A neurocomputational model of learning to select actions
Caso, A. and Cooper, Richard P. (2017) A neurocomputational model of learning to select actions. In: Van Vugt, M. and Banks, A. and Kennedy, W. (eds.) Proceedings of the 15th International Conference on Cognitive Modelling. ICCM. (In Press)
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A Neurocomputational Model of Learning to Select Actions (2017).pdf - Author's Accepted Manuscript Download (4MB) | Preview |
Abstract
We present an extension of a schema-based architecture for action selection, where competition between schemas is resolved using a variation of a neuroanatomically detailed model of the basal ganglia. The extended model implements distinct learning mechanisms for cortical schemas and for units within the basal ganglia. We demonstrate the functionality of the proposed mechanisms by applying the model to two classic neuropsychological tasks, the Wisconsin Card Sorting Task (WCST) and the Probabilistic Reversal Learning Task (PRLT). We discuss how the model captures existing behavioural data in neurologically healthy subjects and PD patients and how to overcome its shortcomings.
Metadata
| Item Type: | Book Section |
|---|---|
| Keyword(s) / Subject(s): | schema theory, basal ganglia, Wisconsin Card Sorting Test, Probabilistic Reversal Task |
| School: | School of Science > Psychological Sciences |
| Research Centres and Institutes: | Cognition, Computation and Modelling, Centre for |
| Depositing User: | Rick Cooper |
| Date Deposited: | 04 Oct 2017 10:03 |
| Last Modified: | 11 Jun 2021 06:02 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/18823 |
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