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在规则学习过程中神经元表现的几何形状揭示了扣带皮层和纹状体的互补作用。

The geometry of neuronal representations during rule learning reveals complementary roles of cingulate cortex and putamen.

机构信息

Department of Neurobiology, Weizmann Institute of Science, Rehovot 76100, Israel.

出版信息

Neuron. 2021 Mar 3;109(5):839-851.e9. doi: 10.1016/j.neuron.2020.12.027. Epub 2021 Jan 22.

Abstract

Learning new rules and adopting novel behavioral policies is a prominent adaptive behavior of primates. We studied the dynamics of single neurons in the dorsal anterior cingulate cortex and putamen of monkeys while they learned new classification tasks every few days over a fixed set of multi-cue patterns. Representing the rules and the neuronal selectivity as vectors in the space spanned by a set of stimulus features allowed us to characterize neuronal dynamics in geometrical terms. We found that neurons in the cingulate cortex mainly rotated toward the rule, implying a policy search, whereas neurons in the putamen showed a magnitude increase that followed the rotation of cortical neurons, implying strengthening of confidence for the newly acquired rule-based policy. Further, the neural representation at the end of a session predicted next-day behavior, reflecting overnight retention. The novel framework for characterization of neural dynamics suggests complementing roles for the putamen and the anterior cingulate cortex.

摘要

学习新规则并采用新的行为策略是灵长类动物的一种突出的适应性行为。我们研究了猴子的背侧前扣带皮层和纹状体中的单个神经元的动力学,在几天的时间里,它们在一组固定的多线索模式上学习新的分类任务。通过在一组刺激特征所构成的空间中用向量来表示规则和神经元选择性,我们可以用几何术语来描述神经元的动力学。我们发现,扣带皮层中的神经元主要向规则方向旋转,这意味着一种策略搜索,而纹状体中的神经元则表现出与皮层神经元旋转一致的幅度增加,这意味着对新获得的基于规则的策略的信心增强。此外,在一个会话结束时的神经表示可以预测次日的行为,反映了夜间的保留。这种用于描述神经动力学的新框架表明,纹状体和前扣带皮层具有互补的作用。

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