Simulating the effects of dopamine imbalance on cognition: From positive affect to Parkinson's disease

TitleSimulating the effects of dopamine imbalance on cognition: From positive affect to Parkinson's disease
Publication TypeJournal Article
Year of Publication2012
AuthorsHelie, S., Paul E. J., & F Ashby G.
JournalNeural Networks
Volume32
Pagination74-85
Date Published2012 Aug
ISSN1879-2782
KeywordsAdult, Affect, Aged, Aging, Algorithms, Artificial Intelligence, Cognition, Computer Simulation, Dopamine, Feedback, Physiological, Humans, Learning, Neural Pathways, Parkinson Disease, Reward, Somatosensory Cortex, Young Adult
Abstract

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, Rabi, and Minda (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 another type that depends on procedural learning (information-integration). 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, Altamirano, & D'Esposito, 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.

DOI10.1016/j.neunet.2012.02.033
Alternate JournalNeural Netw
PubMed ID22402326
PubMed Central IDPMC3368085
Grant ListP01 NS044393 / NS / NINDS NIH HHS / United States
P01 NS044393-09 / NS / NINDS NIH HHS / United States
P01NS044393 / NS / NINDS NIH HHS / United States