Prefrontal Cortex Predicts State Switches during Reversal Learning
Prefrontal Cortex Predicts State Switches during Reversal Learning
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DOI：
10.1016/j.neuron.2020.03.024
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发表时间：
2020-06-17
期刊：
影响因子：
16.2
通讯作者：
Averbeck, Bruno B.
中科院分区：
文献类型：
--
作者：
Bartolo, Ramon;Averbeck, Bruno B.
强化学习使生物体能够预测未来的结果，并更新他们对世界价值的信念。背外侧前额叶皮层（dlPFC）整合了奖励回路携带的信息，这些信息可以用来推断不确定情况下世界的当前状态。在这里，我们探讨了在随机反转学习过程中与更新当前信念相关的dlPFC计算。我们同时记录了两只雄性猕猴在执行双臂逆贼学习任务时多达1000个神经元的活动。使用贝叶斯框架的行为分析表明，动物推断反转并迅速改变选择偏好，而不是缓慢地更新选择值，与状态推断一致。此外，dlPFC神经群准确地编码了选择偏好开关。这些结果表明，前额叶神经元动态地编码与贝叶斯主观价值相关的决策，突出了PFC在代表对当前世界状态的信念方面的作用。
Reinforcement learning allows organisms to predict future outcomes and to update their beliefs about value in the world. The dorsal-lateral prefrontal cortex (dlPFC) integrates information carried by reward circuits, which can be used to infer the current state of the world under uncertainty. Here, we explored the dlPFC computations related to updating current beliefs during stochastic reversal learning. We recorded the activity of populations up to 1,000 neurons, simultaneously, in two male macaques while they executed a two-armed bandit reversal learning task. Behavioral analyses using a Bayesian framework showed that animals inferred reversals and switched their choice preference rapidly, rather than slowly updating choice values, consistent with state inference. Furthermore, dlPFC neural populations accurately encoded choice preference switches. These results suggest that prefrontal neurons dynamically encode decisions associated with Bayesian subjective values, highlighting the role of the PFC in representing a belief about the current state of the world.