25772
Comment:
|
20058
|
Deletions are marked like this. | Additions are marked like this. |
Line 7: | Line 7: |
* 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 * Default montages for EEG (sensor selection) |
|
Line 12: | Line 16: |
* RAW file viewer: | * RAW file viewer speed: |
Line 17: | Line 21: |
* Bad trials: When changing the status of bad to good: remove the bad segments as well, otherwise it is not processed by processes like the PSD. * Review clinical recordings: Reduce the dimensionality of the data with a simple inverse problem, similar to what we do for the magnetic extrapolation ("Regional sources" in BESA, cf S Rampp) * MEG/EEG registration: Apply the same transformation to multiple runs * Create heat maps: Maybe with matlab function heatmap? |
|
Line 22: | Line 22: |
* Simulations: https://github.com/lrkrol/SEREEGA == ECOG/SEEG == * Display: * Bad channels: Contacts greyed out instead of ignored (Marcel) * Display time in H:M:S (useful for tutorial Epileptogenicity) * Display curved SEEG electrodes * 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 * Group analysis: extract clusters across subjects, display or average signals (see MIA) * Spike detection: * https://iopscience.iop.org/article/10.1088/1741-2552/ac9259/pdf * Automatic segmentation of CT: * LeGUI: https://github.com/Rolston-Lab/LeGUI/tree/main/LeGUI<<BR>>https://neuroimage.usc.edu/forums/t/automatic-localization-of-seeg-electrodes/36302/7 * GARDEL: http://meg.univ-amu.fr/wiki/GARDEL:presentation * SEEG DEETO Arnulfo 2015: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-015-0511-6 * Used routinely at Niguarda Hospital + other hospitals worldwide, reliable tool. * To be used with SEEG-assistant/3DSlicer: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-017-1545-8 * ECOG Centracchio 2021: https://link.springer.com/content/pdf/10.1007/s11548-021-02325-0.pdf * Classifier on thresholded CT: https://github.com/Jcentracchio/Automated-localization-of-ECoG-electrodes-in-CT-volumes * SEEG Granados 2018 (no code shared): https://link.springer.com/content/pdf/10.1007/s11548-018-1740-8.pdf * ECOG: * Project and display contacts on cortex surface should consider the rigidity of the grids: Contacts cannot rotate, and distance between contacts should remain constant across runs * Method for contacts projection: https://pdfs.semanticscholar.org/f10d/6b899d851f3c4b115404298d7b997cf1d5ab.pdf * ECOG: Brain shift: When creating contact positions on a post-implantation image, the brain shift should be taken into account for creating images of the ECOG contacts on the pre-op brain => iELVis (http://ielvis.pbworks.com/w/page/116347253/FrontPage) <<BR>>Normalization MNI? solutions with FieldTrip? * Display CT images: Better brightness/contrast adjustment: https://neuroimage.usc.edu/forums/t/automatic-localization-of-seeg-electrodes/36302/8 * Detection CEEP stim artifacts: Use ImaGIN code ImaGIN_StimDetect == Pre-processing == * process_detectbad: * Allow on raw files (for bad channels only) * Add detection on derivative of the signal (see EEGLAB) * Document in tutorial Bad channels * PREP pipeline / EEGLAB (Bigdely-Shamlo 2015) * Improve bad channel/trial detection: * ft_artifact_threshold and ft_rejectartifact * MNE-Python * EEGLAB * Integrate with EYE-EEG (Olaf Dimigen) * Reproduce tutorial: https://www.eyetracking-eeg.org/tutorial.html * Create EYE-EEG plugin + processes (Raphael Lambert) * Process: Detect sacades (extended events) + fixations * Improved ICA * Eye-movement related potentials * Add note when rejecting trials: https://neuroimage.usc.edu/forums/t/33686 * ICA: <<BR>> * Automatic classification: ICLabel: https://neuroimage.usc.edu/forums/t/automatic-eeg-ic-ica-classification-for-brainstorm/33785 * Exploration: Add window with spectral decomposition (useful for muscle artifacts) * Export IC time series (and then compute their spectrum): solves the problem above * Import ICA matrices available in EEGLAB .set files * ICA+machine learning: https://www.ncbi.nlm.nih.gov/pubmed/28497769 * Automated artifact rejection: https://arxiv.org/abs/1612.08194 * Use EYE-EEG: EEGLAB toolbox for eye-tracker guided ICA (Olaf Dimigen): http://www2.hu-berlin.de/eyetracking-eeg/ * SSP: * Display warning if changing the ChannelFlag while there is a Projector applied == Reproducibility toolbox == * Generate fully reproducible scripts, including all the interactive/graphical parts * Record all GUI actions as script calls * Import window: Add button to create the corresponding processing pipeline (to generate script or to edit additional options) * Adding the list of plugins to the reports (optionnal or foldable) * Better provenance: History fields, uniform file names... * Improving the pipeline editor to handle loops over data files or subjects |
|
Line 25: | Line 89: |
* Snapshot: Save as image / all figures (similar to Movie/all figure) * Generalize the use of the units (field .DisplayUnits): Rewrite processes to save the units correctly * Colormaps: * Allow brightness/contrast manipulations on the custom colormaps * Global colormap max: Should get the maximum across all the open files * Copy figures to clipboard (with the screencapture function) * Smooth display from figure_image (ERPimage, raster plot...) |
* Colormaps: Global colormap max: Should get the maximum across all the open files * Snapshot: * Save as image / all figures (similar to Movie/all figure) * Copy figures to clipboard (with the screencapture function) |
Line 34: | Line 96: |
* Display CTF coils: Show discs instead of squares * Use boundary() instead of conhull() in all the display functions (ie. 2DDisc) * Progress bar: Add a "Cancel" button * Error message: Add a link to report directly the bug on the forum * Reorganize menus (Dannie's suggestion): {{attachment:dannie_menus.png||width="382",height="237"}} |
