ArticleScientific reports2023
A generalized reinforcement learning based deep neural network agent model for diverse cognitive constructs.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Computational Modeling of Parkinson's Disease Across Scales: From Mechanisms to Biomarkers, Drug Discovery, and Personalized Therapies.Brain sciences · 2026Review
- A Basal Ganglia model for understanding working memory functions in healthy and Parkinson's conditions.Cognitive neurodynamics · 2024Article
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7 authors.
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Abstract
Human cognition is characterized by a wide range of capabilities including goal-oriented selective attention, distractor suppression, decision making, response inhibition, and working memory. Much research has focused on studying these individual components of cognition in isolation, whereas in several translational applications for cognitive impairment, multiple cognitive functions are altered in a given individual. Hence it is important to study multiple cognitive abilities in the same subject or, in computational terms, model them using a single model. To this end, we propose a unified, reinforcement learning-based agent model comprising of systems for representation, memory, value computation and exploration. We successfully modeled the aforementioned cognitive tasks and show how individual performance can be mapped to model meta-parameters. This model has the potential to serve as a proxy for cognitively impaired conditions, and can be used as a clinical testbench on which therapeutic interventions can be simulated first before delivering to human subjects.
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