Literature DB >> 29656872

The Medial Prefrontal Cortex Shapes Dopamine Reward Prediction Errors under State Uncertainty.

Clara Kwon Starkweather1, Samuel J Gershman2, Naoshige Uchida3.   

Abstract

Animals make predictions based on currently available information. In natural settings, sensory cues may not reveal complete information, requiring the animal to infer the "hidden state" of the environment. The brain structures important in hidden state inference remain unknown. A previous study showed that midbrain dopamine neurons exhibit distinct response patterns depending on whether reward is delivered in 100% (task 1) or 90% of trials (task 2) in a classical conditioning task. Here we found that inactivation of the medial prefrontal cortex (mPFC) affected dopaminergic signaling in task 2, in which the hidden state must be inferred ("will reward come or not?"), but not in task 1, where the state was known with certainty. Computational modeling suggests that the effects of inactivation are best explained by a circuit in which the mPFC conveys inference over hidden states to the dopamine system. VIDEO ABSTRACT.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  KOR; dopamine; hidden state inference; medial prefrontal cortex; reinforcement learning; reward prediction errors; temporal difference learning

Mesh:

Substances:

Year:  2018        PMID: 29656872      PMCID: PMC5934341          DOI: 10.1016/j.neuron.2018.03.036

Source DB:  PubMed          Journal:  Neuron        ISSN: 0896-6273            Impact factor:   17.173


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