== Database == * Save iHeadModel somewhere in the datbase structure * Generalize the use of the units (field .DisplayUnits): Save in source files |
Line 42: | Line 102: |
* Thresholding and stat tests the connectivity matrices * Connectivity on unconstrained sources: "Default signal extraction for volume grids should be the time series of the first principal component of the triplet signals after each has been zero-meaned" (SB) * Display of connectivity graphs: * Display as straight lines * Recode 2D graphs * 3D display with anatomical constrains * Display using real position of EEG electrodes * Use new band-pass filters in bst_connectivity ('bst-hfilter' instead of 'bst-fft-fir') * Matrix view of NxN graphs: Add legend of the elements along X and Y axis * Weighted Phase Lag Index (WPLI) * Graph view: * Does not display negative values correctly (correlation or difference of coherence) * Re-write using pure Matlab code and smoothed graphics * Fixed scales for intensity sliders * Text bigger * Too much data in appdata * Fixed scales for intensity sliders * Add "=" shortcut for having graphs with similar configurations * Disable zoom in one region (serious bugs) * NxN on sensors: does not place the sensors correctly in space * Coherence: * Average cross-spectra instead of concatenating epochs (to avoid discontinuities)<<BR>>Explore inter-trial approaches (Esther refers to chronux toolbox) * Granger: Check for minimum time window (Esther: min around 500-1000 data points) * PLV: * Add p-values * Remove evoked * Optimize code * Add time integration * Unconstrained sources * Add warning when running of short windows (because of filters) |
* Thresholding and stat tests for connectivity matrices: * Panel Display: Show only the top N% measures * Misic: https://www.nature.com/articles/s41583-022-00601-9 * {{attachment:connect_toolboxes.jpg}} * Connect NxN display: * Graph on sensors: does not place the sensors correctly in space * Display as image: Add legend of the elements along X and Y axis * Display as time series: Display warning before trying to open too many signals * Optimize display: use surface() instead of line() for links? (as in figure_3d/PlotFibers) |
Line 73: | Line 112: |
* Tutorial coherence [1xN] : Reproduce FieldTrip results? * Connect NxN: Display as time series > Display warning before trying to open too many signals |
|
Line 77: | Line 114: |
* Decoding/Classifiers: Implement Dimitrios and scikit-learn algorithms * Allow processes in Python and Java |
|
Line 81: | Line 116: |
* BEM single layer (John wants to test it) * ICA: https://neuroimage.usc.edu/forums/t/ica-on-very-long-eeg/23556/4 |
|
Line 86: | Line 123: |
* Chronux toolbox : http://chronux.org/ | |
Line 96: | Line 134: |
* ft_prepare_sourcemodel: Compute MNI transformation (linear and non-linear) => Peter | |
Line 99: | Line 136: |
* ft_read_atlas('TTatlas+tlrc.BRICK'); | |
Line 104: | Line 140: |
* Test speed for writing files: <<BR>>https://undocumentedmatlab.com/articles/improving-fwrite-performance | |
Line 110: | Line 147: |
* When computing sources from the pipeline editor: doesn't reselect the options if you click twice on "edit" (works for minnorm, but not for lcmv) | |
Line 112: | Line 148: |
* ICA: * 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 * Use faster methods (MNE-Python?) * Dimension reduction with PCA adds artifacts: Not done by default in EEGLAB<<BR>>Contact: Stephen Shall Jones ( shall-jones@infoscience.otago.ac.nz )<<BR>>Student Carl Leichter detailed this in his thesis * S Makeig: Use ICA to select the IC of interest instead of only removing artifacts * Display of spectrum for components (PSD/FFT) * Import ICA matrices available in EEGLAB .set files * EEGLAB recommends ICA + trial rejection + ICA again: Impossible right now with Brainstorm<<BR>>(http://sccn.ucsd.edu/wiki/Chapter_09:_Decomposing_Data_Using_ICA) * ICA+machine learning: https://www.ncbi.nlm.nih.gov/pubmed/28497769 * Automated artifact rejection: https://arxiv.org/abs/1612.08194 * Use EYE-EEG: EEGLAB toolbox for eye-tracker guided ICA (Olaf Dimigen): http://www2.hu-berlin.de/eyetracking-eeg/ * Other EEGLAB functions: * Step function detection: https://github.com/lucklab/erplab/wiki/Artifact-Detection:-Tutorial * SSP: * Display warning if changing the ChannelFlag while there is a Projector applied * Spectral flattening (John): * ARIMA(5,0,1): Apply on the signal before any frequency/connectivity/PAC analysis * PSD: * Rewrite to have the same input as coherence (frequency resolution instead of window length) * Allow display of Avg+StdErr |
|
Line 144: | Line 152: |
* Matching pursuit: http://m.jneurosci.org/content/36/12/3399.abstract?etoc * Bug: Display logs as negative * Bug: 3D figures: Colormaps with "log" option doesn't work * Bug: Difference of power displayed in log: problems (Soheila) * 2D Layout in spectrum * Make much faster and more memory efficient (C functions coded by Matti ?) * TF scouts: should display average of TF maps * Impossible to keep complex values for unconstrained sources * Pad short epochs with zero values for getting lower frequencies |
|
Line 154: | Line 153: |
* Extend clusters tab to display of TF to overlay TF signals (Svet) | |
Line 156: | Line 154: |
* Allow baseline normalization of files computed with time bands | |
Line 160: | Line 157: |
