EConnectome: A MATLAB toolbox for mapping and imaging of brain functional connectivity

Bin He, Yakang Dai, Laura Astolfi, Fabio Babiloni, Han Yuan, Lin Yang

Research output: Contribution to journalArticlepeer-review

137 Scopus citations

Abstract

We have developed a MATLAB-based toolbox, eConnectome (electrophysiological connectome), for mapping and imaging functional connectivity at both the scalp and cortical levels from the electroencephalogram (EEG), as well as from the electrocorticogram (ECoG). Graphical user interfaces were designed for interactive and intuitive use of the toolbox. Major functions of eConnectome include EEG/ECoG preprocessing, scalp spatial mapping, cortical source estimation, connectivity analysis, and visualization. Granger causality measures such as directed transfer function and adaptive directed transfer function were implemented to estimate the directional interactions of brain functional networks, over the scalp and cortical sensor spaces. Cortical current density inverse imaging was implemented using a generic realistic geometry brain-head model from scalp EEGs. Granger causality could be further estimated over the cortical source domain from the inversely reconstructed cortical source signals as derived from the scalp EEG. Users may implement other connectivity estimators in the framework of eConnectome for various applications. The toolbox package is open-source and freely available at http://econnectome.umn.edu under the GNU general public license for noncommercial and academic uses.

Original languageEnglish (US)
Pages (from-to)261-269
Number of pages9
JournalJournal of Neuroscience Methods
Volume195
Issue number2
DOIs
StatePublished - Feb 15 2011

Keywords

  • ECoG
  • EConnectome
  • EEG
  • Functional connectivity
  • MATLAB
  • Source imaging

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