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In this Doctoral Thesis, the characterization of the altered functional network structure and neural dynamics in schizophrenia during a cognitive task has been addressed. Firstly, new evidences for the dysconnectivity hypothesis and the aberrant salience hypothesis in schizophrenia were found. Abnormal response to novel and relevant stimulus (aberrant salience) was recurrently found in patients with schizophrenia in this Thesis. This abnormal response was accompanied by a diminished integration among brain regions connected by long-range interactions. Secondly, novel findings about possible underpinnings of these anomalies were provided by means of the study of the structural network and functional local measures based on regularity. Importantly, a hyperactivation focused on segregated assemblies of neuronal entities during the stimulus expectation can suppose the main difference between the odd response during cognition in schizophrenia. Thirdly, a novel graph measure of network complexity was developed. SCG provides an estimation of the ratio between the order of the network and the amount of information stored in it. The measure is insensitive to changes in connectivity strength and network size for networks large enough (\(N > 30\)). Having shown its virtues, SCG provides new clues about brain network dynamics in schizophrenia during cognition. Finally, the previously mentioned findings using SGC allow us to propose a novel network modeling to describe the brain network dynamics and the main differences between healthy and schizophrenia subjects. This network modeling identifies different reorganization strategies of the brain network as response to an oddball task for patients with schizophrenia, which could be the basis for new studies focused on the heterogeneity in this disorder.
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