle of the faces instead of the vertices * Project scouts betweens subjects and between hemispheres * Display scouts in a tree: hemisphere, region, subregion * Downsample to atlas: allow on timefreq/connect files * 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? |
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* ANOVA: Use LENA functions | * Stat on unconstrained sources? * Stat/time series: Hide lines going down to zero (Dimitrios: https://neuroimage.usc.edu/forums/t/common-source-activation-across-subjects-and-conditions/1152/21) * Cluster stat: Add frequency selection option * ANOVA: * Write panel similar to Process1 and Process2 |
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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 * t-test on volume sources * Create icons for Stat/PAC, Stat/Sprectrum, etc. * One sample t-test across subjects |
* Multivariate stim-response analysis: https://github.com/mickcrosse/mTRF-Toolbox |
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* EEG File formats: * EEG !CeeGraph * EGI: Finish support for epoched files (formats 3,5,7) * !FieldTrip structures: In / Out * BCI2000 Input (via EEGLAB plugin) * Export TF maps to SPM / volumes * EEGLAB import: Selection of conditions in script mode == Distribution & documentation == * 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 * Advanced tutorials: * EEG (How to import an EEG cap) |
* BIDS import: * Add option to process to specify the protocol name * Disable logging of sub-processes (reloading the previous report should only show process_import_bids) * Full support for iEEG and EEG * Read real fiducials (OMEGA) / transformation matrices: * https://groups.google.com/g/bids-discussion/c/BeyUeuNGl7I * https://github.com/bids-standard/bids-specification/issues/752#issuecomment-795880992 * https://github.com/brainstorm-tools/brainstorm3/issues/139 * Use BIDS-Matlab? * Test datasets: * See list of test datasets in process_import_bids.m * ds004085 / ds004473: Check response epoch + BUG with coordinate interpretation * BIDS export: * EEG, iEEG: Add events.tsv, channel.tsv, electrodes.tsv * Anatomy: Add t1w.json (including fiducials) * Use BIDS-Matlab? * EDF+ reader: Add resampling of channels with different sampling rates * Support for OpenJData / JNIfTI: https://github.com/brainstorm-tools/brainstorm3/issues/284 * DICOM converter: * Add dcm2nii (MRICron) * Add MRIConvert * SPM .mat/.dat: Fix the import of the EEG/SEEG coordinates * EEG File formats:<<BR>> * XLTEK: https://github.com/danielmhanover/OpenXLT * Persyst .lay: https://github.com/ieeg-portal/Persyst-Reader * Nervus .eeg: https://github.com/ieeg-portal/Nervus-Reader * Biopac .acq: https://github.com/ieeg-portal/Biopac-Reader * BCI2000 Input (via EEGLAB plugin) * 4D file format: * Use reader from MNE-Python: mne.io.read_raw_kit (skip Yokogawa slow library) * Reference gradiometers: Keep the orientation of the first or second coil? * Reference gradiometers: Add the sensor definition from coil_def.dat * Validate with phantom recordings that noise compensation is properly taken into account * The noise compensation is considered to be always applied on the recordings, not sure this assumption is always correct * 4D phantom tutorial (JM Badier?) * BST-BIN: Add compression to .bst * MINC MRI: Add support for "voxel to world" transformation (vox2ras) similarly to .nii == Distribution == * Java-free Matlab: All references of functions below must be removed * '''JavaFrame''': screencapture.m (used for screen captures of videos) * '''Actxcontrol''': Used for video-EEG * uihtml + JavaScript callbacks? * ActiveX in .NET app? * Pure Java framce + VLC java plugin? * Other video player? * '''Javacomponent''': * mri_editMask * figure_mri * process_bandpass * List .jar files used from Matlab distribution (e.g. dom) => Check all the import calls * Cleanup GitHub repository: * https://github.com/brainstorm-tools/brainstorm3/issues/473 * Move external I/O libraries as plugins: * mne-matlab * CEDS64ML * edfimport * eeprobe * son * ricoh * yokogawa == Documentation == * All tutorial datasets in BIDS (including introduction tutorials) * Deface the MRIs of all the tutorials * Count GitHub clones in the the download stats * MNE-Python 1.0: Test and update install documentation * Tutorial OMEGA/BIDS: * Update the organization of derivatives folder (full FS folders) * Download example datasets directly from the OMEGA repository * New tutorials: <<BR>> * Other public datasets: [[https://github.com/INCF/BIDS-examples/tree/bep008_meg|https://github.com/INCF/BIDS-examples/tree/bep008_meg/]] * EEG/research * Cam-CAN database: https://camcan-archive.mrc-cbu.cam.ac.uk/dataaccess/<<BR>>(download new datasets, including maxfiltered files and manual fiducial placements) * MEG steady-state / high-gamma visual / frequency tagging * Reproduce results from "Simultaneous human intracerebral stimulation and HD-EEG, ground-truth for source localization methods": https://www.nature.com/articles/s41597-020-0467-x * Stand-alone ICA tutorial * https://archive.physionet.org/ [data and tools] |
