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eConnectome: A MATLAB toolbox for mapping and imaging of brain functional connectivity
Open accessAbstract
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.
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“The eConnectome approach (104, 105) has stirred interest in studying pathological networks such as epilepsy, where determining the source that drives seizures is of particular importance (106).”
From Electrophysiological source imaging: A noninvasive window to brain dynamics (2018) · cites this paper as [104]
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Metadata
- Authors
- He, B., Dai, Y., Astolfi, L., Babiloni, F., Yuan, H., & Yang, L.
- Affiliations
- University of Minnesota (US)
- Fondazione Santa Lucia (IT)
- Corresponding author
- He, Bin
- Venue
- Journal of Neuroscience Methods
- Publisher
- Elsevier BV
- Published
- 2011-02
- Volume
- 195
- Issue
- 2
- Pages
- 261-269
- ISSN
- 0165-0270 (ISSN-L)
- PMC
- PMC3244474
- OpenAlex
- W2086498469
- Cited by
- 229
- References
- 46
- Citations by year
- 2026: 7 · 2025: 9 · 2024: 13 · 2023: 8 · 2022: 14 · 2021: 17 · 2020: 17 · 2019: 18 · 2018: 22 · 2017: 20 · 2016: 19 · 2015: 23 · 2014: 17 · 2013: 11 · 2012: 9
- FWCI
- 4.85
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Neuroscience Methods (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- IRIS Research product catalog (Sapienza University of Rome) (submittedVersion)
- Funders
- NIH/NIBIB (RO1EB006433, RO1EB007920)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- brain functional connectivity, EEG, electrocorticography, Granger causality, directed transfer function, MATLAB toolbox
- MeSH terms
- Brain, Brain Mapping, Computer Simulation, Diagnostic Imaging, Electroencephalography, Evoked Potentials, Humans, Signal Processing, Computer-Assisted, Software, Time Factors
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