Stimulation-Based Control of Dynamic Brain Networks.
The ability to modulate brain states using targeted stimulation is increasingly being employed to treat neurological disorders and to enhance human performance. Despite the growing interest in brain stimulation as a form of neuromodulation, much remains unknown about the network-level impact of thes...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2016-09-01
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| Series: | PLoS Computational Biology |
| Online Access: | http://europepmc.org/articles/PMC5017638?pdf=render |
| _version_ | 1818612020618985472 |
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| author | Sarah Feldt Muldoon Fabio Pasqualetti Shi Gu Matthew Cieslak Scott T Grafton Jean M Vettel Danielle S Bassett |
| author_facet | Sarah Feldt Muldoon Fabio Pasqualetti Shi Gu Matthew Cieslak Scott T Grafton Jean M Vettel Danielle S Bassett |
| author_sort | Sarah Feldt Muldoon |
| collection | DOAJ |
| description | The ability to modulate brain states using targeted stimulation is increasingly being employed to treat neurological disorders and to enhance human performance. Despite the growing interest in brain stimulation as a form of neuromodulation, much remains unknown about the network-level impact of these focal perturbations. To study the system wide impact of regional stimulation, we employ a data-driven computational model of nonlinear brain dynamics to systematically explore the effects of targeted stimulation. Validating predictions from network control theory, we uncover the relationship between regional controllability and the focal versus global impact of stimulation, and we relate these findings to differences in the underlying network architecture. Finally, by mapping brain regions to cognitive systems, we observe that the default mode system imparts large global change despite being highly constrained by structural connectivity. This work forms an important step towards the development of personalized stimulation protocols for medical treatment or performance enhancement. |
| first_indexed | 2024-12-16T15:39:35Z |
| format | Article |
| id | doaj.art-6977cb6cfd5c4a368bb15650443c3c86 |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-12-16T15:39:35Z |
| publishDate | 2016-09-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-6977cb6cfd5c4a368bb15650443c3c862022-12-21T22:26:04ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582016-09-01129e100507610.1371/journal.pcbi.1005076Stimulation-Based Control of Dynamic Brain Networks.Sarah Feldt MuldoonFabio PasqualettiShi GuMatthew CieslakScott T GraftonJean M VettelDanielle S BassettThe ability to modulate brain states using targeted stimulation is increasingly being employed to treat neurological disorders and to enhance human performance. Despite the growing interest in brain stimulation as a form of neuromodulation, much remains unknown about the network-level impact of these focal perturbations. To study the system wide impact of regional stimulation, we employ a data-driven computational model of nonlinear brain dynamics to systematically explore the effects of targeted stimulation. Validating predictions from network control theory, we uncover the relationship between regional controllability and the focal versus global impact of stimulation, and we relate these findings to differences in the underlying network architecture. Finally, by mapping brain regions to cognitive systems, we observe that the default mode system imparts large global change despite being highly constrained by structural connectivity. This work forms an important step towards the development of personalized stimulation protocols for medical treatment or performance enhancement.http://europepmc.org/articles/PMC5017638?pdf=render |
| spellingShingle | Sarah Feldt Muldoon Fabio Pasqualetti Shi Gu Matthew Cieslak Scott T Grafton Jean M Vettel Danielle S Bassett Stimulation-Based Control of Dynamic Brain Networks. PLoS Computational Biology |
| title | Stimulation-Based Control of Dynamic Brain Networks. |
| title_full | Stimulation-Based Control of Dynamic Brain Networks. |
| title_fullStr | Stimulation-Based Control of Dynamic Brain Networks. |
| title_full_unstemmed | Stimulation-Based Control of Dynamic Brain Networks. |
| title_short | Stimulation-Based Control of Dynamic Brain Networks. |
| title_sort | stimulation based control of dynamic brain networks |
| url | http://europepmc.org/articles/PMC5017638?pdf=render |
| work_keys_str_mv | AT sarahfeldtmuldoon stimulationbasedcontrolofdynamicbrainnetworks AT fabiopasqualetti stimulationbasedcontrolofdynamicbrainnetworks AT shigu stimulationbasedcontrolofdynamicbrainnetworks AT matthewcieslak stimulationbasedcontrolofdynamicbrainnetworks AT scotttgrafton stimulationbasedcontrolofdynamicbrainnetworks AT jeanmvettel stimulationbasedcontrolofdynamicbrainnetworks AT daniellesbassett stimulationbasedcontrolofdynamicbrainnetworks |