Suppr超能文献

相位多巴胺增强了嗅结节中不同的纹状体刺激编码,从而驱动多巴胺能奖赏预测。

Phasic dopamine reinforces distinct striatal stimulus encoding in the olfactory tubercle driving dopaminergic reward prediction.

机构信息

Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, 68159, Mannheim, Germany.

Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London, W1T 4JG, UK.

出版信息

Nat Commun. 2020 Jul 10;11(1):3460. doi: 10.1038/s41467-020-17257-7.

Abstract

The learning of stimulus-outcome associations allows for predictions about the environment. Ventral striatum and dopaminergic midbrain neurons form a larger network for generating reward prediction signals from sensory cues. Yet, the network plasticity mechanisms to generate predictive signals in these distributed circuits have not been entirely clarified. Also, direct evidence of the underlying interregional assembly formation and information transfer is still missing. Here we show that phasic dopamine is sufficient to reinforce the distinctness of stimulus representations in the ventral striatum even in the absence of reward. Upon such reinforcement, striatal stimulus encoding gives rise to interregional assemblies that drive dopaminergic neurons during stimulus-outcome learning. These assemblies dynamically encode the predicted reward value of conditioned stimuli. Together, our data reveal that ventral striatal and midbrain reward networks form a reinforcing loop to generate reward prediction coding.

摘要

刺激-结果关联的学习使得人们能够对环境做出预测。腹侧纹状体和多巴胺能中脑神经元形成了一个更大的网络,用于从感觉线索中产生奖励预测信号。然而,这些分布式电路中产生预测信号的网络可塑性机制尚未完全阐明。此外,关于潜在的区域间集合形成和信息传递的直接证据仍然缺失。在这里,我们表明,即使在没有奖励的情况下,脉冲式多巴胺也足以增强腹侧纹状体中刺激表示的独特性。在这种强化作用下,纹状体的刺激编码会产生区域间集合,在刺激-结果学习过程中驱动多巴胺能神经元。这些集合动态地对条件刺激的预测奖励值进行编码。总之,我们的数据表明,腹侧纹状体和中脑奖励网络形成了一个强化回路,以产生奖励预测编码。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6be2/7351739/a3dc7142b9c5/41467_2020_17257_Fig1_HTML.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验