海马体中的奖赏预测编码

Mohammad Hassan Yaghoubi, Andres Nieto-Pasadas, Coralie-Anne Mosser, Thomas Gisiger, Emmanuel Wilson, Sylvain Williams, Mark P Brandon
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摘要

大脑的一个基本目标就是预测未来的结果。这一过程需要学习世界的状态以及这些状态之间的过渡关系。海马认知图谱被认为就是这样一个内部模型。然而,海马神经元表征中的预测编码和奖赏敏感性的证据表明,它的作用超出了纯粹的空间表征。事实上,这提出了一个问题:什么样的空间表征对学习和最大化未来奖励最有用?在这里,我们追踪了小鼠在学习解决一项对认知要求极高的基于奖励的任务时,奖励表征在数周内的演变过程。我们的发现揭示了在学习过程中海马奖励表征的高度组织化重组。具体来说,我们在群体和单细胞水平上发现了多个证据,表明海马表征在数周内变得可以预测奖赏。也就是说,随着时间的推移,群体水平的奖赏信息和奖赏调谐神经元的百分比都会下降。与此同时,动物的选择和奖赏接近期(选择和奖赏之间的时期)的表征随着时间的推移而增加。通过在不同阶段追踪单个奖赏细胞,我们发现最初调谐奖赏的神经元会将其调谐转向选择和奖赏接近期,这表明奖赏细胞会随着经验的增加而反向传播其调谐以预测奖赏。这些发现强调了海马表征的动态性质,突出了它们通过预测未来结果在学习中的关键作用。
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Predictive Coding of Reward in the Hippocampus
A fundamental objective of the brain is to anticipate future outcomes. This process requires learning the states of the world as well as the transitional relationships between those states. The hippocampal cognitive map is believed to be one such internal model. However, evidence for predictive coding and reward sensitivity in the hippocampal neuronal representation suggests that its role extends beyond purely spatial representation. In fact, it raises the question of what kind of spatial representation is most useful for learning and maximizing future rewards? Here, we track the evolution of reward representation over weeks as mice learn to solve a cognitively demanding reward-based task. Our findings reveal a highly organized restructuring of hippocampal reward representations during the learning process. Specifically, we found multiple lines of evidence, both at the population and single-cell levels, that hippocampal representation becomes predictive of reward over weeks. Namely, both population-level information about reward and the percentage of reward-tuned neurons decrease over time. At the same time, the representation of the animals' choice and reward approach period (the period between choice and reward) increased over time. By tracking individual reward cells across sessions, we found that neurons initially tuned for reward shifted their tuning towards choice and reward approach periods, indicating that reward cells backpropagate their tuning to anticipate reward with experience. These findings underscore the dynamic nature of hippocampal representations, highlighting their critical role in learning through the prediction of future outcomes.
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