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经典条件作用驱动了外侧小脑中攀爬纤维的习得性奖励预测信号。

Classical conditioning drives learned reward prediction signals in climbing fibers across the lateral cerebellum.

机构信息

Department of Neurobiology, Duke University School of Medicine, Durham, United States.

出版信息

Elife. 2019 Sep 11;8:e46764. doi: 10.7554/eLife.46764.

Abstract

Classical models of cerebellar learning posit that climbing fibers operate according to a supervised learning rule to instruct changes in motor output by signaling the occurrence of movement errors. However, cerebellar output is also associated with non-motor behaviors, and recently with modulating reward association pathways in the VTA. To test how the cerebellum processes reward related signals in the same type of classical conditioning behavior typically studied to evaluate reward processing in the VTA and striatum, we have used calcium imaging to visualize instructional signals carried by climbing fibers across the lateral cerebellum in mice before and after learning. We find distinct climbing fiber responses in three lateral cerebellar regions that can each signal reward prediction. These instructional signals are well suited to guide cerebellar learning based on reward expectation and enable a cerebellar contribution to reward driven behaviors, suggesting a broad role for the lateral cerebellum in reward-based learning.

摘要

经典的小脑学习模型假设, climbing fibers 根据监督学习规则运作,通过信号运动错误的发生来指示运动输出的变化。然而,小脑输出也与非运动行为有关,最近还与调节 VTA 中的奖励关联途径有关。为了测试小脑在同一类型的经典条件反射行为中如何处理奖励相关信号,该行为通常用于评估 VTA 和纹状体中的奖励处理,我们使用钙成像技术在学习前后可视化小鼠外侧小脑中 climbing fibers 携带的指令信号。我们在三个外侧小脑区域中发现了独特的 climbing fiber 反应,每个反应都可以信号奖励预测。这些指令信号非常适合指导基于奖励预期的小脑学习,并使小脑能够对奖励驱动的行为做出贡献,这表明外侧小脑在基于奖励的学习中具有广泛的作用。

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