What's next

A roadmap to the future developments of Brainstorm.

Recordings

• 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:
  • 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
• 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?

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)
• Smooth display from figure_image (ERPimage, raster plot...)

• 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
• 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):

Connectivity

• 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
• 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)
    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)
• Time-resolved correlation/coherence: Display as time bands

• Tutorial coherence [1xN] : Reproduce FieldTrip results?

• Connect NxN: Display as time series > Display warning before trying to open too many signals

Processes

• Decoding/Classifiers: Implement Dimitrios and scikit-learn algorithms
• Allow processes in Python and Java
• Add MNE-Python functions:
  • scikit-learn classifiers
  • Implement data exchange with MNE-Python: write FIF files from Brainstorm and/or pass python objects in memory instead of FIF files

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

  • SSS/tSSS cleaning
  • Reproduce other tutorials / examples
  • 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_sourcemodel: Compute MNI transformation (linear and non-linear) => Peter

  • ft_prepare_heamodel: Add support from BEM surfaces from the Brainstorm database
  • Freqanalysis: ITC
  • ft_read_atlas('TTatlas+tlrc.BRICK');

  • 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)
  • 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)

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

• ICA:
  • 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

  • Use faster methods (MNE-Python?)
  • Add methods: SOBI, Fastica, AMICA/CUDICA (recommended by S Makeig)

  • 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

  • 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
    (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

• 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

  • 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
  • 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.
  • Extend clusters tab to display of TF to overlay TF signals (Svet)
  • When normalizing with baseline: Propagate with the edge effects marked in TFmask
  • Allow baseline normalization of files computed with time bands
  • 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.
• 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

  • Fix units in simulation processes => no *1e-9 in "simulate recordings"

  • Use "add noise" process from Hui-Ling (in Work/Dev/Divers)
• 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

• Sensitivity maps: https://mne.tools/stable/auto_examples/forward/plot_forward_sensitivity_maps.html

• Use 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

• 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

• Display source maps on a flat 2D cortex projection (Mollweide projection): https://neuroimage.usc.edu/forums/t/source-model-display-and-output/13940/5

Anatomy

• Keep ASEG volume + display region name in MRI viewer
• Multi-Scale Brain Parcellator (Lausanne2008):

  • https://github.com/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

• 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

  • 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

• CAT12: Optimize interpolation of atlases (import is super slow...)

• BrainSuite:

  • Add new labels to all BrainSuite anatomy templates

  • Use same colors for left and right for anatomical atlases
  • Use for volume coregistration (rigid / non-rigid)
• FEM 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

  • MRI to FEM mesh generation
• * Cut the MRI (T1 and T2) 40 mm below the skull alomh axial plan to avoid unnecessary time computation

  • Process the FEM cortex (either from CAT or SimNibs) and fits all the dipoles within the grey matter (important in the case where white matter and scf are considered)

• Scouts:
  • Display edges in the middle of the faces instead of the vertices
  • 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)

• Parcellating volume grids: scikit-learn.cluster.Ward
• 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

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

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

Statistics

• ANOVA:
  • Which functions to use?
  • Write panel similar to Process1 and Process2 to allow the
  • 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

• Quality control before statistics, on condition averages across subjects:
  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

Input / output

• Bug import multiple files: use same "time" for all files
• BIDS import:
  • Read real fiducials
  • Read associated empty room
  • Test all the BIDS examples
• BIDS Export:
  • Add events ts, channel tsv, EEG, iEEG

• XDF import: Use FieldTRip or the EEGLAB plugin, contact Martin Bleichner (Oldenburg)
  https://github.com/sccn/xdf/blob/master/xdf_sample.xdf

• DICOM converter:
  • Add dcm2nii (MRICron)
  • Add MRIConvert

• 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

• 4D file format:
  • Use reader from MNE-Python: mne.io.read_raw_kit (doesn't require 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?)
• 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)
• BST-BIN: Add compression to .bst
• 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

• 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/

  • Rat PAC + high gamma (Soheila)
  • EEG/research

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

  • FieldTrip cortico-muscular coherence tutorial: http://www.fieldtriptoolbox.org/tutorial/coherence

  • 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
  • BIDS-EEG example datasets
• 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

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 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
• in_bst_data_multi: If trials have different sizes, output is random (the one of the first file)
• Canolty maps computation: Fix progress bar

Geeky programming details

• 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.

• 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)

• Hide Java panels instead of deleting them
• Processes with "radio" and "radio_line" options: Replace with "radio_label" and "radio_linelabel"
• Interpolations: Use scatteredInterpolant, griddedInterpolant, triangulation.nearestNeighbor (2014b)
• 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