* Artifact detection: * Artifact rejection like SPM: if bad in 20%, bad everywhere * Test difference between adjacent samples * Events detection: Add option "std" vs "amplitude" * Simulation: * EEGSourceSim: https://www.sciencedirect.com/science/article/pii/S0165027019302341 * Use field process field "Group" to separate Input/Processing/Output options * Use new Matlab functions: movmean, movsum, movmedian, movmax, movmin, movvar, movstd == Database == * MEG protocols: More flexible organization of the database; sub-conditions to allow different runs X different conditions. * Matrix files: Allow to be dependent from other files * Rename multiple files * Default headmodel lost when reloaded: Keep selection on the hard drive (in brainstormstudy.mat) * Auto-save: * protocol.mat can be too big: do not store the results links in it (and recreate when loading)- http://neuroimage.usc.edu/forums/t/abnormally-slow-behavior/2065/10 * Improve auto-save: add tracking file next to protocol.mat, do not save all the time, only when closing app, and reload protocol at stratup if tracking file is still there == Distributed computing == * Options from FieldTrip: * Loose collection of computers: https://github.com/fieldtrip/fieldtrip/tree/master/peer * Alternative, with less limitations: http://research.cs.wisc.edu/htcondor/ * Single multicore machine: https://github.com/fieldtrip/fieldtrip/tree/master/engine * Batch system: https://github.com/fieldtrip/fieldtrip/tree/master/qsub * Documentation: http://fieldtrip.fcdonders.nl/faq#distributed_computing_with_fieldtrip_and_matlab * PSOM: http://psom.simexp-lab.org/ * Various initiatives: http://samirdas.github.io/Data_sharing.html#/ == Source modeling == * Unconstrained to flat: Default PCA for stat and connectivity? * Sensitivity maps: https://mne.tools/stable/auto_examples/forward/plot_forward_sensitivity_maps.html * 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 * Use eLORETA instead of sLORETA? <<BR>>https://neuroimage.usc.edu/forums/t/compute-eeg-sources-with-sloreta/13425/6 * "eLORETA algorithm is available in the MEG/EEG Toolbox of Hamburg (METH)": https://www.biorxiv.org/content/biorxiv/early/2019/10/17/809285.full.pdf * Point-spread and cross-talk functions (code in MNE-Python): * https://www.biorxiv.org/content/biorxiv/early/2019/06/18/672956.full.pdf * https://github.com/olafhauk/EEGMEGResolutionAtlas * Dipoles: * Project individual dipoles files on a template * panel_dipoles: Doesn't work with multiple figures * Project sources: Very poor algorithm to project sub-cortical regions and cerebellum (algorithm to fit surfaces should be imrpoved) * Menu head model > Copy to other conditions/subjects (check if applicable first) * Menu Sources > Maximum value: Doesn't work with volume or mixed head models * Mixed head models: * Set loose parameter from the interface * Bug when displaying interpolated in MRI viewer * Volume grid: * Optimize: 3D display (better than 9x9 cubes) * Optimize: vol_dilate (with 26 neighbors) * Menu Sources > Simulate recordings: * Do not close the 3D figures after generating a new file * Add a process equivalent to this menu * Panel Get coordinates: Add button "find maximum" * BEM single sphere: Get implementation from MNE * Unconstrained sources: * Stat and connectivity: what to do? (re-send email John+Sylvain) * Sources on surface: Display peak regions over time (time = color) => A.Gramfort * Process "Extract scouts time series": Add PCA option (replace isnorm with choice PCA/Norm) * Add eyes models to attract eye activity |
|
Line 225: | Line 159: |
* Keep ASEG volume + display region name in MRI viewer * '''CAT12''': Optimize interpolation of atlases (import is super slow...) * '''SimNIBS''': Replace HEADRECO with CHARM (headreco will be removed in SimNIBS 4) * Infant templates: Add electrodes positions (at least 10-10) * Multi-Scale Brain Parcellator (Lausanne2008): * [[https://github.com/sebastientourbier/multiscalebrainparcellatorhttps://hub.docker.com/r/sebastientourbier/multiscalebrainparcellator|https://github.com/sebastientourbier/multiscalebrainparcellator]] * [[https://github.com/sebastientourbier/multiscalebrainparcellatorhttps://hub.docker.com/r/sebastientourbier/multiscalebrainparcellator|https://hub.docker.com/r/sebastientourbier/multiscalebrainparcellator]] * https://multiscalebrainparcellator.readthedocs.io/en/latest/ * MNI transformation: Use SPM non-linear MNI transformation y_... * Registration: * Getting electrode positions from 3D scanners: https://sccn.ucsd.edu/wiki/Get_chanlocs * GARDEL: http://meg.univ-amu.fr/wiki/GARDEL:presentation * Use the same registration for multiple recording sessions that have already re-registered previously (eg. with MaxFilter) * When linking multiple EEG recordings including 3D positions, do the registration only once and copy it to all the runs * Compute non-linear MNI registration instead of linear * Select and remove bad digitized head points before automatic coregistration * Load the MNE -transf.fif: http://neuroimage.usc.edu/forums/showthread.php?2830 |
* BEM surfaces: Deform fieldtrip BEM surfaces from ICBM152 to subject space with MNI coordinates? * 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) |
Line 249: | Line 173: |
* Edit fiducials: Replace 6 text boxes with 1 for easy copy-paste (see fiducials.m) * Optimize computation interpolation MRI-surface (tess_tri_interp) => spm_mesh_to_grid |
* Surface>Volume interpolation: Use '''spm_mesh_to_grid''' instead of tess_tri_interp * Defacing: * https://afni.nimh.nih.gov/pub/dist/doc/htmldoc/tutorials/refacer/refacer_run.html * Removing MNI face mask using MNI coordinates * Atlas switch in 3D MRI figures * Bug import anatomy: Requested nVert > high-resolution cortex surface: Creates an empty cortex_0V |
Line 252: | Line 180: |
* Add new labels to all BrainSuite anatomy templates | |
Line 255: | Line 182: |
* FEM templates for different ages: | * 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 |
Line 261: | Line 192: |
* Neurodev database: https://jerlab.sc.edu/projects/neurodevelopmental-mri-database/ * https://openneuro.org/datasets/ds000256/versions/00002 * https://osf.io/axz5r/ |
|
Line 264: | Line 198: |
* Display scouts in a tree: hemisphere, region, subregion * Sort scouts by region in process options * Downsample to atlas: allow on timefreq/connect files * Project from one hemisphere to the other using registered spheres/squares (http://neuroimage.usc.edu/forums/t/how-to-create-mirror-roi-in-the-other-hemisphere/5910/8) |
|
Line 269: | Line 199: |
* Major bug when importing surfaces for an MRI that was re-oriented manually * Surface>Volume interpolation: Use spm_mesh_to_grid * Bug: Hide scouts in the preview of the grid for volume head models |
|
Line 273: | Line 200: |
== ECOG/SEEG == * Electrodes models: Import / export * Contact positions: Import / set / detect * New option: Align on none|inner|cortex to replace ECOG-mid * Add history: Save modifications and transformations applied to the channel files (Marcel) * Project contact positions across subjects or templates (Marcel) * Add menu to import implantation channel file in imported recordings * SEEG/ECOG: Identify contacts in resected areas / identify ROIs for each contact * SEEG/ECOG: Identify contacts in a give 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 * Arnulfo: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-015-0511-6 * MAP07 / SPM: https://www.epi.ch/_files/Artikel_Epileptologie/Huppertz_2_13.pdf * ECOG: * Project and display contacts on cortex surface should consider the rigidity of the grids: Contacts cannot rotate, and distance between contacts should remain constant across runs * Method for contacts projection: https://pdfs.semanticscholar.org/f10d/6b899d851f3c4b115404298d7b997cf1d5ab.pdf * ECOG: Brain shift: When creating contact positions on a post-implantation image, the brain shift should be taken into account for creating images of the ECOG contacts on the pre-op brain => iELVis (http://ielvis.pbworks.com/w/page/116347253/FrontPage) * Display: * Bad channels: Contacts greyed out instead of ignored (Marcel) * Display time in H:M:S * Display curved SEEG electrodes * Export list of contacts with a probability of anatomical regions from various atlases: https://neuroimage.usc.edu/forums/t/seeg-contacts-anatomical-location/14756 * Detection CEEP stim artifacts: Use ImaGIN code ImaGIN_StimDetect |
* 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) * OpenMEEG: Detect bad results + exclude from leadfield * BEM single sphere: Get implementation from MNE * Add eyes models to attract eye activity == Source modeling == * Reproduce results in "Simultaneous human intracerebral stimulation and HD-EEG, ground-truth for source localization methods": https://www.nature.com/articles/s41597-020-0467-x * eLORETA instead of sLORETA? * https://neuroimage.usc.edu/forums/t/compute-eeg-sources-with-sloreta/13425/6 * https://neuroimage.usc.edu/forums/t/loreta-and-source-localization/30525 * "eLORETA algorithm is available in the MEG/EEG Toolbox of Hamburg (METH)": https://www.biorxiv.org/content/biorxiv/early/2019/10/17/809285.full.pdf * https://github.com/brainstorm-tools/brainstorm3/issues/114 * Point-spread and cross-talk functions (code in MNE-Python): * https://www.biorxiv.org/content/biorxiv/early/2019/06/18/672956.full.pdf * https://github.com/olafhauk/EEGMEGResolutionAtlas * Dipoles: * Display dipoles in MRI viewer * panel_dipoles: Doesn't work with multiple figures * Project sources: Very poor algorithm to project sub-cortical regions and cerebellum * Maximum: * Menu Sources > Maximum value: Doesn't work with volume or mixed head models * Panel Get coordinates: Add button "find maximum" * Sources on surface: Display peak regions over time (time = color) => A.Gramfort * Volume grid: * Optimize: 3D display (better than 9x9 cubes) * Optimize: vol_dilate (with 26 neighbors) |
Line 299: | Line 236: |
* 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 |
|
Line 300: | Line 240: |
* Which functions to use? * Write panel similar to Process1 and Process2 to allow the |
* Write panel similar to Process1 and Process2 |
Line 304: | Line 243: |
* Quality control before statistics, on condition averages across subjects:<<BR>>mean(baseline)/std(baseline): shows bad subject quickly. * Use SurfStat: Impements interesting things, like an analytical cluster-based p-value correction (Random-field theory which is used in SPM) - Peter * Export to R or SPSS for advanced stat |
* Multivariate stim-response analysis: https://github.com/mickcrosse/mTRF-Toolbox |
Line 309: | Line 246: |
* Bug import multiple files: use same "time" for all files | |
Line 311: | Line 247: |
* Read real fiducials (OMEGA) * Read associated empty room * Test all the BIDS examples * BIDS Export: |
* 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 * BIDS export: |
Line 316: | Line 254: |
* '''XDF import''': Use FieldTRip or the EEGLAB plugin, contact Martin Bleichner (Oldenburg)<<BR>>https://github.com/sccn/xdf/blob/master/xdf_sample.xdf |
* BIDS-Matlab? * Support for OpenJData / JNIfTI: https://github.com/brainstorm-tools/brainstorm3/issues/284 |
Line 321: | Line 259: |
* FieldTrip: Import/Export time-frequency: * Export: http://neuroimage.usc.edu/forums/t/export-time-frequency-to-fieldtrip/1968 * Import: http://neuroimage.usc.edu/forums/t/import-time-frequency-data-from-fieldtrip/2644 |
* 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) |
Line 325: | Line 267: |
* Use reader from MNE-Python: mne.io.read_raw_kit (doesn't require Yokogawa slow library) | * Use reader from MNE-Python: mne.io.read_raw_kit (skip Yokogawa slow library) |
