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Biologically constrained large-scale model of the Wisconsin Card Sorting Test

From National Research Council Canada

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Linkhttps://escholarship.org/uc/item/4xg8936b
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Affiliation
  1. National Research Council Canada. Digital Technologies
FormatText, Article
Conference43rd Annual Meeting of the Cognitive Science Society (CogSci 2021), July 26-29, 2023, Vienna, Austria [Hybrid Conference]
SubjectWisconsin Card Sorting Test; spiking neural network; neural engineering framework; semantic pointers
Abstract
We propose a biologically constrained, large-scale neural network model that solves the Wisconsin Card Sorting Test (WCST). The WCST has been widely used in clinical and research settings to study cognitive flexibility and executive function. The model shows a good quantitative match with human responses across a number of WCST scoring indices, while consisting of neural networks that functionally and anatomically map to brain areas and structures implicated in the task, such as the prefrontal cortex and the cortico-basal ganglia-thalamus-cortical loop. We argue that the model provides a mechanistic account of WCST solving, and demonstrate its robustness by examining its performance across a range of biologically motivated parameter values.
Publication date
PublisherCognitive Science Society
eScholarship
In
  • Proceedings of the Annual Meeting of the Cognitive Science Society 43 (29 July 2021): 2295–2301.
LanguageEnglish
Peer reviewedYes
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Record identifier53eb3b7c-9ad6-49d9-882b-14de9b4cca29
Record created2023-06-02
Record modified2023-06-05
Date modified: