ArticleFrontiers in computational neuroscience2014
An extended reinforcement learning model of basal ganglia to understand the contributions of serotonin and dopamine in risk-based decision making, reward prediction, and punishment learning.
Article in Frontiers in computational neuroscience, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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19 citing papers in PubMed, 44 citations in OpenAlex.
- Impaired arbitration between reward-related decision-making strategies in Alcohol Users compared to Alcohol Non-Users: a computational modeling study.NPP - digital psychiatry and neuroscience · 2025Article
- A Basal Ganglia model for understanding working memory functions in healthy and Parkinson's conditions.Cognitive neurodynamics · 2024Article
- Distinct neural activations correlate with maximization of reward magnitude versus frequency.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- A generalized reinforcement learning based deep neural network agent model for diverse cognitive constructs.Scientific reports · 2023Article
- Coarse-Grained Neural Network Model of the Basal Ganglia to Simulate Reinforcement Learning Tasks.Brain sciences · 2022Article
- Linking Salience Signaling With Early Adversity and Affective Distress in Individuals at Clinical High Risk for Psychosis: Results From an Event-Related fMRI Study.Schizophrenia bulletin open · 2022Article
- A global framework for a systemic view of brain modeling.Brain informatics · 2021Article
- Bipolar oscillations between positive and negative mood states in a computational model of Basal Ganglia.Cognitive neurodynamics · 2020Article
- The Role of Tryptophan and Tyrosine in Executive Function and Reward Processing.International journal of tryptophan research : IJTR · 2020Review
- The Protective Action Encoding of Serotonin Transients in the Human Brain.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2018Article
- Toward a multiscale modeling framework for understanding serotonergic function.Journal of psychopharmacology (Oxford, England) · 2017Review
- Learning Reward Uncertainty in the Basal Ganglia.PLoS computational biology · 2016Article
- Nicotinic receptors in the ventral tegmental area promote uncertainty-seeking.Nature neuroscience · 2016Article
- A Neurocomputational Model of the Effect of Cognitive Load on Freezing of Gait in Parkinson's Disease.Frontiers in human neuroscience · 2016Article
- Association between the dopamine D4 receptor gene exon III variable number of tandem repeats and political attitudes in female Han Chinese.Proceedings. Biological sciences · 2015Article
- A network model of basal ganglia for understanding the roles of dopamine and serotonin in reward-punishment-risk based decision making.Frontiers in computational neuroscience · 2015Article
- Identifying the Basal Ganglia network model markers for medication-induced impulsivity in Parkinson's disease patients.PloS one · 2015Article
- Could dopamine agonists aid in drug development for anorexia nervosa?Frontiers in nutrition · 2014Review
- Basal ganglia: physiological, behavioral, and computational studies.Frontiers in systems neuroscience · 2014Article
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Although empirical and neural studies show that serotonin (5HT) plays many functional roles in the brain, prior computational models mostly focus on its role in behavioral inhibition. In this study, we present a model of risk based decision making in a modified Reinforcement Learning (RL)-framework. The model depicts the roles of dopamine (DA) and serotonin (5HT) in Basal Ganglia (BG). In this model, the DA signal is represented by the temporal difference error (δ), while the 5HT signal is represented by a parameter (α) that controls risk prediction error. This formulation that accommodates both 5HT and DA reconciles some of the diverse roles of 5HT particularly in connection with the BG system. We apply the model to different experimental paradigms used to study the role of 5HT: (1) Risk-sensitive decision making, where 5HT controls risk assessment, (2) Temporal reward prediction, where 5HT controls time-scale of reward prediction, and (3) Reward/Punishment sensitivity, in which the punishment prediction error depends on 5HT levels. Thus the proposed integrated RL model reconciles several existing theories of 5HT and DA in the BG.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.