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* 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 * Close figure with coherence results should hide the "frequency" slider |
* Image viewer: * Difficult to get to 100% * Buggy on some systems * 2DLayout: * (TF) Units are weird with % values * (TF) Difficult to navigate in frequencies: Scaling+changing frequency resets the scaling * Progress bar: * Doesn't close properly on some Linux systems (SOLVED?) * Focus requests change workspace when processing constantly (Linux systems) (SOLVED?) == Distributed computing == * Options from FieldTrip: * Loose collection of computers: https://github.com/fieldtrip/fieldtrip/tree/master/peer * Single multicore machine: https://github.com/fieldtrip/fieldtrip/tree/master/engine * Batch system: https://github.com/fieldtrip/fieldtrip/tree/master/qsub * Documentation: https://www.fieldtriptoolbox.org/faq/what_are_the_different_approaches_i_can_take_for_distributed_computing/ * PSOM: http://psom.simexp-lab.org/ * Google: https://www.youtube.com/watch?v=LLMXV3o2FT0 * https://edu.google.com/why-google/case-studies/unc-chapel-hill-gcp/ == Other interesting resources to check == neurojson: https://neurojson.org/ demo:https://neurojson.org/wiki/index.cgi?Doc/Start/User#Dynamically_downloading_caching_linked_binary_data_resources The Neuroscience Gateway (NSG) https://github.com/sccn/nsgportal/wiki https://www.nsgportal.org/index.html BIDSAPP |
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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 * bst_warp and channel_project: Use tess_parametrize_new instead of tess_parametrize * 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) |
* Replace all calls to inpolyhd.m with inpolyhedron.m (10x faster) * Interface scaling: Rewrite class IconLoader to scale only once the icons at startup instead of at each request of an icon (might improve the speed of the rendering of the tree) * Processes with "radio" and "radio_line" options: Replace with "radio_label" and "radio_linelabel" |
What's next
A roadmap to the future developments of Brainstorm.
Contents
Recordings
- Review signals in time-frequency space
- Events processes: Select events names from a list instead of having to type them
- Display CTF coils: Show discs instead of squares
- Sleep scoring wish list (Emily C):
- Configurable horizontal lines (for helping detecting visually some thresholds)
- Mouse ruler: Measure amplitude by dragging the mouse.
- Automatic spindle detector
https://neuroimage.usc.edu/forums/t/page-overlap-while-reviewing-raw-file-a-way-to-set-to-0/11229/13
RAW file viewer speed (Low priority) :
- Consider to change to a format that is faster to read
- Add parameter to make the visual downsampling more or less aggressive
Keep the filter specifications in memory instead of recomputing for every page
(Nice to have)
BioSemi: Add menu "Convert naming system" to rename channels into 10-10 (A1=>FPz)
Simulations: https://github.com/lrkrol/SEREEGA(Low priority)
ECOG/SEEG
https://www.sciencedirect.com/science/article/pii/S1053811922005559
- Display (high-priority)(Part SEEG grant):
- Group display: Overlay multiple channel files in the same figure, coloring contacts by subject/ROI/Cluster/Electrode name
- iEEG tab must be read-only when multiple files (hide configuration controls)
Bad channels: Contacts greyed out instead of ignored (Marcel H, Germany)
(To diff between band and not-recorded) > Rendering of SEEG electrodes: Full surface modelling with surface mesh (see Lead-DBS models + code that generates them?)Display time in H:M:S instead of S > If there is t0 in H:M:S instead of S > As an option in Display configuration button>x-axis
- view_leadfield_sensitivity: Add closing surfaces at cortex limits
- Create clusters from anatomical labels (Anne So) :
Identify contacts in a given anatomical region (volume scout, surface mesh, or label in a volume atlas) / allow extracting the signals from all the contacts in an ROI> As a process to select recordings, then Scouts from Volumen Atlas, Create cluster in channel file, then Extract time series.
