A neurocomputational account of reward and novelty processing and effects of psychostimulants in attention deficit hyperactivity disorder

Computational models of reinforcement learning have helped dissect discrete components of reward-related function and characterize neurocognitive deficits in psychiatric illnesses. Stimulus novelty biases decision-making, even when unrelated to choice outcome, acting as if possessing intrinsic rewar...

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Detalles Bibliográficos
Autores principales: Sethi, Arjun, Voon, Valerie, Critchley, Hugo D, Cercignani, Mara, Harrison, Neil A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Original Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5917772/
https://www.ncbi.nlm.nih.gov/pubmed/29547978
http://dx.doi.org/10.1093/brain/awy048

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5917772/
https://www.ncbi.nlm.nih.gov/pubmed/29547978
http://dx.doi.org/10.1093/brain/awy048

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