Line 331: | Line 273: |
* EEG File formats: * EEG CeeGraph * EGI: Finish support for epoched files (formats 3,5,7) * XLTEK: https://github.com/danielmhanover/OpenXLT * Persyst .lay: https://github.com/ieeg-portal/Persyst-Reader * Nervus .eeg: https://github.com/ieeg-portal/Nervus-Reader * Biopac .acq: https://github.com/ieeg-portal/Biopac-Reader * gTec EEG recordings: Read directly from the HDF5 files instead of the Matlab exports. * BCI2000 Input (via EEGLAB plugin) |
|
Line 341: | Line 274: |
* Review raw on all the file formats (ASCII EEG and Cartool missing) * SPM .mat/.dat: Fix the import of the EEG/SEEG coordinates * Get acquisition date from files: Missing for 4D * Support for OpenJData / JNIfTI: https://github.com/brainstorm-tools/brainstorm3/issues/284 == Distribution & documentation == |
* MINC MRI: Add support for "voxel to world" transformation (vox2ras) similarly to .nii == Distribution == * Java-free Matlab: All references of functions below must be removed * '''JavaFrame''': screencapture.m (used for screen captures of videos) * '''Actxcontrol''': Used for video-EEG * uihtml + JavaScript callbacks? * ActiveX in .NET app? * Pure Java framce + VLC java plugin? * Other video player? * '''Javacomponent''': * mri_editMask * figure_mri * process_bandpass * List .jar files used from Matlab distribution (e.g. dom) => Check all the import calls * Cleanup GitHub repository: * https://github.com/brainstorm-tools/brainstorm3/issues/473 * Remove ICBM152 default anatomy from repo * Move external I/O libraries as plugins: * mne-matlab * CEDS64ML * edfimport * eeprobe * son * ricoh * yokogawa * easyh5 == Documentation == * All tutorial datasets in BIDS (including introduction tutorials) * Deface the MRIs of all the tutorials * Count GitHub clones in the the download stats * MNE-Python 1.0: Test and update install documentation |
Line 348: | Line 308: |
* Update the organization of derivatives folder (same for ECOG tutorial) * Add review of literature for the resting state MEG |
* Update the organization of derivatives folder (full FS folders) |
Line 351: | Line 310: |
* Tutorial iEEG: * Rename _coordsystem/_electrodes => space_other |
|
Line 357: | Line 314: |
* FieldTrip cortico-muscular coherence tutorial: http://www.fieldtriptoolbox.org/tutorial/coherence | |
Line 361: | Line 317: |
* BIDS-EEG example datasets | |
Line 363: | Line 318: |
* Stand-alone ICA tutorial * Move all the files to download to the cloud for faster download everywhere in the world * Provide secure way of sending password over HTTPS for: * Account creation * Forum exchanges * org.brainstorm.dialog.CloneControl * Workflows FieldTrip: http://www.fieldtriptoolbox.org/faq/what_types_of_datasets_and_their_respective_analyses_are_used_on_fieldtrip * Count GitHub clones in the the download stats * Deface the MRIs of all the tutorials * Clean up the wiki: * Remove all the wiki pages that are not used * Check all the links in all the pages * Check that all the TODO blocks have been properly handled * Remove useless images from all tutorials * Update page count on the main tutorials page |
* Stand-alone ICA tutorial |
Line 381: | Line 321: |
* MacOS 10.14.5 (Mojave): * Toggle buttons do not show their status * Panel Record: Text is too large for text boxes |
|
Line 393: | Line 330: |
* MacOS bugs: * Buttons {Yes,No,Cancel} listed backwards * Record tab: Text of epoch number is too big * Colormap menus: Do not work well on compiled MacOSX 10.9.5 and 10.10 * Canolty maps computation: Fix progress bar |
== Distributed computing == * Options from FieldTrip: * Loose collection of computers: https://github.com/fieldtrip/fieldtrip/tree/master/peer * Single multicore machine: https://github.com/fieldtrip/fieldtrip/tree/master/engine * Batch system: https://github.com/fieldtrip/fieldtrip/tree/master/qsub * Documentation: https://www.fieldtriptoolbox.org/faq/what_are_the_different_approaches_i_can_take_for_distributed_computing/ * PSOM: http://psom.simexp-lab.org/ * Google: https://www.youtube.com/watch?v=LLMXV3o2FT0 * https://edu.google.com/why-google/case-studies/unc-chapel-hill-gcp/ |
Line 400: | Line 342: |
* Replace all calls to inpolyhd.m with inpolyhedron.m * bst_bsxfun: After 2016b, we can use directly the scalar operators (./ .* ...) instead of bsxfun. Update bst_bsxfun to skip the use of bsxfun when possible. |
* Replace all calls to inpolyhd.m with inpolyhedron.m (10x faster) |
Line 403: | Line 344: |
* Hide Java panels instead of deleting them | |
Line 406: | Line 346: |
* bst_warp and channel_project: Use tess_parametrize_new instead of tess_parametrize * Shared kernels: "get bad channels" operation in a different way (reading all the files is too slow) * Optimize bst_get: * Now study and subject have necessarily the same folder name * Replace big switch with separate functions * Fix all the 'todo' blocks in the code |
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
- 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
BioSemi: Add menu "Convert naming system" to rename channels into 10-10 (A1=>FPz)
Simulations: https://github.com/lrkrol/SEREEGA
ECOG/SEEG
- Display:
- Bad channels: Contacts greyed out instead of ignored (Marcel)
- Display time in H:M:S (useful for tutorial Epileptogenicity)
- Display curved SEEG electrodes
- 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
- Group analysis: extract clusters across subjects, display or average signals (see MIA)
- Spike detection:
- Automatic segmentation of CT:
SEEG DEETO Arnulfo 2015: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-015-0511-6
- Used routinely at Niguarda Hospital + other hospitals worldwide, reliable tool.
