The voice of conscience: neural bases of interpersonal guilt and compensation

Yu, Hongbo; Hu, Jie; Hu, Li; Zhou, Xiaolin

doi:10.1093/scan/nst090

Cited by 91 publications

(131 citation statements)

References 54 publications

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“…The right AI has been consistently associated with the processing of negative experiences in social interactions, such as broken promises (Baumgartner et al, 2009), social exclusion (Eisenberger, 2012, aggression (Krämer et al, 2007), interpersonal guilt (Yu et al, 2014), and being treated unfairly (Sanfey et al, 2003). More recently, Liljeholm et al (2014) demonstrated that the right AI tracked the interaction between intentionality and harmful consequence in an interpersonal transgression context, such that intentionally inflicted bodily harm (e.g., delivering aversive salty tea to the participants) elicited higher AI responses than unintentionally inflicted harm.…”

Section: Discussionmentioning

confidence: 99%

Neural Substrates of Intention–Consequence Integration and Its Impact on Reactive Punishment in Interpersonal Transgression

Zhou

2015

J. Neurosci.

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When evaluating interpersonal transgressions, people take into account both the consequential damage and the intention of the agent. The intention and consequence, however, do not always match, as is the case with accidents and failed attempts. We combined an interactive game and functional MRI to investigate the neural substrates underlying the processing of intention and consequence, and its bearing on reactive punishment. The participant interacted with anonymous partners, who decided to deliver pain stimulation either to himself/herself or to the participant to earn a monetary reward. In some cases, the decision was reversed by the computer. After pain delivery, the partner's intention was revealed. Unbeknownst to the partner, the participant was then allowed to punish the partner by reducing his/her monetary reward. Behaviorally, the punishment was lower in the accidental condition (unintended harm relative to intended harm) but higher in the failed-attempt condition (unintended no-harm relative to intended no-harm). Neurally, the left amygdala/hippocampus was activated in the conditions with blameworthy intention (i.e., intentional harm and failed attempt). The accidental (relative to intentional) harm activated the right temporoparietal junction (TPJ) and the anterior inferior frontal gyrus (IFG), while the failed attempt (relative to genuine no-harm) activated the anterior insula (AI) and the posterior IFG. Effective connectivity analysis revealed that in the unintentional conditions (i.e., accidental and failed attempt) the IFG received input from the TPJ and AI, and sent regulatory signals to the amygdala. These findings demonstrate that the processing of intention may gate the emotional responses to transgression and regulate subsequent reactive punishment.

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Section: Discussionmentioning

confidence: 99%

Neural Substrates of Intention–Consequence Integration and Its Impact on Reactive Punishment in Interpersonal Transgression

Zhou

2015

J. Neurosci.

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“…Importantly, left AI and dlPFC showed interactions between action agency and empathic pain, indicating that these regions may integrate the processing of self-generated errors with the social consequences of actions (Koban et al, 2013a). This integration process should be crucial for the generation of moral emotions such as guilt and shame that are associated with self-generated actions that have socially negative consequences (Chang et al, 2011;Koban et al, 2013a;Wagner et al, 2012b;Wagner et al, 2011;Yu et al, 2013).…”

Section: Social Influences On the Monitoring Of Self-generated Actionsmentioning

confidence: 99%

Brain systems underlying the affective and social monitoring of actions: An integrative review

