Distributional coding of associative learning within projection-defined populations of midbrain dopamine neurons

Distributional coding of associative learning within projection-defined populations of midbrain dopamine neurons
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投影定义的中脑多巴胺神经元群体中联想学习的分布编码

DOI:
10.1101/2022.07.18.500429
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发表时间:
2022
期刊:
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影响因子:
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通讯作者:
Avvisati R
Avvisati R
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作者:
Avvisati R

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中脑多巴胺神经元被认为在传递预期结果和实际结果之间的差异的学习中起着关键作用。虽然这种教学信号通常被认为是统一的,但最近的证据却支持多巴胺信号的多样性。然而,人们对异质信号如何被组织起来以促进下游回路介导不同行为方面的作用仍然知之甚少。本研究通过记录和标记个体中脑多巴胺神经元在联想行为中的组织逻辑来研究多巴胺能信号的组织逻辑。我们定义了蛋白质表达和细胞定位的组合,根据纹状体区域对记录的神经元进行分类。我们的研究结果表明,奖励信息和任务变量不仅具有异构编码和多路复用性,而且在纹状体不同区域的多巴胺神经元群中分布也存在差异。这些数据在计算模型的支持下,表明这种分布编码可以最大化动态范围和定制多巴胺信号,以促进不同纹状体区域的特化作用。
Midbrain dopamine neurons are thought to play key roles in learning by conveying the difference between expected and actual outcomes. While this teaching signal is often considered to be uniform, recent evidence instead supports diversity in dopamine signaling. However, it remains poorly understood how heterogeneous signals might be organized to facilitate the role of downstream circuits mediating distinct aspects of behavior. Here we investigated the organizational logic of dopaminergic signaling by recording and labeling individual midbrain dopamine neurons during associative behavior. We defined combinations of protein expression and cellular localization to sort recorded neurons according to the striatal regions they innervate. Our findings show that reward information and task variables are not only heterogeneously encoded, with multiplexing, but also differentially distributed across populations of dopamine neurons projecting to different regions of striatum. These data, supported by computational modelling, indicate that such distributional coding can maximize dynamic range and tailor dopamine signals to facilitate the specialized roles of different striatal regions.
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