What's next

A roadmap to the future developments of Brainstorm.

Recordings

• Review signals in time-frequency space
• Events processes: Select events names from a list instead of having to type them
• Display CTF coils: Show discs instead of squares
• Sleep scoring wish list (Emily C):
  • Configurable horizontal lines (for helping detecting visually some thresholds)
  • Mouse ruler: Measure amplitude by dragging the mouse.
  • Automatic spindle detector

  • https://neuroimage.usc.edu/forums/t/page-overlap-while-reviewing-raw-file-a-way-to-set-to-0/11229/13

• RAW file viewer speed (Low priority) :
  

  • Consider to change to a format that is faster to read
  • Add parameter to make the visual downsampling more or less aggressive

  • Keep the filter specifications in memory instead of recomputing for every page
    (Nice to have)

• BioSemi: Add menu "Convert naming system" to rename channels into 10-10 (A1=>FPz)

• Simulations: https://github.com/lrkrol/SEREEGA(Low priority)

ECOG/SEEG

• https://www.sciencedirect.com/science/article/pii/S1053811922005559

• Display (high-priority)(Part SEEG grant):
  • Group display: Overlay multiple channel files in the same figure, coloring contacts by subject/ROI/Cluster/Electrode name

    • https://neuroimage.usc.edu/forums/t/37617

    • iEEG tab must be read-only when multiple files (hide configuration controls)

  • Bad channels: Contacts greyed out instead of ignored (Marcel H, Germany)
    (To diff between band and not-recorded) > Rendering of SEEG electrodes: Full surface modelling with surface mesh (see Lead-DBS models + code that generates them?)

  • Display time in H:M:S instead of S > If there is t0 in H:M:S instead of S > As an option in Display configuration button>x-axis

  • view_leadfield_sensitivity: Add closing surfaces at cortex limits
  • Create clusters from anatomical labels (Anne So) :

  • Identify contacts in a given anatomical region (volume scout, surface mesh, or label in a volume atlas) / allow extracting the signals from all the contacts in an ROI> As a process to select recordings, then Scouts from Volumen Atlas, Create cluster in channel file, then Extract time series.

  • Group analysis: extract clusters across subjects, display or average signals (see MIA) (Anne So)
• Spike detection (Need to check for current toolboxes from scratch)(contact Nicolas R)(Mosher J)(iEEG BIDS):

  • https://iopscience.iop.org/article/10.1088/1741-2552/ac9259/pdf

• Automatic segmentation of CT:

  • LeGUI: https://github.com/Rolston-Lab/LeGUI/tree/main/LeGUI<<BR>>https://neuroimage.usc.edu/forums/t/automatic-localization-of-seeg-electrodes/36302/7

  • GARDEL: http://meg.univ-amu.fr/wiki/GARDEL:presentation

  • Discussed with Samuel and Christian (ins-amu.fr)

  • SEEG DEETO Arnulfo 2015: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-015-0511-6

    • Used routinely at Niguarda Hospital + other hospitals worldwide, reliable tool.

    • To be used with SEEG-assistant/3DSlicer: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-017-1545-8

  • ECOG Centracchio 2021: https://link.springer.com/content/pdf/10.1007/s11548-021-02325-0.pdf

    • Classifier on thresholded CT: https://github.com/Jcentracchio/Automated-localization-of-ECoG-electrodes-in-CT-volumes

  • SEEG Granados 2018 (no code shared): https://link.springer.com/content/pdf/10.1007/s11548-018-1740-8.pdf

• ECOG:
  • Project and display contacts on cortex surface should consider the rigidity of the grids: Contacts cannot rotate, and distance between contacts should remain constant across runs

  • Method for contacts projection: https://pdfs.semanticscholar.org/f10d/6b899d851f3c4b115404298d7b997cf1d5ab.pdf

  • ECOG: Brain shift: When creating contact positions on a post-implantation image, the brain shift should be taken into account for creating images of the ECOG contacts on the pre-op brain => iELVis (http://ielvis.pbworks.com/w/page/116347253/FrontPage)
    Normalization MNI? solutions with FieldTrip?

• Display CT images: Better brightness/contrast adjustment: https://neuroimage.usc.edu/forums/t/automatic-localization-of-seeg-electrodes/36302/8 Range of values is way diff than ones from MRI. Current color maps are not suitable for CT, need to be improved.Together with processing of CT to get electrode positions.

