Cargando…
Coarse-Grained Neural Network Model of the Basal Ganglia to Simulate Reinforcement Learning Tasks
Computational models of the basal ganglia (BG) provide a mechanistic account of different phenomena observed during reinforcement learning tasks performed by healthy individuals, as well as by patients with various nervous or mental disorders. The aim of the present work was to develop a BG model th...
Autores principales: | Drapała, Jarosław, Frydecka, Dorota |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8870197/ https://www.ncbi.nlm.nih.gov/pubmed/35204025 http://dx.doi.org/10.3390/brainsci12020262 |
Ejemplares similares
-
Trauma Disrupts Reinforcement Learning in Rats—A Novel Animal Model of Chronic Stress Exposure
por: Bielawski, Tomasz, et al.
Publicado: (2022) -
Time representation in reinforcement learning models of the basal ganglia
por: Gershman, Samuel J., et al.
Publicado: (2014) -
Coarse-graining of the dynamics seen in neural networks
por: Ben-Tal, Alona, et al.
Publicado: (2013) -
Transferable Coarse Graining via Contrastive Learning of Graph Neural Networks
por: Airas, Justin, et al.
Publicado: (2023) -
Confirmation Bias in the Course of Instructed Reinforcement Learning in Schizophrenia-Spectrum Disorders
por: Frydecka, Dorota, et al.
Publicado: (2022)