Schizophrenia, dopamine, and the prefrontal cortex : theory and computational models

The study of schizophrenia over the past decades has generated a sea of data. This is not entirely surprising in view of the vast size of the subject and the fact that it covers so many disciplines. Unfortunately, all this data has not led us to a single set of con¬ clusions regarding the origin and pathophysiology of schizophrenia. Consequently we have seen a number of theories attempting to describe the underlying biological and psychological processes which are dysfunctional in schizophrenics. This thesis attempts to reconcile some of these theories through the use of computational models which allow us to investigate the links between biological and psychological processes. Existing artificial neural network models of schizophrenia generally have poor bio¬ logical validity (chapter 4). They also rely on the interpretation of mental states as binary patterns of activity, making it difficult to realistically represent complex men¬ tal phenomena such as those that occur in schizophrenia. To try and overcome these problems I have focussed on the information processing properties of certain brain structures implicated in schizophrenia, namely the prefrontal cortex (PfCx) and nu¬ cleus accumbens (NAcc), and I have used models which operate at several different levels. Much work has been done on the structure and function of the PfCx and its involvement in schizophrenia. However, an understanding of the role of dopamine (DA) in the PfCx is still lacking. I have suggested a possible mechanism for the ac¬ tion of DA in the PfCx and illustrated this with biologically plausible models which can be interpreted at cellular and pharmacological levels. I have then related this to schizophrenia. Dysfunctions between brain regions are also suggested to underly the symptoms of schizophrenia. This is the other theme of the thesis, where I have used a reinforcement learning based model to examine interactions between brain regions and the effects of variations in DA transmission on these interactions. More specifically, I will show how oscillations between pyramidal cells and GABA cells in the PfCx may arise (chapter 5), and how disruption of this information pro¬ cessing capacity can occur through multiple different pathologies. The existence of oscillations is shown through simulations and theoretically by modelling neurotrans¬ mitter interactions within the mesocortical and mesolimbic dopamine (DA) systems (chapter 6). This work reveals the conditions under which oscillations will occur, and shows how DA can act as a control parameter in initiating oscillations. I have mod¬ elled a high level cognitive process, the Tower of London task, using a rule-based model to represent PfCx function (chapter 7). Finally, a reinforcement learning model is presented to illustrate putative NAcc function (chapter 8). The interaction between the two models is investigated and illustrations of the possible origins of the positive symptoms of schizophrenia are given. In all of these models, the role of DA has been crucial. One conclusion from this work is that the symptoms of schizophrenia may arise through inappropriate fluctuations in DA levels in the NAcc and the PfCx. The work is based on a large amount of neurobiological data and follows theories pre¬ sented by Friston (1998) and Goldman-Rakic and Selemon (1997) amongst others.