• Detection CCEP stim artifacts: Use ImaGIN code ImaGIN_StimDetect https://f-tract.eu/software/imagin/

• Add support for modeling non-uniform spaced sEEG electrodes (https://neuroimage.usc.edu/forums/t/feature-request-support-seeg-electrodes-with-non-uniform-spacing/39647/6)

• VTA and Efields: fast field :https://doi.org/10.1016/j.neuroimage.2020.117330

Pre-processing

• process_detectbad:
  • Allow on raw files (for bad channels only)
  • Add detection on derivative of the signal (see EEGLAB)
  • Document in tutorial Bad channels
  • PREP pipeline / EEGLAB (Bigdely-Shamlo 2015)
• Improve bad channel/trial detection:
  • ft_artifact_threshold and ft_rejectartifact
  • MNE-Python
  • EEGLAB
• Integrate with EYE-EEG (Olaf Dimigen)

  • Reproduce tutorial: https://www.eyetracking-eeg.org/tutorial.html

  • Create EYE-EEG plugin + processes (Raphael Lambert)
  • Process: Detect sacades (extended events) + fixations
  • Improved ICA
  • Eye-movement related potentials

  • Use it to guide ICA: http://www2.hu-berlin.de/eyetracking-eeg/

• ICA:
  

  • Automatic classification: ICLabel: https://neuroimage.usc.edu/forums/t/automatic-eeg-ic-ica-classification-for-brainstorm/33785

  • Exploration: Add window with spectral decomposition (useful for muscle artifacts)
  • Export IC time series (and then compute their spectrum): solves the problem above
  • Import ICA matrices available in EEGLAB .set files

  • ICA+machine learning: https://www.ncbi.nlm.nih.gov/pubmed/28497769

  • Automated artifact rejection: https://arxiv.org/abs/1612.08194

  • Spectral representation of ICs
• SSP:

  • Display warning if changing the ChannelFlag while there is a Projector applied

• File format:
  • Add support to read GDF file format

https://github.com/donnchadh/biosig/blob/master/biosig/t200_FileAccess/sload.m

Reproducibility toolbox

• Generate fully reproducible scripts, including all the interactive/graphical parts
• Record all GUI actions as script calls
• Import window: Add button to create the corresponding processing pipeline (to generate script or to edit additional options).
• Adding the list of plugins to the reports
• Better provenance: History fields, uniform file names...

Interface

• Add a warning when computing a forward model with > 100000 sources (check selection)

• Colormaps: Global colormap max: Should get the maximum across all the open files
• Snapshot:
  • Save as image / all figures (similar to Movie/all figure)

• Contact sheets & movies: use average of time windows instead of single instants, for each picture.

• Contact sheets: Allow explicit list of times in input (+ display as in MNE-Python with TS)

Database

• Save iHeadModel somewhere in the datbase structure

• Generalize the use of the units (field .DisplayUnits): Save in source files

Connectivity

• Define names and unit labels for each connectivity metric

• Null models: (Bratislav M) https://www.nature.com/articles/s41583-022-00601-9

  • 

• Connect NxN display:
  • Graph on sensors: Place M/EEG sensors by location, not by channel order
  • Display as image: Add legend of the elements along X and Y axis
  • Display as time series: Display warning before trying to open too many signals
  • Optimize display: use surface() instead of line() for links? (as in figure_3d/PlotFibers)
• Time-resolved correlation/coherence: Display as time bands (as done in wavelet, to have same time axis as data)

Processes

• Add MNE-Python functions:
  • scikit-learn classifiers
  • BEM single layer (John wants to test it)

  • https://neuroimage.usc.edu/forums/t/best-way-to-export-to-mne-python/12704/3

  • Reproduce tutorials / examples from FieldTrip and MNE-Python:

    • FieldTrip ECOG tutorial: http://www.fieldtriptoolbox.org/tutorial/human_ecog

    • Reproduce tutorials from MNE-Python: https://martinos.org/mne/stable/tutorials.html

  • Spatial resolution metrics in source space:
    https://mne.tools/stable/auto_examples/inverse/plot_resolution_metrics.html#sphx-glr-auto-examples-inverse-plot-resolution-metrics-py

  • Change the graphic renderer from Matlab

• Chronux toolbox : http://chronux.org/

• Add FieldTrip functions:

  • ft_sourceanalysis:
    • Check noise covariance
    • Check all the options of all the methods
    • Single trial reconstructions + noise covariance?

