Multimodal Investigation of Neurobiological Alterations in the At Risk Mental State and First Episode of Psychosis
The main aim of my doctoral work was to investigate the extent to which neuroanatomical and neurofunctional alterations previously reported in patients with chronic schizophrenia represent neurobiological markers of vulnerability to psychosis or are specifically associated with the onset of the disease. To this purpose, I have applied a range of neuroimaging techniques and analytical approaches to the study of 21 individuals with an At Risk Mental State (ARMS), 26 patients with a First Episode of Psychosis (FEP) and 24 matched healthy controls. I initially focused on the characterisation of neuroanatomical alterations by performing a comparison between voxel-based morphometry and cortical thickness measurements. I then moved on to the investigation of alterations of regional activation and interregional coupling within a network of fronto-temporal regions, using a standard functional Magnetic Resonance Imaging (fMRI) and a Dynamic Casual Modelling (DCM) analysis respectively. Subsequently, I characterised white matter integrity of fronto-temporal connections by performing a virtual in vivo interactive dissection of the main white matter tracts thought to connect temporal, cingulate and frontal regions. Finally, I explored the relationship between fronto-temporal structural connectivity and interregional coupling by performing a correlation analysis between the subject-specific measurements of white matter integrity and functional connectivity. The results of the present multimodal investigation suggest that regional fronto-temporal neuroanatomical and neurofunctional alterations precede the emergence of psychosis, consistent with a neurodevelopmental model of the illness, while most dysconnectivity alterations within the same network may only appear in the presence of active and severe symptoms or as illness progresses. Findings are discussed in relation to their implication for: (i) current neurobiological models of the disease and (ii) the identification of neurobiological markers which could inform early diagnosis.
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