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== Current topics == ==== Documentation ==== * Merging the 12+3 introduction tutorials to illustrate better the latest developments ==== Source modeling ==== * Implementation of a new unified minimum norm/beamformer framework ==== Functional connectivity ==== * Significance thresholding of the connectivity matrices ==== Computation ==== * Removing the dependence to the Java interface to run in headless mode * Interacting directly with distributed computing systems ==== Compatibility ==== * Reading and writing FieldTrip structures * Calling FieldTrip functions from the pipeline <<BR>><<BR>> |
<<TableOfContents(2,2)>> |
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* Nicer 2D topographies, standardized (using FieldTrip .lay files?) * 2DLayout (recordings + TF): Use the same standard positions, too much space between sensors * 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 in the MRI viewer * 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 * 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 * Filtering: Use short FIR filters instead of IIR for bandpass, to limit the ringing<<BR>>Or allow the users to edit the LowStop parameter in bst_bandpass. * Show easily recordings maximum/values in the file viewer |
* Allow brightness/contrast manipulations on the custom colormaps * Global colormap max: Should get the maximum across all the open files |
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== Interface == * Global colormap max: Should get the maximum across all the open files |
* 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] * Thresholding the connectivity matrices * 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 * Optimize display: use surface() instead of line() for links? (as in figure_3d/PlotFibers) * 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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* Distributed processing: Brainstorm that can run without Java * Use Matlab Coder to optimize some processes: Wavelets, bandpass filter, sinusoid removal * Allow processes in Python and Java * Call FieldTrip functions from pipeline editor * Optimize opening time ofr for the menu "Add process" |
* 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/ |
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* Make average the default option | |
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* Show where the attenuation is projected:<<BR>>(sum(IK,2)-sum(SSP(k,:)*IK,2)./sum(IK,2) * Bandpass: * Rewrite without the force low-pass filter at Fs/3 * Show warning when using inappropriate high-pass filter (precision too high) * Use FIR filter * Spectral flattening (John): * Apply on the signal before any frequency/connectivity/PAC analysis * Using ARIMA(5,0,1) * Example code:<<BR>><<BR>> {{{ arm = mean(lpc(diff(detrend(Fbase')),5)); % detrend and diff PRE = filter(arm,1,diff(detrend(Fbase')))'; % apply to the data| X = filter(arm,1,diff(detrend(F')))'; X(:,1:length(arm)) = []; Time = tndx((length(arm)+2):end)/1000 - SOT; }}} * PSD: Rewrite to have the same input as coherence |
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* Interpolate the bad channels * ICA for cleaning eye movements in EEG low density (SSP don't work well) * Band-limited power envelope * Reports: * Save as HTML / PDF * Do not display the intermediate files * Pipeline editor: * Add loops over subjects/conditions/trial groups |
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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 ?) * TF scouts: should display average of TF maps * Artifact detection: * Detection of bad segments in the RAW files (Beth) * Artifact rejection like SPM: if bad in 20%, bad everywhere * Test difference between adjacent samples * 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 * Resample continuous files * Current Source Density (CSD) => Ghislaine<<BR>>http://psychophysiology.cpmc.columbia.edu/software/CSDtoolbox/index.html * Other processes:<<BR>> * 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 * Simulation: * Fix units in simulation processes => no *1e-9 in "simulate recordings" * Use "add noise" process from Hui-Ling (in Work/Dev/Divers) == Database == * Optimize startup speed * Start Brainstorm without Java (-nodesktop) * Sort files by comment * 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 * Allow matrix files to be attached to other 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. == Source modeling == * Unconstrained sources: * Unconstrained to flat: Default PCA for stat and connectivity? * Process "Scouts time series": Add PCA option (replace isnorm with radio PCA/Norm) * 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 * Mixed head models: Bug when displaying interpolated in MRI viewer * 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 * BEM single sphere: Get implementation from MNE * Volume grid: * Optimize: 3D display (better than 9x9 cubes) * Optimize: vol_dilate (with 26 neighbors) * Add eyes models to attract eye activity * Display spectrum scouts (PSD plots when clicking on "Display scouts" on PSD/full cortex) == Anatomy == * MRI segmentation: * Start BrainSuite * Start FreeSurfer * SimNIBS: Replace HEADRECO with CHARM (headreco will be removed in SimNIBS 4) * FastSurfer: https://deep-mi.org/research/fastsurfer/ * MNI normalization: More options: * DARTEL / SHOOT * BrainSuite (wait for Anand) * 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 * Surface>Volume interpolation: Use '''spm_mesh_to_grid''' instead of tess_tri_interp * Atlas switch in 3D MRI figures * ICBM152 update: * Process with FreeSurfer 7.1 + add FS atlases (Brainnettome, Schaeffer, HCP...) * Add volume atlases (+ reimport ASEG as volatlas) * Add facemask => Use for defacing with any MNI registration * Add T2? * 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 * 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 * Neurodev database: https://jerlab.sc.edu/projects/neurodevelopmental-mri-database/ * Scouts: * Display edges in the middle of the faces instead of the vertices * 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 * Geodesic distance calculations:<<BR>>https://www.mathworks.com/matlabcentral/fileexchange/6110-toolbox-fast-marching == ECOG/SEEG == * Contact positions: Import / set / detect * New option: Align on none|inner|cortex to replace ECOG-mid * Project contact positions across subjects or templates (Marcel) * Create clusters from anatomical labels: * 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 * Detection CEEP stim artifacts: Use ImaGIN code ImaGIN_StimDetect == Statistics == * Stat on connectivity? * Stat on unconstrained sources? * 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 == Input / output == * 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 * BIDS export: * Add events tsv, channel tsv, EEG, iEEG * BIDS-Matlab? * 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: * XDF: https://github.com/sccn/xdf * 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 == Distribution & documentation == * All tutorial datasets in BIDS (including introduction tutorials) * Count GitHub clones in the the download stats * Deface the MRIs of all the tutorials * 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 * Reproduce tutorials from MNE-Python: https://martinos.org/mne/stable/tutorials.html * Cam-CAN database: https://camcan-archive.mrc-cbu.cam.ac.uk/dataaccess/<<BR>>(download new datasets, including maxfiltered files and manual fiducial placements) * MEG steady-state / high-gamma visual / frequency tagging * Reproduce results from "Simultaneous human intracerebral stimulation and HD-EEG, ground-truth for source localization methods": https://www.nature.com/articles/s41597-020-0467-x * Stand-alone ICA tutorial == Current bugs == * Image viewer: * Difficult to get to 100% * Buggy on some systems * 2DLayout: * (TF) Units are weird with % values * (TF) Difficult to navigate in frequencies: Scaling+changing frequency resets the scaling * Progress bar: * Doesn't close properly on some Linux systems * Focus requests change workspace when processing constantly (Linux systems) * MacOS 10.14.5 (Mojave): * Toggle buttons do not show their status * Panel Record: Text is too large for text boxes * 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 |
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* Alternative, with less limitations: http://research.cs.wisc.edu/htcondor/ | |
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* Documentation: http://fieldtrip.fcdonders.nl/faq#distributed_computing_with_fieldtrip_and_matlab | * Documentation: https://www.fieldtriptoolbox.org/faq/what_are_the_different_approaches_i_can_take_for_distributed_computing/ |
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== Source modeling == * Finish dipole scanning (allow the tab to control multiple figures separately) * Panel Get coordinates: Add button "find maximum" * Create scout form maximum: Not available yet for mixed/volume head model. * 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 * Visualize Beamformer results: * Read CTF SAM .svl * 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 * Volume grid: * Scouts 3D * Test volume sources with all the subsequent processes (timefreq, stat...) * Optimize: 3D display (better than 9x9 cubes) * Optimize: vol_dilate (with 26 neighbors) * Magnetic extrapolation: Do the same thing with EEG * Noise covariance matrix: * Display with figure_image() * Storage of multiple noise covariance matrices (just like the head models) * Always save as full, then at inversion time, we can decide between full, heteroskedastic (diagonal) or homoskedastic (i.i.d, scalar) * Problem of having inividual trials + averages in the condition => Display warning or not? * Save nAvg in noisecov file, to make it easier to scale to other recordings * 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 * 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 * Time-frequency beamformers: * Band-pass everything in different frequency bands + Source estimation + TF * Ask data to Sarang where he sees effects that cannot be extracted with MN followed by TF * Dipole fitting: We will not implement non-linear fits, recommended use of dense volume grids * Display volume scouts and surface scouts at the same time * Process "Extract scouts time series": Add PCA option (replace isnorm with choice PCA/Norm) == Anatomy == * Project all sub-cortical structures to default anatomy * Warping: Scale option has to be fixed, it is currently very unstable * Scouts: * Display edges in the middle of the faces instead of the vertices * 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 * Co-register MRI and CT for electrodes marking in the MRI Viewer * 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? * Smooth surface: Fix little spikes to irregularities in the mesh * Menu head model > Copy to other conditions/subjects (check if applicable first) * Add cerebellum to default model generated with "Import FS anatomy" * Add eyes models to attract eye activity == Statistics == * ANOVA: Use LENA functions * 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 * 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 == Input / output == * Finish MINC/CIVET integration (finir lecture MINC2: P Bellec) * Send email to CIVET mailing list when done * FieldTrip structures: In / Out (see fieldtrip/utilities/ft_datatype_*) * EEG File formats: * EEG CeeGraph * EGI: Finish support for epoched files (formats 3,5,7) * BCI2000 Input (via EEGLAB plugin) * EEGLAB import: * Selection of conditions in script mode * Support for binary AND epoched files (now it's one or the other) * Allow epoched files with recordings saved in external files (now external files implies continuous recordings) * BST-BIN: Add compression * Review raw on all the file formats (ASCII EEG and Cartool missing) == Distribution & documentation == * Rewrite basic 12+3 tutorials: group in one series * Illustrate 2D Layout * Illustrate unconstrained sources * Cleaning threads on the forum * Add Help buttons and menus (in popups, dialog windows...) => Links to the website. * Publication list: Fold by years * Finish existing tutorials: * Dipoles * Auditory: Extend to MNE/EEGLAB/SPM * Auditory: Finish scripts * Group MEM/Epilepsy + Epilepsy tutorials * New tutorials: * MEG connectome * Scrambled faces (SPM/MNE-Python) * Describe all the processes * Statistics * Coherence (cortico-muscular ?) * Intra-cranial recordings (Average ref by groups using Comment field) * Co-register MEG runs (Beth) * Missing in the introduction tutorials: * Volume scouts * First steps: Brainstorm preferences * First steps: Temporary folder * Exploration: Clusters * Headmodel: explain the fields + how to get the constrained leadfield * Sources: Model evaluation (by simulating recordings) * Sources: Theshold min. size (not documented yet) * Time-frequency: Description of "log freq scale" option * Modify a structure manually: Export to Matlab/Import from Matlab * Missing in tutorial "Export to SPM": Add section "Compare with Brainstorm" * Missing in page "Cite Brainstorm": Add all the methods used in the software * Reference tutorials on Google scholar * Play videos on wiki with <video> tag (save videos in .ogg) == Current bugs == * Workshops: * Create scouts doesn't work: scout created on the other side of the brain * Import anatomy folder: Out of memory sometimes (restart Matlab) * Bandpass filter: Out of memory (Auditory workshop) * Bug workshop Michael (Mint 12/gnome3/linux 3.0.0-12, KWin/Mutter/Compiz) * Cannot import two .ds folders at once * Colors inverted in the PSD/TF plots (power vs. log) * Cannot type the name of a channel in "Detect ECG" * Image viewer: Difficult to get to 100% * Canolty maps computation: Fix progress bar * Smooth TF windows that contain multiple plots * Record tab: Text of epoch number is too big on MacOS * 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 when there is a fading effect in the window manager: captures the window * Close figure with coherence results should hide the "frequency" slider * Edit scout in MRI: small modifications cause huge increase of the scout size * Reports: Text size is too small with Java 1.5 (2006b-2007a) * Optimize MRI viewer with patch() instead of image() * Matlab 2014b bug with rmdir/movefile: Enter but never returns from the call * 2DLayout (time series): * Sometimes the lines are not visible * Does not work when DC offset is not removed * 2DLayout (TF): Images are too far apart with EEG 20 channels * Colormap menus: Do not work well on compiled MacOSX 10.9.5 and 10.10 |
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* Removing all the CTRL and SHIFT in the keyboard shortcuts * Hide Java panels instead of deleting them * mri2scs: convert arguments to meters * Interpolations: Use scatteredInterpolant, griddedInterpolant, triangulation.nearestNeighbor (Matlab 2014b) * 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) * Fix all the 'todo' blocks in the code * Replace handle "0" with bst_get('groot') * At the end of bst_startup in compiled mode, replace loop with waitfor(jFrame) * Error message: Add a link to report directly the bug on the forum * in_bst_results (isFull=1): DataFile should be relative |
* Replace all calls to inpolyhd.m with inpolyhedron.m (10x faster) * Interface scaling: Rewrite class IconLoader to scale only once the icons at startup instead of at each request of an icon (might improve the speed of the rendering of the tree) * Processes with "radio" and "radio_line" options: Replace with "radio_label" and "radio_linelabel" * Interpolations: Use scatteredInterpolant, griddedInterpolant, triangulation.nearestNeighbor (2014b) |
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
- Optimize display: use surface() instead of line() for links? (as in figure_3d/PlotFibers)
- 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 sources:
- Unconstrained to flat: Default PCA for stat and connectivity?
