What's next

A roadmap to the future developments of Brainstorm.

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)

• Simulations: https://github.com/lrkrol/SEREEGA

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-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)
  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.0030135

  • Dimension reduction with PCA adds artifacts: Not done by default in EEGLAB
    Contact: Stephen Shall Jones ( shall-jones@infoscience.otago.ac.nz )
    Student Carl Leichter detailed this in his thesis

  • 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

  • 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

• Simple-brain-plot: https://github.com/dutchconnectomelab/Simple-Brain-Plot

• 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 envelope

  • Surface>Volume interpolation: Use spm_mesh_to_grid instead of tess_tri_interp

• Defacing:

  • https://afni.nimh.nih.gov/pub/dist/doc/htmldoc/tutorials/refacer/refacer_run.html

  • Removing MNI face mask using MNI coordinates
• 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:
  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

• Multivariate stim-response analysis: https://github.com/mickcrosse/mTRF-Toolbox

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:
  

  • 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/

• PSOM: http://psom.simexp-lab.org/

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)