Basis profile curve identification to understand electrical stimulation effects in human brain networks.
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 brai...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2021-09-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1008710&type=printable |
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| _version_ | 1850159957740093440 |
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| author | Kai J Miller Klaus-Robert Müller Dora Hermes |
| author_facet | Kai J Miller Klaus-Robert Müller Dora Hermes |
| author_sort | Kai J Miller |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-41a37880e442491f8abc7cbd5016e083 |
| institution | OA Journals |
| issn | 1553-734X 1553-7358 |
| language | English |
| publishDate | 2021-09-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj-art-41a37880e442491f8abc7cbd5016e0832025-08-20T02:23:18ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582021-09-01179e100871010.1371/journal.pcbi.1008710Basis profile curve identification to understand electrical stimulation effects in human brain networks.Kai J MillerKlaus-Robert MüllerDora HermesBrain 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.https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1008710&type=printable |
| spellingShingle | Kai J Miller Klaus-Robert Müller Dora Hermes Basis profile curve identification to understand electrical stimulation effects in human brain networks. PLoS Computational Biology |
| title | Basis profile curve identification to understand electrical stimulation effects in human brain networks. |
| title_full | Basis profile curve identification to understand electrical stimulation effects in human brain networks. |
| title_fullStr | Basis profile curve identification to understand electrical stimulation effects in human brain networks. |
| title_full_unstemmed | Basis profile curve identification to understand electrical stimulation effects in human brain networks. |
| title_short | Basis profile curve identification to understand electrical stimulation effects in human brain networks. |
| title_sort | basis profile curve identification to understand electrical stimulation effects in human brain networks |
| url | https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1008710&type=printable |
| work_keys_str_mv | AT kaijmiller basisprofilecurveidentificationtounderstandelectricalstimulationeffectsinhumanbrainnetworks AT klausrobertmuller basisprofilecurveidentificationtounderstandelectricalstimulationeffectsinhumanbrainnetworks AT dorahermes basisprofilecurveidentificationtounderstandelectricalstimulationeffectsinhumanbrainnetworks |