- Group analysis: extract clusters across subjects, display or average signals (see MIA) (Anne So)
- Group display: Overlay multiple channel files in the same figure, coloring contacts by subject/ROI/Cluster/Electrode name
- Spike detection (Need to check for current toolboxes from scratch)(contact Nicolas R)(Mosher J)(iEEG BIDS):
- Automatic segmentation of CT:
- Discussed with Samuel and Christian (ins-amu.fr)
SEEG DEETO Arnulfo 2015: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-015-0511-6
- Used routinely at Niguarda Hospital + other hospitals worldwide, reliable tool.
To be used with SEEG-assistant/3DSlicer: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-017-1545-8
ECOG Centracchio 2021: https://link.springer.com/content/pdf/10.1007/s11548-021-02325-0.pdf
Classifier on thresholded CT: https://github.com/Jcentracchio/Automated-localization-of-ECoG-electrodes-in-CT-volumes
SEEG Granados 2018 (no code shared): https://link.springer.com/content/pdf/10.1007/s11548-018-1740-8.pdf
- ECOG:
- Project and display contacts on cortex surface should consider the rigidity of the grids: Contacts cannot rotate, and distance between contacts should remain constant across runs
Method for contacts projection: https://pdfs.semanticscholar.org/f10d/6b899d851f3c4b115404298d7b997cf1d5ab.pdf
ECOG: Brain shift: When creating contact positions on a post-implantation image, the brain shift should be taken into account for creating images of the ECOG contacts on the pre-op brain => iELVis (http://ielvis.pbworks.com/w/page/116347253/FrontPage)
Normalization MNI? solutions with FieldTrip?
Display CT images: Better brightness/contrast adjustment: https://neuroimage.usc.edu/forums/t/automatic-localization-of-seeg-electrodes/36302/8 Range of values is way diff than ones from MRI. Current color maps are not suitable for CT, need to be improved.Together with processing of CT to get electrode positions.
Detection CCEP stim artifacts: Use ImaGIN code ImaGIN_StimDetect https://f-tract.eu/software/imagin/
Pre-processing
- process_detectbad:
- Allow on raw files (for bad channels only)
- Add detection on derivative of the signal (see EEGLAB)
- Document in tutorial Bad channels
- PREP pipeline / EEGLAB (Bigdely-Shamlo 2015)
- Improve bad channel/trial detection:
- ft_artifact_threshold and ft_rejectartifact
- MNE-Python
- EEGLAB
- Integrate with EYE-EEG (Olaf Dimigen)
Reproduce tutorial: https://www.eyetracking-eeg.org/tutorial.html
- Create EYE-EEG plugin + processes (Raphael Lambert)
- Process: Detect sacades (extended events) + fixations
- Improved ICA
- Eye-movement related potentials
Use it to guide ICA: http://www2.hu-berlin.de/eyetracking-eeg/
ICA:
Automatic classification: ICLabel: https://neuroimage.usc.edu/forums/t/automatic-eeg-ic-ica-classification-for-brainstorm/33785
- Exploration: Add window with spectral decomposition (useful for muscle artifacts)
- Export IC time series (and then compute their spectrum): solves the problem above
- Import ICA matrices available in EEGLAB .set files
ICA+machine learning: https://www.ncbi.nlm.nih.gov/pubmed/28497769
Automated artifact rejection: https://arxiv.org/abs/1612.08194
- Spectral representation of ICs
- SSP:
Display warning if changing the ChannelFlag while there is a Projector applied
- File format:
- Add support to read GDF file format
https://github.com/donnchadh/biosig/blob/master/biosig/t200_FileAccess/sload.m
Reproducibility toolbox
- Generate fully reproducible scripts, including all the interactive/graphical parts
- Record all GUI actions as script calls
- Import window: Add button to create the corresponding processing pipeline (to generate script or to edit additional options).
- Adding the list of plugins to the reports
- Better provenance: History fields, uniform file names...
Interface
Add a warning when computing a forward model with > 100000 sources (check selection)
- Colormaps: Global colormap max: Should get the maximum across all the open files
- Snapshot:
- Save as image / all figures (similar to Movie/all figure)
Contact sheets & movies: use average of time windows instead of single instants, for each picture.
