小柯机器人

美国华盛顿大学医学院Ilya E. Monosov研究组揭示了结合信息和奖励的保守价值计算的神经机制。相关论文于2024年1月4日发表在《自然—神经科学》杂志上。

他们展示了人类和猴子在权衡信息和外部奖励的多属性决策过程中，价值判断遵循惊人的保守计算原则。然后，他们在一个高度保守的古老结构，侧缰(LHb)中确定了一个神经基底。LHb神经元发出主观价值信号，将信息价值与外在奖励相结合，LHb预测并因果影响正在进行的决策。

LHb关键输入区域的神经元主要发送这些计算的组成部分，而不是集成的值信号。因此，他们的数据揭示了保守计算的神经机制，这些机制是寻求有关未来信息的决策的基础。

据悉，行为和经济理论告诉他们，他们是根据价值来做出选择的。然而，人类和动物急切地寻求有关不确定的未来奖励的信息，即使这些信息没有提供任何客观价值。这意味着决策是通过赋予信息主观价值并将其与外在奖励价值相结合而做出的，但其机制尚不清楚。

附：英文原文

Title: A neural mechanism for conserved value computations integrating information and rewards

Author: Bromberg-Martin, Ethan S., Feng, Yang-Yang, Ogasawara, Takaya, White, J. Kael, Zhang, Kaining, Monosov, Ilya E.

Issue&Volume: 2024-01-04

Abstract: Behavioral and economic theory dictate that we decide between options based on their values. However, humans and animals eagerly seek information about uncertain future rewards, even when this does not provide any objective value. This implies that decisions are made by endowing information with subjective value and integrating it with the value of extrinsic rewards, but the mechanism is unknown. Here, we show that human and monkey value judgements obey strikingly conserved computational principles during multi-attribute decisions trading off information and extrinsic reward. We then identify a neural substrate in a highly conserved ancient structure, the lateral habenula (LHb). LHb neurons signal subjective value, integrating information’s value with extrinsic rewards, and the LHb predicts and causally influences ongoing decisions. Neurons in key input areas to the LHb largely signal components of these computations, not integrated value signals. Thus, our data uncover neural mechanisms of conserved computations underlying decisions to seek information about the future.

DOI: 10.1038/s41593-023-01511-4

Source: https://www.nature.com/articles/s41593-023-01511-4

Nature Neuroscience：《自然—神经科学》，创刊于1998年。隶属于施普林格·自然出版集团，最新IF：28.771
官方网址：https://www.nature.com/neuro/
投稿链接：https://mts-nn.nature.com/cgi-bin/main.plex