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

Par Conseil national de recherches du Canada

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Lienhttps://escholarship.org/uc/item/4xg8936b
AuteurRechercher : ; Rechercher : 1
Affiliation
  1. Conseil national de recherches du Canada. Technologies numériques
FormatTexte, Article
Conférence43rd Annual Meeting of the Cognitive Science Society (CogSci 2021), July 26-29, 2023, Vienna, Austria [Hybrid Conference]
SujetWisconsin Card Sorting Test; spiking neural network; neural engineering framework; semantic pointers
Résumé
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.
Date de publication
Maison d’éditionCognitive Science Society
eScholarship
Dans
  • Proceedings of the Annual Meeting of the Cognitive Science Society 43 (29 juillet 2021) : 2295–2301.
Langueanglais
Publications évaluées par des pairsOui
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Identificateur de l’enregistrement53eb3b7c-9ad6-49d9-882b-14de9b4cca29
Enregistrement créé2023-06-02
Enregistrement modifié2023-06-05
Date de modification :