- Process "Scouts time series": Add PCA option (replace isnorm with radio PCA/Norm)
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
- Mixed head models: Bug when displaying interpolated in MRI viewer
- 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
- BEM single sphere: Get implementation from MNE
- Volume grid:
- Optimize: 3D display (better than 9x9 cubes)
- Optimize: vol_dilate (with 26 neighbors)
- Add eyes models to attract eye activity
- Display spectrum scouts (PSD plots when clicking on "Display scouts" on PSD/full cortex)
Anatomy
- MRI segmentation:
Start BrainSuite
Start FreeSurfer
- SimNIBS: Replace HEADRECO with CHARM (headreco will be removed in SimNIBS 4)
FastSurfer: https://deep-mi.org/research/fastsurfer/
- MNI normalization: More options:
- DARTEL / SHOOT
BrainSuite (wait for Anand)
- 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 envelopeSurface>Volume interpolation: Use spm_mesh_to_grid instead of tess_tri_interp
- Atlas switch in 3D MRI figures
- ICBM152 update:
Process with FreeSurfer 7.1 + add FS atlases (Brainnettome, Schaeffer, HCP...)
- Add volume atlases (+ reimport ASEG as volatlas)
Add facemask => Use for defacing with any MNI registration
- Add T2?
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
- Templates for different ages:
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
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
Geodesic distance calculations:
https://www.mathworks.com/matlabcentral/fileexchange/6110-toolbox-fast-marching
ECOG/SEEG
- Contact positions: Import / set / detect
- New option: Align on none|inner|cortex to replace ECOG-mid
- Project contact positions across subjects or templates (Marcel)
- Create clusters from anatomical labels:
- 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
Detection CEEP stim artifacts: Use ImaGIN code ImaGIN_StimDetect
Statistics
- Stat on connectivity?
- Stat on unconstrained sources?
- 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
Input / output
- BIDS import:
- Read real fiducials (OMEGA) / transformation matrices:
- Read associated empty room
- BIDS export:
- Add events tsv, channel tsv, EEG, iEEG
- BIDS-Matlab?
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
Distribution & documentation
- All tutorial datasets in BIDS (including introduction tutorials)
Count GitHub clones in the the download stats
- Deface the MRIs of all the tutorials
- 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
Reproduce tutorials from MNE-Python: https://martinos.org/mne/stable/tutorials.html
Cam-CAN database: https://camcan-archive.mrc-cbu.cam.ac.uk/dataaccess/<<BR>>(download new datasets, including maxfiltered files and manual fiducial placements)
- MEG steady-state / high-gamma visual / frequency tagging
Reproduce results from "Simultaneous human intracerebral stimulation and HD-EEG, ground-truth for source localization methods": https://www.nature.com/articles/s41597-020-0467-x
- Stand-alone ICA tutorial
Current bugs
- Image viewer:
- Difficult to get to 100%
- Buggy on some systems
- 2DLayout:
- (TF) Units are weird with % values
- (TF) Difficult to navigate in frequencies: Scaling+changing frequency resets the scaling
- Progress bar:
- Doesn't close properly on some Linux systems
- Focus requests change workspace when processing constantly (Linux systems)
- MacOS 10.14.5 (Mojave):
- Toggle buttons do not show their status
- Panel Record: Text is too large for text boxes
- 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
Distributed computing
Options from FieldTrip:
Loose collection of computers: https://github.com/fieldtrip/fieldtrip/tree/master/peer
Single multicore machine: https://github.com/fieldtrip/fieldtrip/tree/master/engine
Batch system: https://github.com/fieldtrip/fieldtrip/tree/master/qsub
Documentation: https://www.fieldtriptoolbox.org/faq/what_are_the_different_approaches_i_can_take_for_distributed_computing/
Geeky programming details
- Replace all calls to inpolyhd.m with inpolyhedron.m (10x faster)
Interface scaling: Rewrite class IconLoader to scale only once the icons at startup instead of at each request of an icon (might improve the speed of the rendering of the tree)
- Processes with "radio" and "radio_line" options: Replace with "radio_label" and "radio_linelabel"
- Interpolations: Use scatteredInterpolant, griddedInterpolant, triangulation.nearestNeighbor (2014b)