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默认的自我中心主义:一种 MVPA 方法,用于研究自己和他人社会政治态度的重叠。

Default egocentrism: an MVPA approach to overlap in own and others' socio-political attitudes.

机构信息

Kairos Research, Dayton, OH 45458, USA.

Department of Psychology, University of California, Los Angeles, CA 90095, USA.

出版信息

Soc Cogn Affect Neurosci. 2023 Jun 20;18(1). doi: 10.1093/scan/nsad028.

Abstract

Understanding the socio-political attitudes of other people is a crucial skill, yet the neural mechanisms supporting this capacity remain understudied. This study used multivariate pattern analysis to examine patterns of activity in the default mode network (DMN) while participants assessed their own attitudes and the attitudes of other people. Classification analyses indicated that common patterns in DMN regions encode both own and others' support across a variety of contemporary socio-political issues. Moreover, cross-classification analyses demonstrated that a common coding of attitudes is implemented at a neural level. This shared informational content was associated with a greater perceived overlap between own attitude positions and those of others (i.e. attitudinal projection), such that higher cross-classification accuracy corresponded with greater attitudinal projection. This study thus identifies a possible neural basis for egocentric biases in the social perception of individual and group attitudes and provides additional evidence for self/other overlap in mentalizing.

摘要

理解他人的社会政治态度是一项至关重要的技能,但支持这种能力的神经机制仍未得到充分研究。本研究使用多元模式分析来检查默认模式网络(DMN)中的活动模式,同时参与者评估自己的态度和他人的态度。分类分析表明,DMN 区域中的共同模式编码了各种当代社会政治问题中的自身和他人的支持。此外,交叉分类分析表明,态度的共同编码是在神经水平上实现的。这种共享的信息内容与自身态度立场与他人态度立场之间的感知重叠(即态度投射)有关,即更高的交叉分类准确性对应于更大的态度投射。因此,这项研究确定了社会感知个体和群体态度时自我中心偏见的可能神经基础,并为心理理论中的自我/他人重叠提供了额外证据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2253/10281243/85dc7a1db745/nsad028f1.jpg

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