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Optogenetic Blockade of Dopamine Transients Prevents Learning Induced by Changes in Reward Features.

ABSTRACT: Prediction errors are critical for associative learning [1, 2]. Transient changes in dopamine neuron activity correlate with positive and negative reward prediction errors and can mimic their effects [3-15]. However, although causal studies show that dopamine transients of 1-2 s are sufficient to drive learning about reward, these studies do not address whether they are necessary (but see [11]). Further, the precise nature of this signal is not yet fully established. Although it has been equated with the cached-value error signal proposed to support model-free reinforcement learning, cached-value errors are typically confounded with errors in the prediction of reward features [16]. Here, we used optogenetic and transgenic approaches to prevent transient changes in midbrain dopamine neuron activity during the critical error-signaling period of two unblocking tasks. In one, learning was unblocked by increasing the number of rewards, a manipulation that induces errors in predicting both value and reward features. In another, learning was unblocked by switching from one to another equally valued reward, a manipulation that induces errors only in reward feature prediction. Preventing dopamine neurons in the ventral tegmental area from firing for 5 s beginning before and continuing until after the changes in reward prevented unblocking of learning in both tasks. A similar duration suppression did not induce extinction when delivered during an expected reward, indicating that it did not act independently as a negative prediction error. This result suggests that dopamine transients play a general role in error signaling rather than being restricted to only signaling errors in value.

SUBMITTER: Chang CY

PROVIDER: S-EPMC5698141 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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Optogenetic Blockade of Dopamine Transients Prevents Learning Induced by Changes in Reward Features.

Chang Chun Yun CY Gardner Matthew M Di Tillio Maria Gonzalez MG Schoenbaum Geoffrey G

Current biology : CB 20171102 22

Prediction errors are critical for associative learning [1, 2]. Transient changes in dopamine neuron activity correlate with positive and negative reward prediction errors and can mimic their effects [3-15]. However, although causal studies show that dopamine transients of 1-2 s are sufficient to drive learning about reward, these studies do not address whether they are necessary (but see [11]). Further, the precise nature of this signal is not yet fully established. Although it has been equated ...[more]

PMID: 29103933

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Project description:In the DSM-5, psychiatric diagnoses are made based on self-reported symptoms and clinician-identified signs. Though helpful in choosing potential interventions based on the available regimens, this conceptualization of psychiatric diseases can limit basic science investigation into their underlying causes. The reward prediction error (RPE) hypothesis of dopamine neuron function posits that phasic dopamine signals encode the difference between the rewards a person expects and experiences. The computational framework from which this hypothesis was derived, temporal difference reinforcement learning (TDRL), is largely focused on reward processing rather than punishment learning. Many psychiatric disorders are characterized by aberrant behaviors, expectations, reward processing, and hypothesized dopaminergic signaling, but also characterized by suffering and the inability to change one's behavior despite negative consequences. In this review, we provide an overview of the RPE theory of phasic dopamine neuron activity and review the gains that have been made through the use of computational reinforcement learning theory as a framework for understanding changes in reward processing. The relative dearth of explicit accounts of punishment learning in computational reinforcement learning theory and its application in neuroscience is highlighted as a significant gap in current computational psychiatric research. Four disorders comprise the main focus of this review: two disorders of traditionally hypothesized hyperdopaminergic function, addiction and schizophrenia, followed by two disorders of traditionally hypothesized hypodopaminergic function, depression and post-traumatic stress disorder (PTSD). Insights gained from a reward processing based reinforcement learning framework about underlying dopaminergic mechanisms and the role of punishment learning (when available) are explored in each disorder. Concluding remarks focus on the future directions required to characterize neuropsychiatric disorders with a hypothesized cause of underlying dopaminergic transmission.

Dataset Information

Optogenetic Blockade of Dopamine Transients Prevents Learning Induced by Changes in Reward Features.

Publications

Optogenetic Blockade of Dopamine Transients Prevents Learning Induced by Changes in Reward Features.

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