Uncovering the large-scale effects and mechanisms of brain disease through whole-brain computational modeling
The activity of the brain at rest reveals an intricate functional architecture and yet, the underlying mechanisms generating it are still not well understood. Whole-brain computational models have turned into fundamental tools for exploring these mechanisms as well as to uncover the relationship bet...
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| Tipo de recurso: | tesis doctoral |
| Estado: | Versión publicada |
| Fecha de publicación: | 2018 |
| País: | España |
| Institución: | CBUC, CESCA |
| Repositorio: | TDR. Tesis Doctorales en Red |
| OAI Identifier: | oai:www.tdx.cat:10803/565910 |
| Acceso en línea: | http://hdl.handle.net/10803/565910 |
| Access Level: | acceso abierto |
| Palabra clave: | Whole-brain modeling Brain disease Brain networks Complexity Criticality Modelos computacionales cerebrales a gran escala Enfermedades cerebrales Redes cerebrales Complejidad Criticalidad 62 |
| Sumario: | The activity of the brain at rest reveals an intricate functional architecture and yet, the underlying mechanisms generating it are still not well understood. Whole-brain computational models have turned into fundamental tools for exploring these mechanisms as well as to uncover the relationship between structure and function both in the healthy and diseased brain. The results presented here aim to show that these models can be used as unique frameworks for understanding the origin of disease as well as to understand how local alterations have global and systemic eects. These models can be used to alter local dynamics by means of artificial stimulation and lesioning without the need of clinical interventions. Such alterations resonate with empirical observations, pinpointing to the origin of the mechanisms generating disease. |
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