Suppr超能文献

可识别性对第三方惩罚影响的神经计算基础。

Neurocomputational Substrates Underlying the Effect of Identifiability on Third-Party Punishment.

机构信息

Key Laboratory of Brain, Cognition and Education Sciences, South China Normal University, Ministry of Education, Guangzhou, 510631, China

School of Psychology, South China Normal University, Guangzhou, 510631, China.

出版信息

J Neurosci. 2023 Nov 22;43(47):8018-8031. doi: 10.1523/JNEUROSCI.0460-23.2023.

Abstract

The identifiable target effect refers to the preference for helping identified victims and punishing identifiable perpetrators compared with equivalent but unidentifiable counterparts. The identifiable target effect is often attributed to the heightened moral emotions evoked by identified targets. However, the specific neurocognitive processes that mediate and/or modulate this effect remain largely unknown. Here, we combined a third-party punishment game with brain imaging and computational modeling to unravel the neurocomputational underpinnings of the identifiable transgressor effect. Human participants (males and females) acted as bystanders and punished identified or anonymous wrongdoers. Participants were more punitive toward identified wrongdoers than anonymous wrongdoers because they took a vicarious perspective of victims and adopted lower reference points of inequity (i.e., more stringent norms) in the identified context than in the unidentified context. Accordingly, there were larger activity of the ventral anterior insula, more distinct multivariate neural patterns in the dorsal anterior insula and dorsal anterior cingulate cortex, and lower strength between ventral anterior insula and dorsolateral PFC and between dorsal anterior insula and ventral striatum connectivity in response to identified transgressors than anonymous transgressors. These findings implicate the interplay of expectancy violations, emotions, and self-interest in the identifiability effect. Last, individual differences in the identifiability effect were associated with empathic concern/social dominance orientation, activity in the precuneus/cuneus and temporo-parietal junction, and intrinsic functional connectivity of the dorsolateral PFC. Together, our work is the first to uncover the neurocomputational processes mediating identifiable transgressor effect and to characterize psychophysiological profiles modulating the effect. The identifiable target effect, more help to identified victims or stronger punishment to identifiable perpetrators, is common in daily life. We examined the neurocomputational mechanisms mediating/modulating the identifiability effect on third-party punishment by bridging literature from economics and cognitive neuroscience. Our findings reveal that identifiable transgressor effect is mediated by lower reference points of inequity (i.e., more stringent norms), which might be associated with a stronger involvement of the emotion processes and a weaker engagement of the analytic/deliberate processes. Furthermore, personality traits, altered brain activity, and intrinsic functional connectivity contribute to the individual variance in the identifiability effect. Overall, our study advances the understanding of the identifiability effect by shedding light on its component processes and modulating factors.

摘要

可识别目标效应是指与同等但不可识别的对应物相比,人们更倾向于帮助可识别的受害者和惩罚可识别的犯罪者。可识别目标效应通常归因于可识别目标引起的更高道德情感。然而,介导和/或调节这种效应的具体神经认知过程在很大程度上仍然未知。在这里,我们结合第三方惩罚游戏和脑成像以及计算模型来揭示可识别侵犯者效应的神经计算基础。人类参与者(男性和女性)充当旁观者并惩罚可识别或匿名的作恶者。参与者对可识别的作恶者比对匿名的作恶者更具惩罚性,因为他们从受害者的替代视角出发,并在可识别的情境中采用更低的不公平参考点(即更严格的规范),而不是在不可识别的情境中。因此,在响应可识别的违规者时,腹侧前扣带回的活动更大,背侧前扣带回和背侧前扣带皮层的多变量神经模式更为明显,以及腹侧前扣带回与背外侧前额叶皮层和背侧前扣带与腹侧纹状体之间的连接强度更低。这些发现表明,可识别性效应中的期望违反、情绪和自身利益相互作用。最后,可识别性效应的个体差异与同理心/社会支配倾向、楔前叶/楔叶和颞顶联合区的活动以及背外侧前额叶皮层的内在功能连接有关。总之,我们的工作首次揭示了介导可识别侵犯者效应的神经计算过程,并描述了调节该效应的心理生理特征。在日常生活中,可识别目标效应更为常见,即更多地帮助可识别的受害者或对可识别的犯罪者进行更严厉的惩罚。我们通过将经济学和认知神经科学的文献联系起来,研究了介导/调节第三方惩罚中可识别性效应的神经计算机制。我们的发现表明,可识别的侵犯者效应是由不公平的较低参考点(即更严格的规范)介导的,这可能与情绪过程的更强参与和分析/深思熟虑过程的较弱参与有关。此外,人格特质、改变的大脑活动和内在功能连接有助于可识别性效应的个体差异。总的来说,我们的研究通过揭示其组成过程和调节因素,推进了对可识别性效应的理解。