To be used with SEEG-assistant/3DSlicer: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-017-1545-8
ECOG Centracchio 2021: https://link.springer.com/content/pdf/10.1007/s11548-021-02325-0.pdf
Classifier on thresholded CT: https://github.com/Jcentracchio/Automated-localization-of-ECoG-electrodes-in-CT-volumes
SEEG Granados 2018 (no code shared): https://link.springer.com/content/pdf/10.1007/s11548-018-1740-8.pdf
- ECOG:
- Project and display contacts on cortex surface should consider the rigidity of the grids: Contacts cannot rotate, and distance between contacts should remain constant across runs
Method for contacts projection: https://pdfs.semanticscholar.org/f10d/6b899d851f3c4b115404298d7b997cf1d5ab.pdf
ECOG: Brain shift: When creating contact positions on a post-implantation image, the brain shift should be taken into account for creating images of the ECOG contacts on the pre-op brain => iELVis (http://ielvis.pbworks.com/w/page/116347253/FrontPage)
Normalization MNI? solutions with FieldTrip?
Display CT images: Better brightness/contrast adjustment: https://neuroimage.usc.edu/forums/t/automatic-localization-of-seeg-electrodes/36302/8
Detection CEEP stim artifacts: Use ImaGIN code ImaGIN_StimDetect
Pre-processing
- process_detectbad:
- Allow on raw files (for bad channels only)
- Add detection on derivative of the signal (see EEGLAB)
- Document in tutorial Bad channels
- PREP pipeline / EEGLAB (Bigdely-Shamlo 2015)
- Improve bad channel/trial detection:
- ft_artifact_threshold and ft_rejectartifact
- MNE-Python
- EEGLAB
- Integrate with EYE-EEG (Olaf Dimigen)
Reproduce tutorial: https://www.eyetracking-eeg.org/tutorial.html
- Create EYE-EEG plugin + processes (Raphael Lambert)
- Process: Detect sacades (extended events) + fixations
- Improved ICA
- Eye-movement related potentials
Add note when rejecting trials: https://neuroimage.usc.edu/forums/t/33686
ICA:
Automatic classification: ICLabel: https://neuroimage.usc.edu/forums/t/automatic-eeg-ic-ica-classification-for-brainstorm/33785
- Exploration: Add window with spectral decomposition (useful for muscle artifacts)
- Export IC time series (and then compute their spectrum): solves the problem above
- Import ICA matrices available in EEGLAB .set files
ICA+machine learning: https://www.ncbi.nlm.nih.gov/pubmed/28497769
Automated artifact rejection: https://arxiv.org/abs/1612.08194
Use EYE-EEG: EEGLAB toolbox for eye-tracker guided ICA (Olaf Dimigen): http://www2.hu-berlin.de/eyetracking-eeg/
- SSP:
Display warning if changing the ChannelFlag while there is a Projector applied
Reproducibility toolbox
- Generate fully reproducible scripts, including all the interactive/graphical parts
- Record all GUI actions as script calls
- Import window: Add button to create the corresponding processing pipeline (to generate script or to edit additional options)
- Adding the list of plugins to the reports (optionnal or foldable)
- Better provenance: History fields, uniform file names...
- Improving the pipeline editor to handle loops over data files or subjects
Interface
Add a warning when computing a forward model with > 100000 sources (check selection)
- Colormaps: Global colormap max: Should get the maximum across all the open files
- Snapshot:
- Save as image / all figures (similar to Movie/all figure)
- Copy figures to clipboard (with the screencapture function)
Contact sheets & movies: use average of time windows instead of single instants, for each picture.
