Classical conditioning drives learned reward prediction signals in climbing fibers across the lateral cerebellum
Classical conditioning drives learned reward prediction signals in climbing fibers across the lateral cerebellum
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DOI：
10.7554/elife.46764
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发表时间：
2019-09-11
期刊：
影响因子：
7.7
通讯作者：
Hull, Court
中科院分区：
文献类型：
--
作者：
Heffley, William;Hull, Court
小脑学习的经典模型假设，攀爬纤维根据有监督的学习规则工作，通过发出运动错误发生的信号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中的奖赏关联路径有关。为了测试小脑如何在同一类型的经典条件反射行为中处理奖赏相关信号，典型的研究是评估VTA和纹状体中的奖赏处理，我们使用钙成像技术在学习前后可视化小鼠小脑外侧的攀爬纤维携带的指示信号。我们在三个小脑外侧区域发现了不同的爬行纤维反应，每个反应都可以发出奖励预测的信号。这些指示信号非常适合于指导基于奖励期望的小脑学习，并使小脑对奖励驱动的行为做出贡献，这表明小脑外侧在基于奖励的学习中发挥着广泛的作用。
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.