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前额叶血管活性肠肽能神经元在逆向学习中的选择性参与。

Selective engagement of prefrontal VIP neurons in reversal learning.

作者信息

Yi Jee Hyun, Yoon Young Ju, Jeong Huijeong, Choe Seo Yeon, Jung Min Whan

机构信息

Center for Synaptic Brain Dysfunctions, Institute for Basic Science, Daejeon 34141, Republic of Korea.

Department of Neurology, University of California, San Francisco, San Francisco, CA 94158, USA.

出版信息

Sci Adv. 2025 Jul 25;11(30):eadt4945. doi: 10.1126/sciadv.adt4945. Epub 2025 Jul 23.

Abstract

To gain insights into neural mechanisms enabling behavioral adaptations to complex and multidimensional environmental dynamics, we examined roles of vasoactive intestinal polypeptide (VIP)-expressing neurons in mouse medial prefrontal cortex (mPFC) in probabilistic reversal learning. Behaviorally, manipulating VIP neuronal activity left probabilistic classical conditioning unaffected but severely impaired reversal learning. Physiologically, conditioned cue-associated VIP neuronal responses changed abruptly after encountering an unexpected reward. They also conveyed strong reward prediction error signals during behavioral reversal, but not before or after, unlike pyramidal neurons that consistently conveyed error signals throughout all phases. Furthermore, the signal's persistence across trials correlated with reversal learning duration. These results suggest that mPFC VIP neurons play crucial roles in rapid reversal learning, but not in gradual value updating under stable probabilistic contingencies, by monitoring salient deviations from ongoing environmental contingencies and imposing error-correction signals during behavioral adjustments. These findings shed light on the intricate cortical circuit dynamics underpinning behavioral flexibility in complex, multifaceted environments.

摘要

为深入了解使行为适应复杂多维环境动态的神经机制,我们研究了小鼠内侧前额叶皮质(mPFC)中表达血管活性肠肽(VIP)的神经元在概率性反转学习中的作用。在行为方面,操纵VIP神经元活动对概率性经典条件反射没有影响,但严重损害了反转学习。在生理方面,与条件线索相关的VIP神经元反应在遇到意外奖励后会突然改变。与在所有阶段都持续传递误差信号的锥体神经元不同,它们在行为反转期间也传递强烈的奖励预测误差信号,但在之前或之后则不然。此外,该信号在试验中的持续性与反转学习持续时间相关。这些结果表明,mPFC VIP神经元通过监测与当前环境意外情况的显著偏差并在行为调整期间施加纠错信号,在快速反转学习中起关键作用,但在稳定概率性意外情况下的渐进价值更新中不起作用。这些发现揭示了支撑复杂多面环境中行为灵活性的复杂皮质回路动态。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a00/12285700/dd9f4377a66e/sciadv.adt4945-f1.jpg

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