Study of brain complexity using information theory tools
The human brain is a complex network that shares and processes information by using the structural paths between areas in order to perform a function. The connectome models the brain as a graph where nodes correspond to brain regions and edges to structural or functional connections. In this thesis,...
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| Tipo de recurso: | tesis doctoral |
| Estado: | Versión publicada |
| Fecha de publicación: | 2016 |
| País: | España |
| Institución: | CBUC, CESCA |
| Repositorio: | TDR. Tesis Doctorales en Red |
| OAI Identifier: | oai:www.tdx.cat:10803/404384 |
| Acceso en línea: | http://hdl.handle.net/10803/404384 |
| Access Level: | acceso abierto |
| Palabra clave: | Connectome Connectoma Conectoma Brain complexity Complexitat del cervell Complejidad del cerebro Information theory Teoria de la informació Teoría de la información Brain networks Xarxes cerebrals Redes cerebrales 004 616.8 |
| Sumario: | The human brain is a complex network that shares and processes information by using the structural paths between areas in order to perform a function. The connectome models the brain as a graph where nodes correspond to brain regions and edges to structural or functional connections. In this thesis, we investigate and provide new methods to study the brain complexity and improve the understanding of the brain functioning by using information theory. Firstly, we focus on brain parcellation, which is a key step to perform brain studies since determines the regions to be analyzed. Secondly, we focus on the definition of measures to characterize the complexity of the brain networks. Finally, the consistency of the results across healthy subjects using functional or structural connectivity data, demonstrates the flexibility and robustness of the proposed methods |
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