Coding Dynamics of the Striatal Networks During Learning.

IF 2.7 3区 医学 Q3 NEUROSCIENCES
eNeuro Pub Date : 2024-10-29 Print Date: 2024-10-01 DOI:10.1523/ENEURO.0436-23.2024
Maxime Villet, Patricia Reynaud-Bouret, Julien Poitreau, Jacopo Baldi, Sophie Jaffard, Ashwin James, Alexandre Muzy, Evgenia Kartsaki, Gilles Scarella, Francesca Sargolini, Ingrid Bethus
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引用次数: 0

Abstract

The rat dorsomedial (DMS) and dorsolateral striatum (DLS), equivalent to caudate nucleus and putamen in primates, are required for goal-directed and habit behaviour, respectively. However, it is still unclear whether and how this functional dichotomy emerges in the course of learning. In this study, we investigated this issue by recording DMS and DLS single neuron activity in rats performing a continuous spatial alternation task, from the acquisition to optimized performance. We first applied a classical analytical approach to identify task-related activity based on the modifications of single neuron firing rate in relation to specific task events or maze trajectories. We then used an innovative approach based on Hawkes process to reconstruct a directed connectivity graph of simultaneously recorded neurons, that was used to decode animal behavior. This approach enabled us to better unravel the role of DMS and DLS neural networks across learning stages. We showed that DMS and DLS display different task-related activity throughout learning stages, and the proportion of coding neurons over time decreases in the DMS and increases in the DLS. Despite these major differences, the decoding power of both networks increases during learning. These results suggest that DMS and DLS neural networks gradually reorganize in different ways in order to progressively increase their control over the behavioral performance.

学习过程中纹状体网络的编码动态
大鼠背内侧纹状体(DMS)和背外侧纹状体(DLS)相当于灵长类动物的尾状核和普塔门,分别是目标定向行为和习惯行为所必需的。然而,这种功能上的二分法是否以及如何在学习过程中出现,目前仍不清楚。在本研究中,我们通过记录大鼠在执行连续空间交替任务时从习得到优化的 DMS 和 DLS 单神经元活动来研究这一问题。我们首先采用经典的分析方法,根据单神经元发射率与特定任务事件或迷宫轨迹相关的变化来识别与任务相关的活动。然后,我们采用了一种基于霍克斯过程的创新方法,重建了同时记录的神经元的有向连接图,用于解码动物行为。这种方法使我们能够更好地揭示 DMS 和 DLS 神经网络在不同学习阶段的作用。我们发现,DMS 和 DLS 在整个学习阶段表现出不同的任务相关活动,而且随着时间的推移,编码神经元的比例在 DMS 中减少,在 DLS 中增加。尽管存在这些重大差异,但在学习过程中,两个网络的解码能力都在增强。我们的研究有助于理解背内侧纹状体(DMS)和背外侧纹状体(DLS)在行为策略的习得和优化过程中的作用。一般认为,背内侧纹状体介导行动-结果关联,而背外侧纹状体支持习惯行为,但这些过程在学习过程中是如何出现的仍不清楚。为了分析DMS和DLS网络活动在不同学习阶段的动态变化,我们使用了一种结合单神经元发射率和神经元之间连接的数学分析方法来解码大鼠在目标定向空间任务中的行为。我们证明,在所有学习阶段,DMS 和 DLS 活动都支持行为表现,从而对 DMS 活动逐渐转向 DLS 活动的假说提出了质疑。
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来源期刊
eNeuro
eNeuro Neuroscience-General Neuroscience
CiteScore
5.00
自引率
2.90%
发文量
486
审稿时长
16 weeks
期刊介绍: An open-access journal from the Society for Neuroscience, eNeuro publishes high-quality, broad-based, peer-reviewed research focused solely on the field of neuroscience. eNeuro embodies an emerging scientific vision that offers a new experience for authors and readers, all in support of the Society’s mission to advance understanding of the brain and nervous system.
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