Dopamine and the mechanisms of cognition: Part I. A neural network model predicting dopamine effects on selective attention

Abstract

Background: Dopamine affects neural information processing, cognition, and behavior; however, the mechanisms through which these three levels of function are affected have remained unspecified. We present a parallel-distributed processing model of dopamine effects on neural ensembles that accounts for effects on human performance in a selective attention task.

Methods: Task performance is stimulated using principles and mechanisms that capture salient aspects of information processing in neural ensembles. Dopamine effects are simulated as a change in gain of neural assemblies in the area of release.

Results: The model leads to different predictions as a function of the hypothesized location of dopamine effects. Motor system effects are simulated as a change in gain over the response layer of the model. This induces speeding of reaction times but an impairment of accuracy. Cognitive attentional effects are simulated as a change in gain over the attention layer. This induces a speeding of reaction times and an improvement of accuracy, especially at very fast reaction times and when processing of the stimulus requires selective attention.

Conclusions: A computer simulation using widely accepted principles of processing in neural ensembles can account for reaction time distributions and time-accuracy curves in a selective attention task. The simulation can be used to generate predictions about the effects of dopamine agonists on performance. An empirical study evaluating these predictions is described in a companion paper.