- Contact sheets: Allow explicit list of times in input (+ display as in MNE-Python with TS)
Database
- Save iHeadModel somewhere in the datbase structure
Generalize the use of the units (field .DisplayUnits): Save in source files
Connectivity
- Define names and unit labels for each connectivity metric
Null models: (Bratislav M) https://www.nature.com/articles/s41583-022-00601-9
- Connect NxN display:
- Graph on sensors: Place M/EEG sensors by location, not by channel order
- Display as image: Add legend of the elements along X and Y axis
- Display as time series: Display warning before trying to open too many signals
- Optimize display: use surface() instead of line() for links? (as in figure_3d/PlotFibers)
- Time-resolved correlation/coherence: Display as time bands (as done in wavelet, to have same time axis as data)
Processes
- Add MNE-Python functions:
- scikit-learn classifiers
- BEM single layer (John wants to test it)
https://neuroimage.usc.edu/forums/t/best-way-to-export-to-mne-python/12704/3
Reproduce tutorials / examples from FieldTrip and MNE-Python:
FieldTrip ECOG tutorial: http://www.fieldtriptoolbox.org/tutorial/human_ecog
Reproduce tutorials from MNE-Python: https://martinos.org/mne/stable/tutorials.html
Spatial resolution metrics in source space:
https://mne.tools/stable/auto_examples/inverse/plot_resolution_metrics.html#sphx-glr-auto-examples-inverse-plot-resolution-metrics-py- Change the graphic renderer from Matlab
Chronux toolbox : http://chronux.org/
Add FieldTrip functions:
- ft_sourceanalysis:
- Check noise covariance
- Check all the options of all the methods
- Single trial reconstructions + noise covariance?
Filters?? http://www.fieldtriptoolbox.org/example/common_filters_in_beamforming
Beamformers: Save ftSource.avg.mom
http://www.fieldtriptoolbox.org/workshop/meg-uk-2015/fieldtrip-beamformer-demohttp://www.fieldtriptoolbox.org/tutorial/beamformingextended
- Baseline? Two inputs?
- ft_prepare_heamodel: Add support from BEM surfaces from the Brainstorm database
ft_volumereslice: http://www.fieldtriptoolbox.org/faq/how_change_mri_orientation_size_fov
- ft_freqanalysis
- ft_combineplanar
- 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/S1053811916304232Remove line noise: http://www.nitrc.org/projects/cleanline
- Time-frequency:
- Optimization: bst_timefreq (around l.136), remove evoked in source space: Average should be computed in sensor space instead of source space (requested by Dimitrios)
Short-time Fourier transform: http://www.mikexcohen.com/lectures.html
- Hilbert with time bands very slow on very long files (eg. 3600s at 1000Hz) because the time vector is still full (10^7 values): save compressed time vector instead.
- When normalizing with baseline: Propagate with the edge effects marked in TFmask
- Allow running TF on montages
- Bug when computing TF on constrained and unconstrained scouts at the same time (in mixed head models for instance): uses only the constrained information and doesn't sum the 3 orientations for the unconstrained regions.
- requested feature from the forum:
* https://neuroimage.usc.edu/forums/t/event-export-and-process-find-maximum-value-amplitude/41911/2
* https://neuroimage.usc.edu/forums/t/custom-process-that-involves-merging-of-channels/40638
* https://neuroimage.usc.edu/forums/t/swloreta-for-source-localization/41882/4
Anatomy
- Display parcellation values (matrices) in 3D and 2D.
Import SimNIBS4: Use final_tissues_LUT.txt instead of fixed list of tissues: https://neuroimage.usc.edu/forums/t/removing-a-lesioned-area/38414/20
Simple-brain-plot: https://github.com/dutchconnectomelab/Simple-Brain-Plot
- MNI normalization: More options:
- DARTEL / SHOOT
BrainSuite (wait for Anand)
- Import from SimNIBS (Conform2MNI_nonl.nii.gz, MNI2Conform_nonl.nii.gz)
- MRI Viewer:
Adjust CT contrast better: https://neuroimage.usc.edu/forums/t/automatic-localization-of-seeg-electrodes/36302/10
- Pan in zoomed view (shift + click + move?)
- Zoom in/out with mouse (shift + scroll?)