Koban

Pourtois

2014

Neuroscience & Biobehavioral Reviews

155

159

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(max 170 words)Action monitoring allows the swift detection of conflicts, errors, and the rapid evaluation of outcomes. These processes are crucial for learning, adaptive behavior, and for the regulation of cognitive control. Our review discusses neuroimaging and electrophysiological studies that have explored the contribution of emotional and social factors during action monitoring. Metaanalytic brain activation maps demonstrate reliable overlap of error monitoring, emotional, and social processes in the dorsal mediofrontal cortex (dMFC), lateral prefrontal areas, and anterior insula (AI). Cumulating evidence suggests that action monitoring is modulated by trait anxiety and negative affect, and that activity of the dMFC and the amygdala during action monitoring might contribute to the 'affective tagging' of actions along a valence dimension. The role of AI in action monitoring may be the integration of outcome information with self-agency and social context factors, thereby generating more complex situation-specific and conscious emotional feeling states. Our review suggests that action-monitoring processes operate at multiple levels in the human brain, and are shaped by dynamic interactions with affective and social processes.Keywords: Anterior insula; dorsal cingulate cortex; mediofrontal cortex; amygdala; error monitoring; ERN; feedback processing; social cognition; emotions; cognitive control; emotioncognition interactions; meta-analysis 3 Overview and motivationIn order to adapt their behavior, to detect and learn from errors, and ultimately to increase their chances of survival, humans and other animals have to monitor their actions (Rabbitt, 1966). Flexible regulation of behavior requires its constant evaluation in terms of performance and outcomes, as well as in terms of costs and future consequences. Action and error monitoring have been studied for several decades in psychology and neuroscience (for previous reviews see (Etkin et al., 2011;Moser et al., 2013;Pessoa, 2008;Proudfit et al., 2013;Shackman et al., 2011;Shenhav et al., 2013), we propose that error and action monitoring is an intrinsically affective and social process. However, we show that meta-analytic activation maps support overlapping brain responses to error processing, emotional, and social information processing not only in dMFC, but also in several other brain regions, including anterior insula and lateral prefrontal cortex.Further, recent intracranial electrophysiological recordings showed error-related activity in the amygdala, suggesting this limbic region may contribute to affective responses to errors and negative action outcomes. In the closing part, we outline an integrative framework for 4 understanding the brain systems underlying affective and social interactions with action monitoring, which may be crucial to foster behavioral control in real life.

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“…Functional neuroimaging studies have focused on imagining the event in which they felt the most guilt that they had ever experienced (Shin et al, 2000), intentionally or accidentally (Berthoz et al, 2006), gender difference (Michl et al, 2014), interpersonal (altruistic) guilt (Yu et al, 2014) or deontological guilt (Basile et al, 2011), compensation that might be stimulated by guilt (Yu et al, 2014), differences between guilty and embarrassment (Takahashi et al, 2004), compassion (Zahn et al, 2009a), pride (Zahn et al, 2009b), shame (Wagner et al, 2011) (Michl et al, 2014), and sadness (Wagner et al, 2011). In these functional studies, feelings of guilt were related to activation of the superior temporal/ inferior parietal lobule (IPL) including the superior temporal sulcus (STS) (Takahashi et al, 2004;Michl et al, 2014), ventromedial prefrontal cortex (vmPFC) (Zahn et al, 2009b;Morey et al, 2012), insula (Shin et al, 2000;Yu et al, 2014;Michl et al, 2014), amygdala, and subgenual cingulate cortex (SCC) (Zahn et al, 2009a(Zahn et al, ,b, 2013. A structural neuroimaging study dealing with healthy subjects linked proneness to guilt with individual variations in anterior brain regions (Zahn et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Comprehensive neural networks for guilty feelings in young adults

et al. 2015

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Feelings of guilt are associated with widespread self and social cognitions, e.g., empathy, moral reasoning, and punishment. Neural correlates directly related to the degree of feelings of guilt have not been detected, probably due to the small numbers of subjects, whereas there are growing numbers of neuroimaging studies of feelings of guilt. We hypothesized that the neural networks for guilty feelings are widespread and include the insula, inferior parietal lobule (IPL), amygdala, subgenual cingulate cortex (SCC), and ventromedial prefrontal cortex (vmPFC), which are essential for cognitions of guilt. We investigated the association between regional gray matter density (rGMD) and feelings of guilt in 764 healthy young students (422 males, 342 females; 20.7 ± 1.8 years) using magnetic resonance imaging and the guilty feeling scale (GFS) for the younger generation which comprises interpersonal situation (IPS) and rule-breaking situation (RBS) scores. Both the IPS and RBS were negatively related to the rGMD in the right posterior insula (PI). The IPS scores were negatively correlated with rGMD in the left anterior insula (AI), right IPL, and vmPFC using small volume correction. A post hoc analysis performed on the significant clusters identified through these analyses revealed that rGMD activity in the right IPL showed a significant negative association with the empathy quotient. These findings at the whole-brain level are the widespread comprehensive neural network regions for guilty feelings. Interestingly, the novel finding in this study is that the PI was implicated as a common region for feelings of guilt with interaction between the IPS and RBS. Additionally, the neural networks including the IPL were associated with empathy and with regions implicated in moral reasoning (AI and vmPFC), and punishment (AI).

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The voice of conscience: neural bases of interpersonal guilt and compensation

Cited by 91 publications

References 54 publications

Neural Substrates of Intention–Consequence Integration and Its Impact on Reactive Punishment in Interpersonal Transgression

Neural Substrates of Intention–Consequence Integration and Its Impact on Reactive Punishment in Interpersonal Transgression

Brain systems underlying the affective and social monitoring of actions: An integrative review

Comprehensive neural networks for guilty feelings in young adults

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