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社会学习的神经和计算系统。

The neural and computational systems of social learning.

机构信息

Department of Clinical Neuroscience, Division of Psychology, Karolinska Institutet, Solna, Sweden.

Laboratory of Emotions' Neurobiology, Centre of Excellence for Neural Plasticity and Brain Disorders (BRAINCITY), Nencki Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland.

出版信息

Nat Rev Neurosci. 2020 Apr;21(4):197-212. doi: 10.1038/s41583-020-0276-4. Epub 2020 Mar 12.

DOI:10.1038/s41583-020-0276-4
PMID:32221497
Abstract

Learning the value of stimuli and actions from others - social learning - adaptively contributes to individual survival and plays a key role in cultural evolution. We review research across species targeting the neural and computational systems of social learning in both the aversive and appetitive domains. Social learning generally follows the same principles as self-experienced value-based learning, including computations of prediction errors and is implemented in brain circuits activated across task domains together with regions processing social information. We integrate neural and computational perspectives of social learning with an understanding of behaviour of varying complexity, from basic threat avoidance to complex social learning strategies and cultural phenomena.

摘要

从他人那里学习刺激和行为的价值——社会学习——适应性地有助于个体的生存,并在文化进化中发挥关键作用。我们综述了跨物种的研究,这些研究针对的是厌恶和偏好领域中社会学习的神经和计算系统。社会学习通常遵循与基于自我经验的价值学习相同的原则,包括预测误差的计算,并通过激活跨任务领域的大脑回路以及处理社会信息的区域来实现。我们将社会学习的神经和计算观点与对不同复杂程度的行为的理解相结合,从基本的回避威胁到复杂的社会学习策略和文化现象。

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