相似文献

1
Neurocomputational Substrates Underlying the Effect of Identifiability on Third-Party Punishment.
J Neurosci. 2023 Nov 22;43(47):8018-8031. doi: 10.1523/JNEUROSCI.0460-23.2023.
2
An fMRI investigation of the intention-outcome interactions in second- and third-party punishment.
Brain Imaging Behav. 2022 Apr;16(2):715-727. doi: 10.1007/s11682-021-00555-z. Epub 2021 Sep 17.
3
Strengths of social ties modulate brain computations for third-party punishment.
Sci Rep. 2023 Jun 28;13(1):10510. doi: 10.1038/s41598-023-37286-8.
4
Neural substrates of context- and person-dependent altruistic punishment.
Hum Brain Mapp. 2017 Nov;38(11):5535-5550. doi: 10.1002/hbm.23747. Epub 2017 Jul 26.
5
Computational substrates of social norm enforcement by unaffected third parties.
Neuroimage. 2016 Apr 1;129:95-104. doi: 10.1016/j.neuroimage.2016.01.040. Epub 2016 Jan 26.
6
To Blame or Not? Modulating Third-Party Punishment with the Framing Effect.
Neurosci Bull. 2022 May;38(5):533-547. doi: 10.1007/s12264-021-00808-3. Epub 2022 Jan 6.
7
Distinct affective responses to second- and third-party norm violations.
Acta Psychol (Amst). 2020 Apr;205:103060. doi: 10.1016/j.actpsy.2020.103060. Epub 2020 Mar 25.
8
Acute stress during witnessing injustice shifts third-party interventions from punishing the perpetrator to helping the victim.
PLoS Biol. 2024 May 16;22(5):e3002195. doi: 10.1371/journal.pbio.3002195. eCollection 2024 May.
9
Effective connectivity of brain regions underlying third-party punishment: Functional MRI and Granger causality evidence.
Soc Neurosci. 2017 Apr;12(2):124-134. doi: 10.1080/17470919.2016.1153518. Epub 2016 Mar 10.

本文引用的文献

1
Stan: A Probabilistic Programming Language.
J Stat Softw. 2017;76. doi: 10.18637/jss.v076.i01. Epub 2017 Jan 11.
3
Ire and punishment: Incidental anger and costly punishment in children, adolescents, and adults.
J Exp Child Psychol. 2022 Jun;218:105376. doi: 10.1016/j.jecp.2022.105376. Epub 2022 Jan 31.
4
Striving toward translation: strategies for reliable fMRI measurement.
Trends Cogn Sci. 2021 Sep;25(9):776-787. doi: 10.1016/j.tics.2021.05.008. Epub 2021 Jun 14.
5
Common brain networks underlying human social interactions: Evidence from large-scale neuroimaging meta-analysis.
Neurosci Biobehav Rev. 2021 Jul;126:289-303. doi: 10.1016/j.neubiorev.2021.03.025. Epub 2021 Mar 26.
6
We, Them, and It: Dictator Game Offers Depend on Hierarchical Social Status, Artificial Intelligence, and Social Dominance.
Front Psychol. 2020 Nov 23;11:541756. doi: 10.3389/fpsyg.2020.541756. eCollection 2020.
7
Prediction of trust propensity from intrinsic brain morphology and functional connectome.
Hum Brain Mapp. 2021 Jan;42(1):175-191. doi: 10.1002/hbm.25215. Epub 2020 Oct 1.
9
Ten simple rules for the computational modeling of behavioral data.
Elife. 2019 Nov 26;8:e49547. doi: 10.7554/eLife.49547.
10
Neurocognitive mechanisms of reactions to second- and third-party justice violations.
Sci Rep. 2019 Jun 25;9(1):9271. doi: 10.1038/s41598-019-45725-8.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验