人际去人性化及其相关脑网络的功能作用

IF 21.8 Q1 PSYCHOLOGY, MULTIDISCIPLINARY
Lasana T. Harris, Naira Delgado
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引用次数: 0

摘要

非人性化通常被认为是一种群体间现象,人们在群体关系的基础上被降低到低于人类的地位。然而,在日常生活中,人们经常忽视他人的情绪状态,这可以被认为是一种更微妙的非人化形式。在这篇综述中,我们研究了人际非人化,我们将其定义为无法推断他人的精神状态。首先,我们在三个时间尺度上描述了人际非人性化的功能:作为对过去道德违规的回顾性辩护,作为当前行为的促进者,以及作为一种主动的共情调节策略。接下来,我们考虑促进和影响日常非人性化的大脑网络:具体来说,与社会认知、同理心和道德决策相关的网络。最后,我们提出了人际非人性化研究的未来研究方向及其影响,可以为制定具体解决方案提供信息,以促进日常生活中更人道和道德的互动。非人性化通常被认为是一种群体间现象,但无法推断他人的心理状态也发生在日常人际交往中。在这篇综述中,Harris和Delgado在三个时间尺度上描述了人际非人化的功能,并讨论了它们的支持脑网络。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

The functional role of interpersonal dehumanization and associated brain networks

The functional role of interpersonal dehumanization and associated brain networks
Dehumanization is typically considered as an intergroup phenomenon, whereby people are reduced to less-than-human status on the basis of group affiliations. However, in everyday life, people often disregard the emotional states of others, which could be considered a more subtle form of dehumanization. In this Review, we examine interpersonal dehumanization, which we define as a failure to infer another person’s mental state. First, we describe the functions of interpersonal dehumanization at three temporal scales: as retrospective justification for past moral violations, as a facilitator of present behaviours and as a proactive empathy-regulation strategy. Next, we consider the brain networks that facilitate and influence daily dehumanization: specifically, networks associated with social cognition, empathy and moral decision making. We conclude by suggesting future research directions for the study of interpersonal dehumanization and its implications that could inform the development of concrete solutions to foster more humane and ethical interactions in everyday life. Dehumanization is typically considered as an intergroup phenomenon, but failures to infer another person’s mental state also occur in everyday interpersonal contexts. In this Review, Harris and Delgado describe the functions of interpersonal dehumanization at three temporal scales and discuss their supporting brain networks.
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来源期刊
CiteScore
9.30
自引率
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