    • Filters?? http://www.fieldtriptoolbox.org/example/common_filters_in_beamforming

    • Beamformers: Save ftSource.avg.mom
      http://www.fieldtriptoolbox.org/workshop/meg-uk-2015/fieldtrip-beamformer-demo

    • http://www.natmeg.se/ft_beamformer/beamformer.html

    • http://www.fieldtriptoolbox.org/tutorial/beamformingextended

    • Baseline? Two inputs?
  • ft_prepare_heamodel: Add support from BEM surfaces from the Brainstorm database

  • ft_volumereslice: http://www.fieldtriptoolbox.org/faq/how_change_mri_orientation_size_fov

  • ft_freqanalysis
  • ft_combineplanar
• Optimization:
  • Use CUDA for speeding up some operations (filtering, wavelets, etc)
  • Use Matlab Coder to optimize: Wavelets, bandpass filter, sinusoid removal
• Pipeline editor:
  • Bug: After "convert to continuous", the time of the following processes should change
  • Add loops over subjects/conditions/trial groups
  • Events: Allow selection from a drop-down list (similar to option "channelname" in panel_process_selection)

• ITC: Inter-trial coherence (see MNE reports for group tutorial)
  http://www.sciencedirect.com/science/article/pii/S1053811916304232

• 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
  • Bug when computing TF on constrained and unconstrained scouts at the same time (in mixed head models for instance): uses only the constrained information and doesn't sum the 3 orientations for the unconstrained regions.
  • requested feature from the forum:

• * https://neuroimage.usc.edu/forums/t/event-export-and-process-find-maximum-value-amplitude/41911/2

• * https://neuroimage.usc.edu/forums/t/custom-process-that-involves-merging-of-channels/40638

• * https://neuroimage.usc.edu/forums/t/swloreta-for-source-localization/41882/4

Anatomy

• Display parcellation values (matrices) in 3D and 2D.

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

  • Scouts

• Import SimNIBS4: Use final_tissues_LUT.txt instead of fixed list of tissues: https://neuroimage.usc.edu/forums/t/removing-a-lesioned-area/38414/20

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

• MNI normalization: More options:
  • DARTEL / SHOOT

  • BrainSuite (wait for Anand)

  • Import from SimNIBS (Conform2MNI_nonl.nii.gz, MNI2Conform_nonl.nii.gz)
• MRI Viewer:

  • Adjust CT contrast better: https://neuroimage.usc.edu/forums/t/automatic-localization-of-seeg-electrodes/36302/10

  • Pan in zoomed view (shift + click + move?)
  • Zoom in/out with mouse (shift + scroll?)
  • Ruler tool to measure distances
  • Display scouts as additional volumes

  • Render surface envelope in the MRI as a thin line instead of the full interpolation matrix
    Or use inpolyhedron to get a surface mask and then erode it to get the volume envelope

  • Surface>Volume interpolation: Use spm_mesh_to_grid instead of tess_tri_interp

• Defacing:

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

  • Removing MNI face mask using MNI coordinates (mask available ICMB152 2023b)

• Bug import anatomy: Requested nVert > high-resolution cortex surface: Creates an empty cortex_0V

• BrainSuite:

  • Use same colors for left and right for anatomical atlases
  • Use for volume coregistration (rigid / non-rigid)
  • USCBrain: Add default electrodes positions

  • Remove BrainSuite1 when not needed anymore

• Brain2mesh: Add import of 10-10 positions
• Templates for different ages:

  • MNI: https://www.bic.mni.mcgill.ca/ServicesAtlases/NIHPD-obj1

  • Pediatric head atlases: https://www.pedeheadmod.net/pediatric-head-atlases-v1-2/

  • https://iopscience.iop.org/article/10.1088/2057-1976/ab4c76

  • https://www.biorxiv.org/content/biorxiv/early/2020/02/09/2020.02.07.939447.full.pdf

  • John Richards: https://www.nitrc.org/frs/?group_id=1361

  • Neurodev database: https://jerlab.sc.edu/projects/neurodevelopmental-mri-database/

  • https://openneuro.org/datasets/ds000256/versions/00002

  • https://osf.io/axz5r/

• Scouts:
  • Display edges in the middle of the faces instead of the vertices
• Parcellating volume grids: scikit-learn.cluster.Ward

• Geodesic distance calculations:
  https://www.mathworks.com/matlabcentral/fileexchange/6110-toolbox-fast-marching

• Improving the registration between EEG and anatomy templates:
  • Warping: Improve the basic alignment of the digitized electrodes on the templat, possibly with Cz and other anatomical landmarks
  • EEG template positions: rework using a standardized Cz position (+ other landmarks)

Forward modeling

• DUNEuro/FEM:

  • Add lesion mask to SimNIBS: https://simnibs.github.io/simnibs/build/html/documentation/command_line/add_tissues_to_upsampled.html#add-tissues-to-upsampled-doc

  • GeomtryAdapted: Buggy?

