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• W1982670892 abstract "The striatal dopaminergic system has been implicated in reinforcement learning (RL), motor performance, and incentive motivation. Various computational models have been proposed to account for each of these effects individually, but a formal analysis of their interactions is lacking. Here we present a novel algorithmic model expanding the classical actor-critic architecture to include fundamental interactive properties of neural circuit models, incorporating both incentive and learning effects into a single theoretical framework. The standard actor is replaced by a dual opponent actor system representing distinct striatal populations, which come to differentially specialize in discriminating positive and negative action values. Dopamine modulates the degree to which each actor component contributes to both learning and choice discriminations. In contrast to standard frameworks, this model simultaneously captures documented effects of dopamine on both learning and choice incentive-and their interactions-across a variety of studies, including probabilistic RL, effort-based choice, and motor skill learning." @default.
• W1982670892 created "2016-06-24" @default.
• W1982670892 creator A5007609257 @default.
• W1982670892 creator A5067451415 @default.
• W1982670892 date "2014-01-01" @default.
• W1982670892 modified "2023-10-12" @default.
• W1982670892 title "Opponent actor learning (OpAL): Modeling interactive effects of striatal dopamine on reinforcement learning and choice incentive." @default.
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• W1982670892 doi "https://doi.org/10.1037/a0037015" @default.
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