Identification of optimal structural connectivity using functional connectivity and neural modeling
The complex network dynamics that arise from the interaction of the brain’s structural and functional architectures give rise to mental/nfunction. Theoretical models demonstrate that the structure–function relation is maximal when the global network dynamics operate at/na critical point of state tra...
| Autores: | , , , , , , , |
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| Formato: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2014 |
| País: | España |
| Recursos: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:10230/23090 |
| Acesso em linha: | http://hdl.handle.net/10230/23090 http://dx.doi.org/10.1523/JNEUROSCI.4423-13.2014 |
| Access Level: | acceso abierto |
| Palavra-chave: | Anatomy fMRI Functional connectivity Modeling |
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oai:recercat.cat:10230/23090 |
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España |
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Identification of optimal structural connectivity using functional connectivity and neural modeling Deco, Gustavo McIntosh, Anthony R. Shen, Kelly Hutchison, R. Matthew Menon, Ravi S. Everling, Stefan Hagmann, Patric Jirsa, Viktor K. Anatomy fMRI Functional connectivity Modeling The complex network dynamics that arise from the interaction of the brain’s structural and functional architectures give rise to mental/nfunction. Theoretical models demonstrate that the structure–function relation is maximal when the global network dynamics operate at/na critical point of state transition. In the present work, we used a dynamic mean-field neural model to fit empirical structural connectivity/n(SC) and functional connectivity (FC) data acquired in humans and macaques and developed a new iterative-fitting algorithm to optimize/nthe SC matrix based on the FC matrix. A dramatic improvement of the fitting of the matrices was obtained with the addition of a small/nnumber of anatomical links, particularly cross-hemispheric connections, and reweighting of existing connections. We suggest that the/nnotion of a critical working point, where the structure–function interplay is maximal, may provide a new way to link behavior and/ncognition, and a new perspective to understand recovery of function in clinical conditions. G.D. was supported by the European Research Council Advanced Grant DYSTRUCTURE (n.295129), by the Spanish/nResearch Project SAF2010-16085, and by the CONSOLIDER-INGENIO 2010 Programme CSD2007-00012. V.K.J. and/nG.D. are supported by FP7-ICT BrainScales. The research reported herein was supported by Collaborative Research/nGrant 220020255 from the James S. McDonnell Foundation. P.H. is supported by the Leenaards Foundation Society for Neuroscience http://hdl.handle.net/10230/23090 http://dx.doi.org/10.1523/JNEUROSCI.4423-13.2014 |
| title |
Identification of optimal structural connectivity using functional connectivity and neural modeling |
| spellingShingle |
Identification of optimal structural connectivity using functional connectivity and neural modeling Deco, Gustavo Anatomy fMRI Functional connectivity Modeling |
| title_short |
Identification of optimal structural connectivity using functional connectivity and neural modeling |
| title_full |
Identification of optimal structural connectivity using functional connectivity and neural modeling |
| title_fullStr |
Identification of optimal structural connectivity using functional connectivity and neural modeling |
| title_full_unstemmed |
Identification of optimal structural connectivity using functional connectivity and neural modeling |
| title_sort |
Identification of optimal structural connectivity using functional connectivity and neural modeling |
| author |
Deco, Gustavo |
| author_facet |
Deco, Gustavo McIntosh, Anthony R. Shen, Kelly Hutchison, R. Matthew Menon, Ravi S. Everling, Stefan Hagmann, Patric Jirsa, Viktor K. |
| author_role |
author |
| author2 |
McIntosh, Anthony R. Shen, Kelly Hutchison, R. Matthew Menon, Ravi S. Everling, Stefan Hagmann, Patric Jirsa, Viktor K. |
| author2_role |
author author author author author author author |
| topic |
Anatomy fMRI Functional connectivity Modeling |
| topic_facet |
Anatomy fMRI Functional connectivity Modeling |
| description |
The complex network dynamics that arise from the interaction of the brain’s structural and functional architectures give rise to mental/nfunction. Theoretical models demonstrate that the structure–function relation is maximal when the global network dynamics operate at/na critical point of state transition. In the present work, we used a dynamic mean-field neural model to fit empirical structural connectivity/n(SC) and functional connectivity (FC) data acquired in humans and macaques and developed a new iterative-fitting algorithm to optimize/nthe SC matrix based on the FC matrix. A dramatic improvement of the fitting of the matrices was obtained with the addition of a small/nnumber of anatomical links, particularly cross-hemispheric connections, and reweighting of existing connections. We suggest that the/nnotion of a critical working point, where the structure–function interplay is maximal, may provide a new way to link behavior and/ncognition, and a new perspective to understand recovery of function in clinical conditions. |
| publishDate |
2014 |
| format |
article |
| status_str |
publishedVersion |
| url |
http://hdl.handle.net/10230/23090 http://dx.doi.org/10.1523/JNEUROSCI.4423-13.2014 |
| eu_rights_str_mv |
openAccess |
| publisher |
Society for Neuroscience |
| institution |
Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| collection |
Recercat. Dipósit de la Recerca de Catalunya |
| reponame_str |
Recercat. Dipósit de la Recerca de Catalunya |
| instname_str |
Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| _version_ |
1878439926980149248 |
| publishDateSort |
2014 |
| author_browse |
Deco, Gustavo Everling, Stefan Hagmann, Patric Hutchison, R. Matthew Jirsa, Viktor K. McIntosh, Anthony R. Menon, Ravi S. Shen, Kelly |
| publisherStr |
Society for Neuroscience |
| score |
6.924472 |