Phasic Dopamine Release in the Rat Nucleus Accumbens Symmetrically Encodes a Reward Prediction Error Term
Phasic Dopamine Release in the Rat Nucleus Accumbens Symmetrically Encodes a Reward Prediction Error Term
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DOI：
10.1523/jneurosci.2489-13.2014
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发表时间：
2014-01-15
影响因子：
5.3
通讯作者：
Phillips, Paul E. M.
中科院分区：
文献类型：
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作者：
Hart, Andrew S.;Rutledge, Robb B.;Phillips, Paul E. M.
对与环境刺激相关的奖励做出预测，并通过反馈更新这些预测，是适应性行为的一个重要方面。理论家认为，多巴胺编码奖励预测误差（RPE）信号，用于这种强化学习过程。最近的fMRI研究表明，多巴胺能靶区的BOLD信号满足RPE假设的公理化模型的充分必要条件。然而，没有直接证据表明多巴胺释放本身也满足编码RPE信号的必要和充分的标准。此外，多巴胺神经元具有较低的张力放电率，这一事实产生了编码负rpe的有限动态范围，这导致了关于正预测错误和负预测错误是否以相似的尺度编码的重大争论。为了解决这两个问题，我们使用快速扫描循环伏安法来测量长期植入伏隔核的碳纤维电极上奖励诱发的多巴胺释放。我们证明了多巴胺浓度传递双向RPE信号，并对称编码正RPE和负RPE。我们的研究结果加强了多巴胺浓度的变化足以编码强化学习所需的全部rpe的情况。
Making predictions about the rewards associated with environmental stimuli and updating those predictions through feedback is an essential aspect of adaptive behavior. Theorists have argued that dopamine encodes a reward prediction error (RPE) signal that is used in such a reinforcement learning process. Recent work with fMRI has demonstrated that the BOLD signal in dopaminergic target areas meets both necessary and sufficient conditions of an axiomatic model of the RPE hypothesis. However, there has been no direct evidence that dopamine release itself also meets necessary and sufficient criteria for encoding an RPE signal. Further, the fact that dopamine neurons have low tonic firing rates that yield a limited dynamic range for encoding negative RPEs has led to significant debate about whether positive and negative prediction errors are encoded on a similar scale. To address both of these issues, we used fast-scan cyclic voltammetry to measure reward-evoked dopamine release at carbon fiber electrodes chronically implanted in the nucleus accumbens core of rats trained on a probabilistic decision-making task. We demonstrate that dopamine concentrations transmit a bidirectional RPE signal with symmetrical encoding of positive and negative RPEs. Our findings strengthen the case that changes in dopamine concentration alone are sufficient to encode the full range of RPEs necessary for reinforcement learning.