Structural, geometric and genetic factors predict interregional brain connectivity patterns probed by electrocorticography

Electrocorticography (ECoG) data can be used to estimate brain-wide connectivity patterns. Yet, the invasiveness of ECoG, incomplete cortical coverage, and variability in electrode placement across individuals make the network analysis of ECoG data challenging. Here, we show that the architecture of...

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Veröffentlicht in:	Nature biomedical engineering 2019-11, Vol.3 (11), p.902-916
Hauptverfasser:	Betzel, Richard F., Medaglia, John D., Kahn, Ari E., Soffer, Jonathan, Schonhaut, Daniel R., Bassett, Danielle S.
Format:	Artikel
Sprache:	eng
Schlagworte:	59/57 631/378 639/705/1041 639/705/531 Adolescent Adult Aged Biomedical and Life Sciences Biomedical Engineering/Biotechnology Biomedicine Brain Brain - physiology Brain architecture Brain Mapping Cerebral cortex Computer Simulation Electrocorticography - methods Electrodes Epilepsy Euclidean geometry Gene Expression Gene Ontology Genetic factors Human Genetics Humans Invasiveness Middle Aged Models, Biological Network analysis Neural networks Prediction models Substantia alba Young Adult
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