- Ruler tool to measure distances
- Display scouts as additional volumes
Render surface envelope in the MRI as a thin line instead of the full interpolation matrix
Or use inpolyhedron to get a surface mask and then erode it to get the volume envelopeSurface>Volume interpolation: Use spm_mesh_to_grid instead of tess_tri_interp
- Defacing:
https://afni.nimh.nih.gov/pub/dist/doc/htmldoc/tutorials/refacer/refacer_run.html
- Removing MNI face mask using MNI coordinates (mask available ICMB152 2023b)
Bug import anatomy: Requested nVert > high-resolution cortex surface: Creates an empty cortex_0V
BrainSuite:
- Use same colors for left and right for anatomical atlases
- Use for volume coregistration (rigid / non-rigid)
- USCBrain: Add default electrodes positions
Remove BrainSuite1 when not needed anymore
- Brain2mesh: Add import of 10-10 positions
- Templates for different ages:
MNI: https://www.bic.mni.mcgill.ca/ServicesAtlases/NIHPD-obj1
Pediatric head atlases: https://www.pedeheadmod.net/pediatric-head-atlases-v1-2/
https://www.biorxiv.org/content/biorxiv/early/2020/02/09/2020.02.07.939447.full.pdf
John Richards: https://www.nitrc.org/frs/?group_id=1361
Neurodev database: https://jerlab.sc.edu/projects/neurodevelopmental-mri-database/
- Scouts:
- Display edges in the middle of the faces instead of the vertices
- Parcellating volume grids: scikit-learn.cluster.Ward
Geodesic distance calculations:
https://www.mathworks.com/matlabcentral/fileexchange/6110-toolbox-fast-marching- Improving the registration between EEG and anatomy templates:
- Warping: Improve the basic alignment of the digitized electrodes on the templat, possibly with Cz and other anatomical landmarks
- EEG template positions: rework using a standardized Cz position (+ other landmarks)
Forward modeling
- DUNEuro/FEM:
Add lesion mask to SimNIBS: https://simnibs.github.io/simnibs/build/html/documentation/command_line/add_tissues_to_upsampled.html#add-tissues-to-upsampled-doc
GeomtryAdapted: Buggy?
Display differences between leadfields: amplitude of difference (right-click > Compare)
- Display sensitivity on FEM surface
- OpenMEEG: Detect bad results + exclude from leadfield
- BEM single sphere: Get implementation from MNE-Python (John Mosher)
- Add eyes models to attract eye activity (Put a dipole in each eye)
Source modeling
Reproduce results in "Simultaneous human intracerebral stimulation and HD-EEG, ground-truth for source localization methods": https://www.nature.com/articles/s41597-020-0467-x
- eLORETA instead of sLORETA?
https://neuroimage.usc.edu/forums/t/compute-eeg-sources-with-sloreta/13425/6
https://neuroimage.usc.edu/forums/t/loreta-and-source-localization/30525
"eLORETA algorithm is available in the MEG/EEG Toolbox of Hamburg (METH)": https://www.biorxiv.org/content/biorxiv/early/2019/10/17/809285.full.pdf
Point-spread functions (PSFs) and cross-talk functions: https://mne.tools/stable/auto_examples/inverse/plot_psf_ctf_vertices.html#sphx-glr-auto-examples-inverse-plot-psf-ctf-vertices-py https://www.biorxiv.org/content/biorxiv/early/2019/06/18/672956.full.pdf
- Dipoles:
- Display dipoles in MRI viewer
- panel_dipoles: Doesn't work with multiple figures (SOLVED?)
- Project sources: Very poor algorithm to project sub-cortical regions and cerebellum
- Maximum:
Menu Sources > Maximum value: Doesn't work with volume or mixed head models
- Panel Get coordinates: Add button "find maximum"
Sources on surface: Display peak regions over time (time = color) => A.Gramfort
- Volume grid:
- Optimize: 3D display (better than 3x3 cubes)
- Optimize: vol_dilate (with 26 neighbors)
Statistics
- Stat on unconstrained sources?
Stat/time series: Hide lines going down to zero (Dimitrios: https://neuroimage.usc.edu/forums/t/common-source-activation-across-subjects-and-conditions/1152/21)
- Cluster stat: Add frequency selection option
- ANOVA:
- Write panel similar to Process1 and Process2
- Output = 1 file per effect, all grouped in a node "ANOVA"
- Display several ANOVA maps (from several files) on one single figure, using a "graphic accumulator", towards which one can send any type of graphic object
Multivariate stim-response analysis: https://github.com/mickcrosse/mTRF-Toolbox
Input / output
- BIDS import:
- Add option to process to specify the protocol name
- Disable logging of sub-processes (reloading the previous report should only show process_import_bids)
- Full support for iEEG and EEG
- Read real fiducials (OMEGA) / transformation matrices:
- Use BIDS-Matlab?
- Test datasets:
- See list of test datasets in process_import_bids.m
- ds004085 / ds004473: Check response epoch + BUG with coordinate interpretation
- BIDS export:
- EEG, iEEG: Add events.tsv, channel.tsv, electrodes.tsv
- Anatomy: Add t1w.json (including fiducials)
- Use BIDS-Matlab?
