Basis profile curve identification to understand electrical stimulation effects in human brain networks
- Authors
- Miller, Kai J.; Mueller, Klaus-Robert; Hermes, Dora; van Vugt, Marieke Karlijn; Marinazzo, Daniele; van Vugt, Marieke Karlijn; Marinazzo, Daniele; van Vugt, Marieke Karlijn; Marinazzo, Daniele
- Issue Date
- 9월-2021
- Publisher
- PUBLIC LIBRARY SCIENCE
- Citation
- PLOS COMPUTATIONAL BIOLOGY, v.17, no.9
- Indexed
- SCIE
SCOPUS
- Journal Title
- PLOS COMPUTATIONAL BIOLOGY
- Volume
- 17
- Number
- 9
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/136690
- DOI
- 10.1371/journal.pcbi.1008710
- ISSN
- 1553-734X
- Abstract
- Brain networks can be explored by delivering brief pulses of electrical current in one area while measuring voltage responses in other areas. We propose a convergent paradigm to study brain dynamics, focusing on a single brain site to observe the average effect of stimulating each of many other brain sites. Viewed in this manner, visually-apparent motifs in the temporal response shape emerge from adjacent stimulation sites. This work constructs and illustrates a data-driven approach to determine characteristic spatiotemporal structure in these response shapes, summarized by a set of unique basis profile curves (BPCs). Each BPC may be mapped back to underlying anatomy in a natural way, quantifying projection strength from each stimulation site using simple metrics. Our technique is demonstrated for an array of implanted brain surface electrodes in a human patient. This framework enables straightforward interpretation of single-pulse brain stimulation data, and can be applied generically to explore the diverse milieu of interactions that comprise the connectome.
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Collections - Graduate School > Department of Artificial Intelligence > 1. Journal Articles
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