ArticleThe Journal of neuroscience : the official journal of the Society for Neuroscience2018
On the Role of Cortex-Basal Ganglia Interactions for Category Learning: A Neurocomputational Approach.
Article in The Journal of neuroscience : the official journal of the Society for Neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Pallidal Deep Brain Stimulation Enhances Habitual Behavior in a Neuro-Computational Basal Ganglia Model During a Reward Reversal Learning Task.The European journal of neuroscience · 2025Article
- The gradual coevolution of syntactic combinatorics and categorization under the effects of human self-domestication: a proposal.Cognitive processing · 2023Article
- Hierarchical categorization learning is associated with representational changes in the dorsal striatum and posterior frontal and parietal cortex.Human brain mapping · 2023Article
- The contribution of the basal ganglia and cerebellum to motor learning: A neuro-computational approach.PLoS computational biology · 2023Article
- Article
- Multilevel development of cognitive abilities in an artificial neural network.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Cumulative Genetic Score of DRD2 Polymorphisms Is Associated with Impulsivity and Masked Semantic Priming.Journal of molecular neuroscience : MN · 2022Article
- A brain-inspired intention prediction model and its applications to humanoid robot.Frontiers in neuroscience · 2022Article
- Mouse visual cortex areas represent perceptual and semantic features of learned visual categories.Nature neuroscience · 2021Article
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- Morphological, Structural, and Functional Networks Highlight the Role of the Cortical-Subcortical Circuit in Individuals With Subjective Cognitive Decline.Frontiers in aging neuroscience · 2021Article
- Holistic Reinforcement Learning: The Role of Structure and Attention.Trends in cognitive sciences · 2019Review
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Authors and funding
7 authors.
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Abstract
In addition to the prefrontal cortex (PFC), the basal ganglia (BG) have been increasingly often reported to play a fundamental role in category learning, but the circuit mechanisms mediating their interaction remain to be explored. We developed a novel neurocomputational model of category learning that particularly addresses the BG-PFC interplay. We propose that the BG bias PFC activity by removing the inhibition of cortico-thalamo-cortical loop and thereby provide a teaching signal to guide the acquisition of category representations in the corticocortical associations to the PFC. Our model replicates key behavioral and physiological data of macaque monkey learning a prototype distortion task from Antzoulatos and Miller (2011) Our simulations allowed us to gain a deeper insight into the observed drop of category selectivity in striatal neurons seen in the experimental data and in the model. The simulation results and a new analysis of the experimental data based on the model's predictions show that the drop in category selectivity of the striatum emerges as the variability of responses in the striatum rises when confronting the BG with an increasingly larger number of stimuli to be classified. The neurocomputational model therefore provides new testable insights of systems-level brain circuits involved in category learning that may also be generalized to better understand other cortico-BG-cortical loops.
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