- EDF+ reader: Add resampling of channels with different sampling rates
Support for OpenJData / JNIfTI: https://github.com/brainstorm-tools/brainstorm3/issues/284
- DICOM converter:
- Add dcm2nii (MRICron)
- Add MRIConvert
- SPM .mat/.dat: Fix the import of the EEG/SEEG coordinates
EEG File formats:
Persyst .lay: https://github.com/ieeg-portal/Persyst-Reader
Nervus .eeg: https://github.com/ieeg-portal/Nervus-Reader
Biopac .acq: https://github.com/ieeg-portal/Biopac-Reader
- BCI2000 Input (via EEGLAB plugin)
- 4D file format:
- Use reader from MNE-Python: mne.io.read_raw_kit (skip Yokogawa slow library)
- Reference gradiometers: Keep the orientation of the first or second coil?
- Reference gradiometers: Add the sensor definition from coil_def.dat
- Validate with phantom recordings that noise compensation is properly taken into account
- The noise compensation is considered to be always applied on the recordings, not sure this assumption is always correct
- 4D phantom tutorial (JM Badier?)
- BST-BIN: Add compression to .bst
- MINC MRI: Add support for "voxel to world" transformation (vox2ras) similarly to .nii
Distribution
- Java-free Matlab: All references of functions below must be removed
JavaFrame: screencapture.m (used for screen captures of videos)
Actxcontrol: Used for video-EEG
uihtml + JavaScript callbacks?
- ActiveX in .NET app?
- Pure Java framce + VLC java plugin?
- Other video player?
Javacomponent:
- mri_editMask
- figure_mri
- process_bandpass
List .jar files used from Matlab distribution (e.g. dom) => Check all the import calls
Cleanup GitHub repository:
- Move external I/O libraries as plugins:
- mne-matlab
- CEDS64ML
- edfimport
- eeprobe
- son
- ricoh
- yokogawa
Documentation
- All tutorial datasets in BIDS (including introduction tutorials)
- Deface the MRIs of all the tutorials
Count GitHub clones in the the download stats
- MNE-Python 1.0: Test and update install documentation
- Tutorial OMEGA/BIDS:
- Update the organization of derivatives folder (full FS folders)
- Download example datasets directly from the OMEGA repository
New tutorials:
Other public datasets: https://github.com/INCF/BIDS-examples/tree/bep008_meg/
- EEG/research
Cam-CAN database: https://camcan-archive.mrc-cbu.cam.ac.uk/dataaccess/<<BR>>(download new datasets, including maxfiltered files and manual fiducial placements)
- MEG steady-state / high-gamma visual / frequency tagging
Reproduce results from "Simultaneous human intracerebral stimulation and HD-EEG, ground-truth for source localization methods": https://www.nature.com/articles/s41597-020-0467-x
- Stand-alone ICA tutorial
https://archive.physionet.org/ [data and tools]
Current bugs
- Image viewer:
- Difficult to get to 100%
- Buggy on some systems
- 2DLayout:
- (TF) Units are weird with % values
- (TF) Difficult to navigate in frequencies: Scaling+changing frequency resets the scaling
- Progress bar:
- Doesn't close properly on some Linux systems (SOLVED?)
- Focus requests change workspace when processing constantly (Linux systems) (SOLVED?)
Distributed computing
Options from FieldTrip:
Loose collection of computers: https://github.com/fieldtrip/fieldtrip/tree/master/peer
Single multicore machine: https://github.com/fieldtrip/fieldtrip/tree/master/engine
Batch system: https://github.com/fieldtrip/fieldtrip/tree/master/qsub
Documentation: https://www.fieldtriptoolbox.org/faq/what_are_the_different_approaches_i_can_take_for_distributed_computing/
Other interesting resources to check
neurojson: https://neurojson.org/ demo:https://neurojson.org/wiki/index.cgi?Doc/Start/User#Dynamically_downloading_caching_linked_binary_data_resources
The Neuroscience Gateway (NSG) https://github.com/sccn/nsgportal/wiki https://www.nsgportal.org/index.html
BIDSAPP
Geeky programming details
- Replace all calls to inpolyhd.m with inpolyhedron.m (10x faster)
Interface scaling: Rewrite class IconLoader to scale only once the icons at startup instead of at each request of an icon (might improve the speed of the rendering of the tree)
- Processes with "radio" and "radio_line" options: Replace with "radio_label" and "radio_linelabel"