Toward a Brain-Based Bio-Marker of Guilt.

Guilt biomarker function MRI morality social cognition

Journal

Neuroscience insights
ISSN: 2633-1055
Titre abrégé: Neurosci Insights
Pays: United States
ID NLM: 101760670

Informations de publication

Date de publication:
2020
Historique:
received: 14 08 2020
accepted: 20 08 2020
entrez: 30 9 2020
pubmed: 1 10 2020
medline: 1 10 2020
Statut: epublish

Résumé

Guilt is a quintessential emotion in interpersonal interactions and moral cognition. Detecting the presence and measuring the intensity of guilt-related neurocognitive processes is crucial to understanding the mechanisms of social and moral phenomena. Existing neuroscience research on guilt has been focused on the neural correlates of guilt states induced by various types of stimuli. While valuable in their own right, these studies have not provided a sensitive and specific bio-marker of guilt suitable for use as an indicator of guilt-related neurocognitive processes in novel experimental settings. In a recent study, we identified a distributed Guilt-Related Brain Signature (GRBS) based on 2 independent functional MRI datasets. We demonstrated the sensitivity of GRBS in detecting a critical cognitive antecedent of guilt, namely one's responsibility in causing harm to another person, across participant populations from 2 distinct cultures (ie, Chinese and Swiss). We also showed that the sensitivity of GRBS did not generalize to other types of negative affective states (eg, physical and vicarious pain). In this commentary, we discuss the relevance of guilt in the broader scope of social and moral phenomena, and discuss how guilt-related biomarkers can be useful in understanding their psychological and neurocognitive mechanisms underlying these phenomena.

Identifiants

pubmed: 32995750
doi: 10.1177/2633105520957638
pii: 10.1177_2633105520957638
pmc: PMC7503000
doi:

Types de publication

Journal Article Comment

Langues

eng

Pagination

2633105520957638

Commentaires et corrections

Type : CommentOn

Informations de copyright

© The Author(s) 2020.

Déclaration de conflit d'intérêts

Declaration of conflicting interests:The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Références

Nat Neurosci. 2017 Feb 23;20(3):365-377
pubmed: 28230847
Br J Med Psychol. 2000 Dec;73 Pt 4:519-30
pubmed: 11140792
J Pers Soc Psychol. 1987 Aug;53(2):247-56
pubmed: 3625466
Soc Cogn Affect Neurosci. 2014 Aug;9(8):1150-8
pubmed: 23893848
Nat Commun. 2014 Nov 17;5:5380
pubmed: 25400102
Neuroimage. 2020 Aug 13;222:117251
pubmed: 32798682
J Cogn Neurosci. 2013 Feb;25(2):258-72
pubmed: 23163419
Psychol Bull. 1994 Mar;115(2):243-67
pubmed: 8165271
Trends Cogn Sci. 2006 Sep;10(9):424-30
pubmed: 16899397
Nat Rev Neurosci. 2012 May 03;13(6):421-34
pubmed: 22551663
Cereb Cortex. 2020 May 18;30(6):3558-3572
pubmed: 32083647
Science. 2014 Sep 12;345(6202):1340-3
pubmed: 25214626

Auteurs

Hongbo Yu (H)

Department of Psychological and Brain Sciences, University of California Santa Barbara, Santa Barbara, California, United States of America.

Leonie Koban (L)

Institute of Cognitive Science, University of Colorado, Boulder, CO, USA.
Department of Psychology and Neuroscience, University of Colorado, Boulder, CO, USA.

Molly J Crockett (MJ)

Department of Psychology, Yale University, New Haven, Connecticut, United States of America.

Xiaolin Zhou (X)

School of Psychological and Cognitive Sciences, Peking University, Beijing, China.
Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China.
PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China.
Institute of Psychological and Brain Sciences, Zhejiang Normal University, Zhejiang, China.
Key Laboratory of Applied Brain and Cognitive Sciences, School of Business and Management, Shanghai International Studies University, Shanghai, China.

Tor D Wager (TD)

Institute of Cognitive Science, University of Colorado, Boulder, CO, USA.
Department of Psychological and Brain Sciences, Dartmouth College, Hanover, New Hampshire, United States of America.

Classifications MeSH