supFunSim: Spatial Filtering Toolbox for EEG

Krzysztof Rykaczewski, Jan Nikadon, Włodzisław Duch, Tomasz Piotrowski

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Brain activity pattern recognition from EEG or MEG signal analysis is one of the most important method in cognitive neuroscience. The supFunSim library is a new Matlab toolbox which generates accurate EEG forward model and implements a collection of spatial filters for EEG source reconstruction, including the linearly constrained minimum-variance (LCMV), eigenspace LCMV, nulling (NL), and minimum-variance pseudo-unbiased reduced-rank (MV-PURE) filters in various versions. It also enables source-level directed connectivity analysis using partial directed coherence (PDC) measure. The supFunSim library is based on the well-known FieldTrip toolbox for EEG and MEG analysis and is written using object-oriented programming paradigm. The resulting modularity of the toolbox enables its simple extensibility. This paper gives a complete overview of the toolbox from both developer and end-user perspectives, including description of the installation process and use cases.

Original languageEnglish
Pages (from-to)107-125
Number of pages19
JournalNeuroinformatics
Volume19
Issue number1
DOIs
StatePublished - Jan 2021
Externally publishedYes

Funding

This work was supported by a grant from the Polish National Science Centre (UMO-2016/20/W/NZ4/00354). The authors are grateful to anonymous reviewers for their constructive comments which surely promoted the usability of the supFunSim toolbox and the readability of the revised manuscript.

FundersFunder number
Polish National Science CentreUMO-2016/20/W/NZ4/00354

    Keywords

    • Localization
    • Matlab
    • Object-oriented
    • Reconstruction
    • Toolbox

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