Aponte, Eduardo A.
- Doctoral Thesis
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Computational psychiatry is a novel field devoted to improving the understanding and treatment of psychiatric disorders through quantitative methods. A significant part of this endeavour is the formulation and evaluation of models that describe relevant physiological and cognitive processes. In this dissertation, we aim to contribute to this field in two manners. First, we present and evaluate methods for model selection with an emphasis on models of brain connectivity. Our main contribution is to implement and extend thermodynamic integration, a method that has not been used in computational neuroscience in the past. Second, we develop statistical models of eye movements in two paradigms that are relevant for psychiatric research: the double step and the antisaccade task. The models developed here are probabilistic in nature and therefore we use the methods presented in the first section to solve several empirical questions related to learning, inhibitory control, and rule guided behavior in the oculomotor system Show more
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Organisational unit03955 - Stephan, Klaas E. / Stephan, Klaas E.
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