Noninvasive electromagnetic source imaging of spatiotemporally distributed epileptogenic brain sources

• Published in: Nature communications Vol. 11; no. 1; pp. 1946 - 15
• Main Authors: Sohrabpour, Abbas, Cai, Zhengxiang, Ye, Shuai, Brinkmann, Benjamin, Worrell, Gregory, He, Bin
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 23.04.2020; Nature Publishing Group; Nature Portfolio
• Subjects: 631/378/116; 639/766/25; 692/617/375/178; 9/26; Algorithms; Biomedical engineering; Brain; Brain - pathology; Brain - physiopathology; Brain - surgery; Brain mapping; Computer Simulation; Convulsions & seizures; EEG; Electroencephalography; Electroencephalography - methods; Electromagnetic measurement; Electromagnetic Phenomena; Epilepsies, Partial - pathology; Epilepsies, Partial - physiopathology; Epilepsies, Partial - surgery; Epilepsy; Functional Neuroimaging - methods; Humanities and Social Sciences; Humans; Imaging techniques; Medical imaging; Metabolism; multidisciplinary; Networks; Neuroimaging; Reproducibility of Results; Science; Science (multidisciplinary); Seizures; Signal Processing, Computer-Assisted; Spatial analysis
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-020-15781-0

Brain networks are spatiotemporal phenomena that dynamically vary over time. Functional imaging approaches strive to noninvasively estimate these underlying processes. Here, we propose a novel source imaging approach that uses high-density EEG recordings to map brain networks. This approach objectively addresses the long-standing limitations of conventional source imaging techniques, namely, difficulty in objectively estimating the spatial extent, as well as the temporal evolution of underlying brain sources. We validate our approach by directly comparing source imaging results with the intracranial EEG (iEEG) findings and surgical resection outcomes in a cohort of 36 patients with focal epilepsy. To this end, we analyzed a total of 1,027 spikes and 86 seizures. We demonstrate the capability of our approach in imaging both the location and spatial extent of brain networks from noninvasive electrophysiological measurements, specifically for ictal and interictal brain networks. Our approach is a powerful tool for noninvasively investigating large-scale dynamic brain networks. Noninvasive electromagnetic measurements are utilized effectively to estimate large scale dynamic brain networks. Sohrabpour et al. propose a novel electrophysiological source imaging approach to estimate the location and size of epileptogenic tissues in patients with epilepsy.