- Contact sheets: Allow explicit list of times in input (+ display as in MNE-Python with TS)
Database
- Save iHeadModel somewhere in the datbase structure
Generalize the use of the units (field .DisplayUnits): Save in source files
Connectivity
- Thresholding and stat tests for connectivity matrices:
- Panel Display: Show only the top N% measures
- Connect NxN display:
- Graph on sensors: does not place the sensors correctly in space
- Display as image: Add legend of the elements along X and Y axis
- Display as time series: Display warning before trying to open too many signals
- Optimize display: use surface() instead of line() for links? (as in figure_3d/PlotFibers)
- Time-resolved correlation/coherence: Display as time bands
Processes
- Add MNE-Python functions:
- scikit-learn classifiers
- BEM single layer (John wants to test it)
ICA: https://neuroimage.usc.edu/forums/t/ica-on-very-long-eeg/23556/4
https://neuroimage.usc.edu/forums/t/best-way-to-export-to-mne-python/12704/3
- Reproduce other tutorials / examples
Point-spread functions (PSFs) and cross-talk functions: https://mne.tools/stable/auto_examples/inverse/plot_psf_ctf_vertices.html#sphx-glr-auto-examples-inverse-plot-psf-ctf-vertices-py
Spatial resolution metrics in source space:
https://mne.tools/stable/auto_examples/inverse/plot_resolution_metrics.html#sphx-glr-auto-examples-inverse-plot-resolution-metrics-py- Change the graphic renderer from Matlab
Chronux toolbox : http://chronux.org/
Add FieldTrip functions:
- ft_sourceanalysis:
- Check noise covariance
- Check all the options of all the methods
- Single trial reconstructions + noise covariance?
Filters?? http://www.fieldtriptoolbox.org/example/common_filters_in_beamforming
Beamformers: Save ftSource.avg.mom
http://www.fieldtriptoolbox.org/workshop/meg-uk-2015/fieldtrip-beamformer-demohttp://www.fieldtriptoolbox.org/tutorial/beamformingextended
- Baseline? Two inputs?
- ft_prepare_heamodel: Add support from BEM surfaces from the Brainstorm database
- Freqanalysis: ITC
ft_volumereslice: http://www.fieldtriptoolbox.org/faq/how_change_mri_orientation_size_fov
- ft_freqanalysis
- ft_combineplanar
- ft_sourceanalysis:
- Optimization:
Test speed for writing files:
https://undocumentedmatlab.com/articles/improving-fwrite-performance- Use CUDA for speeding up some operations (filtering, wavelets, etc)
- Use Matlab Coder to optimize: Wavelets, bandpass filter, sinusoid removal
- Pipeline editor:
- Bug: After "convert to continuous", the time of the following processes should change
- Add loops over subjects/conditions/trial groups
- Events: Allow selection from a drop-down list (similar to option "channelname" in panel_process_selection)
ITC: Inter-trial coherence (see MNE reports for group tutorial)
http://www.sciencedirect.com/science/article/pii/S1053811916304232Remove line noise: http://www.nitrc.org/projects/cleanline
- Time-frequency:
- Optimization: bst_timefreq (around l.136), remove evoked in source space: Average should be computed in sensor space instead of source space (requested by Dimitrios)
Short-time Fourier transform: http://www.mikexcohen.com/lectures.html
- Hilbert with time bands very slow on very long files (eg. 3600s at 1000Hz) because the time vector is still full (10^7 values): save compressed time vector instead.
- When normalizing with baseline: Propagate with the edge effects marked in TFmask
- Allow running TF on montages
- Review continuous files in time-frequency space (for epilepsy)
- Bug when computing TF on constrained and unconstrained scouts at the same time (in mixed head models for instance): uses only the constrained information and doesn't sum the 3 orientations for the unconstrained regions.
Anatomy
- BEM surfaces: Deform fieldtrip BEM surfaces from ICBM152 to subject space with MNI coordinates?
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:
- Pan in zoomed view (shift + click + move?)
- Zoom in/out with mouse (shift + scroll?)
- Ruler tool to measure distances
- Display scouts as additional volumes
Render surface envelope in the MRI as a thin line instead of the full interpolation matrix
Or use inpolyhedron to get a surface mask and then erode it to get the volume envelopeSurface>Volume interpolation: Use spm_mesh_to_grid instead of tess_tri_interp
- Defacing:
https://afni.nimh.nih.gov/pub/dist/doc/htmldoc/tutorials/refacer/refacer_run.html
- Removing MNI face mask using MNI coordinates
- Atlas switch in 3D MRI figures
Bug import anatomy: Requested nVert > high-resolution cortex surface: Creates an empty cortex_0V
BrainSuite:
- Use same colors for left and right for anatomical atlases
- Use for volume coregistration (rigid / non-rigid)
- USCBrain: Add default electrodes positions
Remove BrainSuite1 when not needed anymore
- Brain2mesh: Add import of 10-10 positions
- Templates for different ages:
MNI: https://www.bic.mni.mcgill.ca/ServicesAtlases/NIHPD-obj1
Pediatric head atlases: https://www.pedeheadmod.net/pediatric-head-atlases-v1-2/
https://www.biorxiv.org/content/biorxiv/early/2020/02/09/2020.02.07.939447.full.pdf
John Richards: https://www.nitrc.org/frs/?group_id=1361
Neurodev database: https://jerlab.sc.edu/projects/neurodevelopmental-mri-database/
- Scouts:
- Display edges in the middle of the faces instead of the vertices
- Parcellating volume grids: scikit-learn.cluster.Ward
Geodesic distance calculations:
https://www.mathworks.com/matlabcentral/fileexchange/6110-toolbox-fast-marching- Improving the registration between EEG and anatomy templates:
- Warping: Improve the basic alignment of the digitized electrodes on the templat, possibly with Cz and other anatomical landmarks
- EEG template positions: rework using a standardized Cz position (+ other landmarks)
Forward modeling
- DUNEuro/FEM:
Add lesion mask to SimNIBS: https://simnibs.github.io/simnibs/build/html/documentation/command_line/add_tissues_to_upsampled.html#add-tissues-to-upsampled-doc
GeomtryAdapted: Buggy?
