Basis profile curve identification to understand electrical stimulation effects in human brain networks
DC Field | Value | Language |
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dc.contributor.author | Miller, Kai J. | - |
dc.contributor.author | Mueller, Klaus-Robert | - |
dc.contributor.author | Hermes, Dora | - |
dc.contributor.author | van Vugt, Marieke Karlijn | - |
dc.contributor.author | Marinazzo, Daniele | - |
dc.contributor.author | van Vugt, Marieke Karlijn | - |
dc.contributor.author | Marinazzo, Daniele | - |
dc.contributor.author | van Vugt, Marieke Karlijn | - |
dc.contributor.author | Marinazzo, Daniele | - |
dc.date.accessioned | 2022-02-24T02:40:34Z | - |
dc.date.available | 2022-02-24T02:40:34Z | - |
dc.date.created | 2022-02-15 | - |
dc.date.issued | 2021-09 | - |
dc.identifier.issn | 1553-734X | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/136690 | - |
dc.description.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. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | PUBLIC LIBRARY SCIENCE | - |
dc.subject | EVOKED-POTENTIALS | - |
dc.subject | RESPONSES | - |
dc.subject | CORTEX | - |
dc.title | Basis profile curve identification to understand electrical stimulation effects in human brain networks | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Mueller, Klaus-Robert | - |
dc.identifier.doi | 10.1371/journal.pcbi.1008710 | - |
dc.identifier.scopusid | 2-s2.0-85114443187 | - |
dc.identifier.wosid | 000724165700001 | - |
dc.identifier.bibliographicCitation | PLOS COMPUTATIONAL BIOLOGY, v.17, no.9 | - |
dc.relation.isPartOf | PLOS COMPUTATIONAL BIOLOGY | - |
dc.citation.title | PLOS COMPUTATIONAL BIOLOGY | - |
dc.citation.volume | 17 | - |
dc.citation.number | 9 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Biochemistry & Molecular Biology | - |
dc.relation.journalResearchArea | Mathematical & Computational Biology | - |
dc.relation.journalWebOfScienceCategory | Biochemical Research Methods | - |
dc.relation.journalWebOfScienceCategory | Mathematical & Computational Biology | - |
dc.subject.keywordPlus | EVOKED-POTENTIALS | - |
dc.subject.keywordPlus | RESPONSES | - |
dc.subject.keywordPlus | CORTEX | - |
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