Connectionist models are used to explore the relationship between cognitive deficits and biological abnormalities in schizophrenia. Schizophrenic deficits in tasks that tap attention and language processing are reviewed, as are biological disturbances involving prefrontal cortex and the mesocortical dopamine system. Three computer models are then presented that simulate normal and schizophrenic performance in the Stroop task, the continuous performance test, and a lexical disambiguation task. They demonstrate that a disturbance in the internal representation of contextual information can provide a common explanation for schizophrenic deficits in several attention- and language-related tasks. The models also show that these behavioral deficits may arise from a disturbance in a model parameter (gain) corresponding to the neuromodulatory effects of dopamine, in a model component corresponding to the function of prefrontal cortex.

Noradrenergic locus coeruleus (LC) neurons were recorded in monkeys performing a visual discrimination task, and a computational model was developed addressing the role of the LC brain system in cognitive performance. Changes in spontaneous and stimulus-induced patterns of LC activity correlated closely with fluctuations in behavioral performance. The model explains these fluctuations in terms of changes in electrotonic coupling among LC neurons and predicts improved performance during epochs of high coupling and synchronized LC firing. Cross correlations of simultaneously recorded LC neurons confirmed this prediction, indicating that electrotonic coupling in LC may play an important role in attentional modulation and the regulation of goal-directed versus exploratory behaviors.