Display differences between leadfields: amplitude of difference (right-click > Compare)
- OpenMEEG: Detect bad results + exclude from leadfield
- BEM single sphere: Get implementation from MNE
- Add eyes models to attract eye activity
Source modeling
Reproduce results in "Simultaneous human intracerebral stimulation and HD-EEG, ground-truth for source localization methods": https://www.nature.com/articles/s41597-020-0467-x
- eLORETA instead of sLORETA?
https://neuroimage.usc.edu/forums/t/compute-eeg-sources-with-sloreta/13425/6
https://neuroimage.usc.edu/forums/t/loreta-and-source-localization/30525
"eLORETA algorithm is available in the MEG/EEG Toolbox of Hamburg (METH)": https://www.biorxiv.org/content/biorxiv/early/2019/10/17/809285.full.pdf
- Point-spread and cross-talk functions (code in MNE-Python):
- Dipoles:
- Display dipoles in MRI viewer
- panel_dipoles: Doesn't work with multiple figures
- Project sources: Very poor algorithm to project sub-cortical regions and cerebellum
- Maximum:
Menu Sources > Maximum value: Doesn't work with volume or mixed head models
- Panel Get coordinates: Add button "find maximum"
Sources on surface: Display peak regions over time (time = color) => A.Gramfort
- Volume grid:
- Optimize: 3D display (better than 9x9 cubes)
- Optimize: vol_dilate (with 26 neighbors)
Statistics
- Stat on unconstrained sources?
Stat/time series: Hide lines going down to zero (Dimitrios: https://neuroimage.usc.edu/forums/t/common-source-activation-across-subjects-and-conditions/1152/21)
- Cluster stat: Add frequency selection option
- ANOVA:
- Write panel similar to Process1 and Process2
- Output = 1 file per effect, all grouped in a node "ANOVA"
- Display several ANOVA maps (from several files) on one single figure, using a "graphic accumulator", towards which one can send any type of graphic object
Multivariate stim-response analysis: https://github.com/mickcrosse/mTRF-Toolbox
Input / output
- BIDS import:
- Full support for iEEG and EEG
- Read real fiducials (OMEGA) / transformation matrices:
- 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
- MINC MRI: Add support for "voxel to world" transformation (vox2ras) similarly to .nii
Distribution
- Java-free Matlab: All references of functions below must be removed
JavaFrame: screencapture.m (used for screen captures of videos)
Actxcontrol: Used for video-EEG
uihtml + JavaScript callbacks?
- ActiveX in .NET app?
- Pure Java framce + VLC java plugin?
- Other video player?
Javacomponent:
- mri_editMask
- figure_mri
- process_bandpass
List .jar files used from Matlab distribution (e.g. dom) => Check all the import calls
Cleanup GitHub repository:
- Remove ICBM152 default anatomy from repo
- Move external I/O libraries as plugins:
- mne-matlab
- CEDS64ML
- edfimport
- eeprobe
- son
- ricoh
- yokogawa
- easyh5
Documentation
- All tutorial datasets in BIDS (including introduction tutorials)
- Deface the MRIs of all the tutorials
Count GitHub clones in the the download stats
- MNE-Python 1.0: Test and update install documentation
- Tutorial OMEGA/BIDS:
- Update the organization of derivatives folder (full FS folders)
- Download example datasets directly from the OMEGA repository
New tutorials:
Other public datasets: https://github.com/INCF/BIDS-examples/tree/bep008_meg/
- EEG/research
FieldTrip ECOG tutorial: http://www.fieldtriptoolbox.org/tutorial/human_ecog
Reproduce tutorials from MNE-Python: https://martinos.org/mne/stable/tutorials.html
Cam-CAN database: https://camcan-archive.mrc-cbu.cam.ac.uk/dataaccess/<<BR>>(download new datasets, including maxfiltered files and manual fiducial placements)
- MEG steady-state / high-gamma visual / frequency tagging
Reproduce results from "Simultaneous human intracerebral stimulation and HD-EEG, ground-truth for source localization methods": https://www.nature.com/articles/s41597-020-0467-x
- Stand-alone ICA tutorial
Current bugs
- Image viewer:
- Difficult to get to 100%
- Buggy on some systems
- 2DLayout:
- (TF) Units are weird with % values
- (TF) Difficult to navigate in frequencies: Scaling+changing frequency resets the scaling
- Progress bar:
- Doesn't close properly on some Linux systems
- Focus requests change workspace when processing constantly (Linux systems)
Distributed computing
Options from FieldTrip:
Loose collection of computers: https://github.com/fieldtrip/fieldtrip/tree/master/peer
Single multicore machine: https://github.com/fieldtrip/fieldtrip/tree/master/engine
Batch system: https://github.com/fieldtrip/fieldtrip/tree/master/qsub
Documentation: https://www.fieldtriptoolbox.org/faq/what_are_the_different_approaches_i_can_take_for_distributed_computing/
Geeky programming details
- Replace all calls to inpolyhd.m with inpolyhedron.m (10x faster)
Interface scaling: Rewrite class IconLoader to scale only once the icons at startup instead of at each request of an icon (might improve the speed of the rendering of the tree)
- Processes with "radio" and "radio_line" options: Replace with "radio_label" and "radio_linelabel"
- Interpolations: Use scatteredInterpolant, griddedInterpolant, triangulation.nearestNeighbor (2014b)