Neural modelling of psychiatric disorders

Abstract

The paper reviews recent neural modelling studies of psychiatric disorders. Numerous aspects of psychiatric disturbances have been investigated, such as the role of synaptic changes in the pathogenesis of Alzheimer's disease, the study of spurious attractors as possible neural correlates of schizophrenic positive symptoms, and the exploration of the ability of feed-forward and recurrent networks to quantitatively model the cognitive performance of schizophrenic patients. Current models all employ considerable simplifications, both on the level of the behavioural phenomenology they seek to explore, and on the level of their structure and dynamics. However, it is encouraging to realize that the disruption of just a few simple computational mechanisms can lead to behaviours which correspond to some of the clinical features of psychiatric disorders, and can shed light on their pathogenesis.