A neurocomputational account of cognitive deficits in Parkinson's disease

NEUROPSYCHOLOGIA

卷:50

Article

Helie, Sebastien²  Ashby, F. Gregory¹ 

[1] Univ Calif Santa Barbara, Dept Psychol & Brain Sci, Santa Barbara, CA 93106 USA

[2] Purdue Univ, W Lafayette, IN 47907 USA

关键词: Parkinson's disease;    Computational modeling;    COVIS;    Perceptual categorization;    Probabilistic classification;    Wisconsin Card Sorting Test (WCST);   

DOI  :  10.1016/j.neuropsychologia.2012.05.033

来源: Elsevier

【 摘 要 】

Parkinson's disease (PD) is caused by the accelerated death of dopamine (DA) producing neurons. Numerous studies documenting cognitive deficits of PD patients have revealed impairments in a variety of tasks related to memory, learning, visuospatial skills, and attention. While there have been several studies documenting cognitive deficits of PD patients, very few computational models have been proposed. In this article, we use the COVIS model of category learning to simulate DA depletion and show that the model suffers from cognitive symptoms similar to those of human participants affected by PD. Specifically, DA depletion in COVIS produced deficits in rule-based categorization, non-linear information-integration categorization, probabilistic classification, rule maintenance, and rule switching. These were observed by simulating results from younger controls, older controls, PD patients, and severe PD patients in five well-known tasks. Differential performance among the different age groups and clinical populations was modeled simply by changing the amount of DA available in the model. This suggests that COVIS may not only be an adequate model of the simulated tasks and phenomena but also more generally of the role of DA in these tasks and phenomena. (C) 2012 Elsevier Ltd. All rights reserved.

【 授权许可】

Free