A computational model of information processing in the frontal cortex and basal ganglia

Performance on the Wisconsin Card Sori Test (WCST) of patients with schizop hrenia, Parkinson's disease (PD), and Huntington's disease (HD) was simulat ed by a neural network model constructed on principles derived from neuroan atomic loops from the frontal cortex through the basal ganglia and thalamus . The model provided a computational rationale for the empirical pattern of perseverative errors associated with frontal cortex dysfunction and random errors associated with striatal dysfunction. The model displayed persevera tive errors in performance when the gain parameter of the activation functi on in units representing frontal cortex neurons Nas reduced as an analog of reduced dopamine release. Random errors occurred when the gain parameter o f the activation function in units representing striatal neurons was reduce d, or when the activation level was itself reduced as an analog of a striat al lesion. The model demonstrated that the perseveration of schizophrenic, Huntington's, and demented Parkinsonian patients may be principally due to ineffective inhibition of previously learned contextual rules in the fronta l cortex, while the random errors of Parkinson's and Huntington's patients are more likely to be due to unsystematic errors of matching in the striatu m. The model also made specific, empirically falsifiable predictions that c an be used to explore the utility of these putative mechanisms of informati on processing in the frontal cortex and basal ganglia.