Distributional coding of associative learning in discrete populations of midbrain dopamine neurons
Distributional coding of associative learning in discrete populations of midbrain dopamine neurons
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DOI：
10.1016/j.celrep.2024.114080
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发表时间：
2024-04-04
期刊：
影响因子：
8.8
通讯作者：
Dodson，Paul D.
中科院分区：
文献类型：
--
作者：
Avvisati，Riccardo;Kaufmann，Anna -Kristin;Dodson，Paul D.
中脑多巴胺神经元被认为通过传递预期结果和实际结果之间的差异在学习中发挥关键作用。最近的证据表明，多巴胺信号的多样性，但如何组织不同的信号，以促进下游电路的作用，调节不同方面的行为，仍然知之甚少。在这里，我们通过记录和标记联想行为中的单个中脑多巴胺神经元来研究多巴胺能信号的组织逻辑。我们的发现表明，奖赏信息和行为参数不仅是异质编码的，而且在不同的多巴胺神经元群体中也存在差异分布。逆行追踪和纤维光度法表明，投射到不同纹状体区域的多巴胺神经元群传递着不同的信号。这些数据得到了计算模型的支持，表明这种分布编码可以最大化动态范围并定制多巴胺信号，以促进不同纹状体区域的特殊作用。
Midbrain dopamine neurons are thought to play key roles in learning by conveying the difference between expected and actual outcomes. Recent evidence suggests diversity in dopamine signaling, yet 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. Our findings show that reward information and behavioral parameters are not only heterogeneously encoded but also differentially distributed across populations of dopamine neurons. Retrograde tracing and fiber photometry suggest that populations of dopamine neurons projecting to different striatal regions convey distinct signals. These data, supported by computational modeling, indicate that such distributional coding can maximize dynamic range and tailor dopamine signals to facilitate specialized roles of different striatal regions.