Major depression and schizophrenia : investigation of neural mechanisms using neuroimaging and computational modeling of brain function

Depression and schizophrenia are common psychiatric disorders that can be disabling and chronic. This thesis aimed to further elucidate the underlying neural substrates using functional magnetic resonance imaging (fMRI) based studies. Hypothesized impairments in reinforcement learning in depression and schizophrenia were investigated, as were the neural correlates of abnormalities of social information processing in schizophrenia. Computational models of reinforcement learning are based on the concept of a 'prediction error' (PE, discrepancy between the expected and actual outcome) signal to update predictions of rewards and improve action selection. It has been argued that the firing of dopamine neurons encode a reward PE signal that mediates the learning of associations and the attribution of motivational salience to reward-related stimuli. Using model-based fMRI, the encoding of neural PE signals in patients with depression and schizophrenia were investigated. Consistent with hypotheses, patients exhibited different abnormalities in neural PE signals, with the degree of abnormality correlating with increased anhedonia/psychotic symptoms in depression/schizophrenia. These findings are consistent with the suggestion that a disruption in the encoding of PE signals contributes to anhedonia symptoms in depression by disrupting learning and the acquisition of salience of rewarding events. In schizophrenia, abnormal PE signals may contribute to psychosis by promoting aberrant perceptions and abnormal associations. In a different study, the neural responses to social exclusion in schizophrenia were investigated. Schizophrenia patients failed to modulate activity in the medial prefrontal cortex with the degree of exclusion, unlike controls. This highlights the neural substrates of putatively impaired social information processing in schizophrenia. Overall, these findings are consistent with proposals that psychiatric syndromes reflect different disorders of neural valuation. This perspective may help bridge the gap between the biological and phenomenological levels of understanding of depression and schizophrenia, hopefully contributing in the long term to the development of more effective treatments.EThOS - Electronic Theses Online ServiceGBUnited Kingdo