Humans and animals make predictions about the rewards they expect to receive in different situations. In formal models of behavior, these predictions are known as value representations, and they play two very different roles. Firstly, they drive choice: the expected values of available options are compared to one another, and the best option is selected. Secondly, they support learning: expected values are compared to rewards actually received, and future expectations are updated accordingly. Whether these different functions are mediated by different neural representations remains an open question. Here we employ a recently-developed multi-step task for rats that computationally separates learning from choosing. We investigate the role of value representations in the rodent orbitofrontal cortex, a key structure for value-based cognition. Electrophysiological recordings and optogenetic perturbations indicate that these representations do not directly drive choice. Instead, they signal expected reward information to a learning process elsewhere in the brain that updates choice mechanisms.

中文翻译：

---

啮齿动物眶额皮质驱动学习中的价值表示，而不是选择

人类和动物对他们期望在不同情况下获得的奖励做出预测。在正式的行为模型中，这些预测被称为价值表示，它们扮演着两个截然不同的角色。首先，它们驱动选择：将可用选项的期望值相互比较，然后选择最佳选项。其次，他们支持学习：期望值与实际获得的奖励进行比较，并相应地更新未来的期望。这些不同的功能是否由不同的神经表征介导仍然是一个悬而未决的问题。在这里，我们采用了最近开发的大鼠多步骤任务，该任务在计算上将学习与选择分开。我们研究价值表征在啮齿动物眶额皮质中的作用，这是基于价值的认知的关键结构。电生理记录和光遗传学扰动表明这些表征并不直接驱动选择。相反，它们向大脑其他地方的学习过程发出预期的奖励信息，从而更新选择机制。