Simulating the Effect of Dopamine Imbalance on Cognition: From Positive Affect to Parkinson's Disease
Cools (2006) suggested that prefrontal dopamine levels are related to cognitive stability whereas striatal dopamine levels are related to cognitive plasticity. With such a wide ranging role, almost all cognitive activities should be affected by dopamine levels in the brain. Not surprisingly, factors influencing brain dopamine levels have been shown to improve/worsen performance in many behavioral experiments. On the one hand, Nadler and his colleagues (2010) showed that positive affect (which is thought to increase cortical dopamine levels) improves a type of categorization that depends on explicit reasoning (rule-based) but not a type that depends on procedural learning (informationintegration). On the other hand, Parkinson’s disease (which is known to decrease dopamine levels in both the striatum and cortex) produces proactive interference in the odd-man-out task (Flowers & Robertson, 1985) and renders subjects insensitive to negative feedback during reversal learning (Cools et al., 2006). This article uses the COVIS model of categorization to simulate the effects of different dopamine levels in categorization, reversal learning, and the odd-man-out task. The results show a good match between the simulated and human data, which suggests that the role of dopamine in COVIS can account for several cognitive enhancements and deficits related to dopamine levels in healthy and patient populations.
Dopamine, COVIS, Parkinson’s disease, positive affect, computational modeling.
Date of this Version
Helie, Sebastien; Paul, Erick J.; and Ashby, F Gregory, "Simulating the Effect of Dopamine Imbalance on Cognition: From Positive Affect to Parkinson's Disease" (2012). Department of Psychological Sciences Faculty Publications. Paper 45.
“NOTICE: this is the author’s version of a work that was accepted for publication in Neural Networks. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Neural Networks, [32, (2012)] DOI#10.1016/j.neunet.2012.02.033