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: | , , , , , , , |
|---|---|
| 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 |
| Resumo: | 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. |
|---|