  • Display differences between leadfields: amplitude of difference (right-click > Compare)

  • Display sensitivity on FEM surface
• OpenMEEG: Detect bad results + exclude from leadfield
• BEM single sphere: Get implementation from MNE-Python (John Mosher)
• Add eyes models to attract eye activity (Put a dipole in each eye)

Source modeling

• Reproduce results in "Simultaneous human intracerebral stimulation and HD-EEG, ground-truth for source localization methods": https://www.nature.com/articles/s41597-020-0467-x

• eLORETA instead of sLORETA?

  • https://neuroimage.usc.edu/forums/t/compute-eeg-sources-with-sloreta/13425/6

  • https://neuroimage.usc.edu/forums/t/loreta-and-source-localization/30525

  • "eLORETA algorithm is available in the MEG/EEG Toolbox of Hamburg (METH)": https://www.biorxiv.org/content/biorxiv/early/2019/10/17/809285.full.pdf

  • https://github.com/brainstorm-tools/brainstorm3/issues/114

  • Point-spread functions (PSFs) and cross-talk functions: https://mne.tools/stable/auto_examples/inverse/plot_psf_ctf_vertices.html#sphx-glr-auto-examples-inverse-plot-psf-ctf-vertices-py https://www.biorxiv.org/content/biorxiv/early/2019/06/18/672956.full.pdf

  • https://github.com/olafhauk/EEGMEGResolutionAtlas

• Dipoles:
  • Display dipoles in MRI viewer
  • panel_dipoles: Doesn't work with multiple figures (SOLVED?)
• Project sources: Very poor algorithm to project sub-cortical regions and cerebellum
• Maximum:

  • Menu Sources > Maximum value: Doesn't work with volume or mixed head models

  • Panel Get coordinates: Add button "find maximum"

  • Sources on surface: Display peak regions over time (time = color) => A.Gramfort

• Volume grid:
  • Optimize: 3D display (better than 3x3 cubes)
  • Optimize: vol_dilate (with 26 neighbors)

Statistics

• Stat on unconstrained sources?

• Stat/time series: Hide lines going down to zero (Dimitrios: https://neuroimage.usc.edu/forums/t/common-source-activation-across-subjects-and-conditions/1152/21)

• Cluster stat: Add frequency selection option
• ANOVA:
  • Write panel similar to Process1 and Process2
  • Output = 1 file per effect, all grouped in a node "ANOVA"
  • Display several ANOVA maps (from several files) on one single figure, using a "graphic accumulator", towards which one can send any type of graphic object

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

Input / output

• BIDS import:
  • Add option to process to specify the protocol name
  • Disable logging of sub-processes (reloading the previous report should only show process_import_bids)
  • Full support for iEEG and EEG
  • Read real fiducials (OMEGA) / transformation matrices:

    • https://groups.google.com/g/bids-discussion/c/BeyUeuNGl7I

    • https://github.com/bids-standard/bids-specification/issues/752#issuecomment-795880992

    • https://github.com/brainstorm-tools/brainstorm3/issues/139

  • Use BIDS-Matlab?
• Test datasets:
  • See list of test datasets in process_import_bids.m
  • ds004085 / ds004473: Check response epoch + BUG with coordinate interpretation
• BIDS export:
  • EEG, iEEG: Add events.tsv, channel.tsv, electrodes.tsv
  • Anatomy: Add t1w.json (including fiducials)
  • Use BIDS-Matlab?
• EDF+ reader: Add resampling of channels with different sampling rates
• DICOM converter:
  • Add dcm2nii (MRICron)
  • Add MRIConvert
• SPM .mat/.dat: Fix the import of the EEG/SEEG coordinates

• EEG File formats:
  

