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

178 Scopus citations


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 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
Issue number2
StatePublished - Feb 15 2011

Bibliographical note

Funding Information:
We are grateful to Christopher Wilke for useful discussions and Yunfeng Lu for assistance in the testing of eConnectome software. The development of eConnectome was supported in part by NIH/NIBIB under grants RO1EB006433 and RO1EB007920 to Bin He.


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


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