当前位置:科学网首页 > 小柯机器人 >详情
研究报道5-羟色胺系统中价值的预期代码
作者:小柯机器人 发布时间:2025/3/27 19:37:20

加拿大渥太华大学Richard Naud小组报道了5-羟色胺系统中价值的预期代码。这一研究成果于2025年3月26日发表在国际顶尖学术期刊《自然》上。

将强化学习理论的思想与最近对背中缝核过滤特性的见解结合起来,该团队在未来的价值代码中找到了统一的观点。这种近期奖励的生物学密码解释了为什么5 -羟色胺神经元在受到奖励和惩罚时都能被激活,以及为什么这些神经元在受到令人惊讶的奖励时被更强烈地激活,而对惩罚却没有这种令人惊讶的偏好。最后,他们的模型比以前的理论更好地定量预测体内种群活动。通过调和先前的理论并建立与强化学习的精确联系,他们的工作代表了理解血清素在学习和行为中的作用的重要一步。

据悉,中缝背核5 -羟色胺神经元对情绪显著性刺激的体内反应是一个谜。现有的以奖励、惊奇、显著性和不确定性为中心的理论分别解释了血清素能活动的某些方面,但不能解释其他方面。

附:英文原文

Title: A prospective code for value in the serotonin system

Author: Harkin, Emerson F., Grossman, Cooper D., Cohen, Jeremiah Y., Bque, Jean-Claude, Naud, Richard

Issue&Volume: 2025-03-26

Abstract: The in vivo responses of dorsal raphe nucleus serotonin neurons to emotionally salient stimuli are a puzzle1. Existing theories centring on reward, surprise, salience and uncertainty individually account for some aspects of serotonergic activity but not others. Merging ideas from reinforcement learning theory with recent insights into the filtering properties of the dorsal raphe nucleus, here we find a unifying perspective in a prospective code for value. This biological code for near-future reward explains why serotonin neurons are activated by both rewards and punishments, and why these neurons are more strongly activated by surprising rewards but have no such surprise preference for punishments—observations that previous theories have failed to reconcile. Finally, our model quantitatively predicts in vivo population activity better than previous theories. By reconciling previous theories and establishing a precise connection with reinforcement learning, our work represents an important step towards understanding the role of serotonin in learning and behaviour.

DOI: 10.1038/s41586-025-08731-7

Source: https://www.nature.com/articles/s41586-025-08731-7

期刊信息

Nature:《自然》,创刊于1869年。隶属于施普林格·自然出版集团,最新IF:69.504
官方网址:http://www.nature.com/
投稿链接:http://www.nature.com/authors/submit_manuscript.html