  • XLTEK: https://github.com/danielmhanover/OpenXLT

  • Persyst .lay: https://github.com/ieeg-portal/Persyst-Reader

  • Nervus .eeg: https://github.com/ieeg-portal/Nervus-Reader

  • Biopac .acq: https://github.com/ieeg-portal/Biopac-Reader

  • BCI2000 Input (via EEGLAB plugin)
• 4D file format:
  • Use reader from MNE-Python: mne.io.read_raw_kit (skip Yokogawa slow library)
  • Reference gradiometers: Keep the orientation of the first or second coil?
  • Reference gradiometers: Add the sensor definition from coil_def.dat
  • Validate with phantom recordings that noise compensation is properly taken into account
  • The noise compensation is considered to be always applied on the recordings, not sure this assumption is always correct
  • 4D phantom tutorial (JM Badier?)
• BST-BIN: Add compression to .bst
• MINC MRI: Add support for "voxel to world" transformation (vox2ras) similarly to .nii

Distribution

• Java-free Matlab: All references of functions below must be removed

  • JavaFrame: screencapture.m (used for screen captures of videos)

  • Actxcontrol: Used for video-EEG

    • uihtml + JavaScript callbacks?

    • ActiveX in .NET app?
    • Pure Java framce + VLC java plugin?
    • Other video player?

  • Javacomponent:

    • mri_editMask
    • figure_mri
    • process_bandpass

  • List .jar files used from Matlab distribution (e.g. dom) => Check all the import calls

• Cleanup GitHub repository:

  • https://github.com/brainstorm-tools/brainstorm3/issues/473

  • Move external I/O libraries as plugins:
    • mne-matlab
    • CEDS64ML
    • edfimport
    • eeprobe
    • son
    • ricoh
    • yokogawa

Documentation

• All tutorial datasets in BIDS (including introduction tutorials)
• Deface the MRIs of all the tutorials

• Count GitHub clones in the the download stats

• MNE-Python 1.0: Test and update install documentation
• Tutorial OMEGA/BIDS:
  • Update the organization of derivatives folder (full FS folders)
  • Download example datasets directly from the OMEGA repository

• New tutorials:
  

  • Other public datasets: https://github.com/INCF/BIDS-examples/tree/bep008_meg/

  • EEG/research

  • Cam-CAN database: https://camcan-archive.mrc-cbu.cam.ac.uk/dataaccess/<<BR>>(download new datasets, including maxfiltered files and manual fiducial placements)

  • MEG steady-state / high-gamma visual / frequency tagging

  • Reproduce results from "Simultaneous human intracerebral stimulation and HD-EEG, ground-truth for source localization methods": https://www.nature.com/articles/s41597-020-0467-x

  • Stand-alone ICA tutorial

  • https://archive.physionet.org/ [data and tools]

Current bugs

• Image viewer:
  • Difficult to get to 100%
  • Buggy on some systems
• 2DLayout:
  • (TF) Units are weird with % values
  • (TF) Difficult to navigate in frequencies: Scaling+changing frequency resets the scaling
• Progress bar:
  • Doesn't close properly on some Linux systems (SOLVED?)
  • Focus requests change workspace when processing constantly (Linux systems) (SOLVED?)

Distributed computing

• Options from FieldTrip:

  • Loose collection of computers: https://github.com/fieldtrip/fieldtrip/tree/master/peer

  • Single multicore machine: https://github.com/fieldtrip/fieldtrip/tree/master/engine

  • Batch system: https://github.com/fieldtrip/fieldtrip/tree/master/qsub

  • Documentation: https://www.fieldtriptoolbox.org/faq/what_are_the_different_approaches_i_can_take_for_distributed_computing/

• 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/

Some notes

== Other interesting resources to check for renewal == by tmedani:

neurojson: https://neurojson.org/ demo:https://neurojson.org/wiki/index.cgi?Doc/Start/User#Dynamically_downloading_caching_linked_binary_data_resources

The Neuroscience Gateway (NSG) https://github.com/sccn/nsgportal/wiki https://www.nsgportal.org/index.html

BIDSAPP

https://open-neuroscience.com/en/

OPM OPM : https://vbmeg.atr.jp/software/ Soft: https://vbmeg.atr.jp/docs/v22/static/vbmeg2_opm_simulation.html#toc4 https://www.sciencedirect.com/science/article/pii/S1053811923004081 https://www.fieldtriptoolbox.org/tutorial/preprocessing_opm/ https://www.fieldtriptoolbox.org/getting_started/opm_fil/ https://mne.tools/stable/auto_examples/datasets/opm_data.html

Potential confusion: sLoreta units, on the tutorial it says the units are A.m and on the forum it says unitless.

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"