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了解你自己:用于了解他人的一般和特定神经计算。

Getting to know you: general and specific neural computations for learning about people.

作者信息

Stanley Damian A

机构信息

Division of the Humanities and Social Sciences, California Institute of Technology, Pasadena, CA 91125, USA

出版信息

Soc Cogn Affect Neurosci. 2016 Apr;11(4):525-36. doi: 10.1093/scan/nsv145. Epub 2015 Dec 8.

Abstract

Learning about other peoples' attributes, e.g. whether an individual is generous or selfish, is central to human social cognition. It is well documented that a network of cortical regions is reliably activated when we engage social processes. However, little is known about the specific computations performed by these regions or whether such processing is specialized for the social domain. We investigated these questions using a task in which participants (N= 26) learned about four peoples' generosity by watching them choose to share money with third party partners, or not. In a non-social control condition, participants learned the win/loss rates of four lotteries. fMRI analysis revealed learning-related general (social + non-social) prediction error signals in the dorsomedial and dorsolateral prefrontal cortices (bilaterally), and in the right lateral parietal cortex. Socially specific (social > non-social) prediction error signals were found in the precuneus. Interestingly, the region that exhibited social prediction errors was a distinct subregion of the area in the precuneus and posterior cingulate cortex that exhibited a commonly reported main effect of higher overall activity for social vs non-social stimuli. These findings elucidate the domain--general and--specific computations underlying learning about other people and demonstrate the increased explanatory power of computational approaches to social cognition.

摘要

了解他人的特质,比如一个人是慷慨还是自私,是人类社会认知的核心。有充分的文献记载,当我们参与社会活动时,一个皮层区域网络会被可靠地激活。然而,对于这些区域所执行的具体计算,或者这种处理是否专门针对社会领域,我们却知之甚少。我们使用一项任务来研究这些问题,在该任务中,参与者(N = 26)通过观察四个人是否选择与第三方伙伴分享金钱来了解他们的慷慨程度。在非社会控制条件下,参与者了解了四种彩票的输赢率。功能磁共振成像分析显示,在背内侧和背外侧前额叶皮层(双侧)以及右侧顶叶皮层中存在与学习相关的一般(社会 + 非社会)预测误差信号。在楔前叶中发现了社会特异性(社会 > 非社会)预测误差信号。有趣的是,表现出社会预测误差的区域是楔前叶和后扣带回皮层中一个独特的子区域,该区域通常报告为社会刺激比非社会刺激具有更高的总体活动主效应。这些发现阐明了了解他人背后的领域通用和领域特定计算,并证明了计算方法对社会认知的解释力增强。

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