Social cognitive and affective neuroscience最新文献

Social interaction plays a crucial role in human societies, encompassing complex dynamics among individuals. To understand social interaction at the neural level, researchers have utilized hyperscanning in several social settings. These studies have mainly focused on inter-brain synchrony and the efficiency of paired functional brain networks, examining group interactions in dyads. However, this approach may not fully capture the complexity of multiple interactions, potentially leading to gaps in understanding inter-network differences. To overcome this limitation, the present study aims to bridge this gap by introducing methodological enhancements using the multilayer network approach, which is tailored to extract features from multiple networks. We applied this strategy to analyze the triad condition during social behavior processes to identify group interaction indices. Additionally, to validate our methodology, we compared the multilayer networks of triad conditions with group synchrony to paired conditions without group synchrony, focusing on statistical differences between alpha and beta waves. Correlation analysis between inter-brain and group networks revealed that this methodology accurately reflects the characteristics of actual behavioral synchrony. The findings of our study suggest that measures of paired brain synchrony and group interaction may exhibit distinct trends, offering valuable insights into interpreting group synchrony.

Previous work suggests blood pressure (BP) relates to social algesia, where those with higher BP are more tolerant of social pain. The neural correlates of this association, however, are unknown. Based on findings suggesting neural regions involved in physical pain are activated during social pain, the current study explores whether BP relates to subjective and neural responses to social pain, apart from emotional responding. BP was measured, after which participants completed emotional processing and social exclusion functional magnetic resonance imaging (fMRI) paradigms. Results replicated previous findings, with higher systolic BP related to lower trait sensitivity to social pain. However, there were no associations between BP and reported sensitivity to social pain during social exclusion. Moreover, after accounting for adiposity, we found no association between BP and anterior insula (AI) or dorsal anterior cingulate cortex (dACC) activity to exclusion. Finally, there were no reliable associations between BP and reported valence or arousal, or AI and dACC activity to emotional images. Findings partly replicate and extend prior findings on BP and emotional responding to social pain; however, they appear inconsistent with predictions at the neural level. Future experimental manipulation of BP may allow for causal inferences and adjudication of conceptual perspectives on cardiovascular contributions to social algesia.

Previous work suggests blood pressure (BP) relates to social algesia, where those with higher BP are more tolerant of social pain. The neural correlates of this association, however, are unknown. Based on findings suggesting neural regions involved in physical pain are activated during social pain, the current study explores whether BP relates to subjective and neural responses to social pain, apart from emotional responding. BP was measured, after which participants completed emotional processing and social exclusion functional magnetic resonance imaging (fMRI) paradigms. Results replicated previous findings, with higher systolic BP related to lower trait sensitivity to social pain. However, there were no associations between BP and reported sensitivity to social pain during social exclusion. Moreover, after accounting for adiposity, we found no association between BP and anterior insula (AI) or dorsal anterior cingulate cortex (dACC) activity to exclusion. Finally, there were no reliable associations between BP and reported valence or arousal, or AI and dACC activity to emotional images. Findings partly replicate and extend prior findings on BP and emotional responding to social pain; however, they appear inconsistent with predictions at the neural level. Future experimental manipulation of BP may allow for causal inferences and adjudication of conceptual perspectives on cardiovascular contributions to social algesia.

Social interaction plays a crucial role in human societies, encompassing complex dynamics among individuals. To understand social interaction at the neural level, researchers have utilized hyperscanning in several social settings. These studies have mainly focused on inter-brain synchrony and the efficiency of paired functional brain networks, examining group interactions in dyads. However, this approach may not fully capture the complexity of multiple interactions, potentially leading to gaps in understanding inter-network differences. To overcome this limitation, the present study aims to bridge this gap by introducing methodological enhancements using the multilayer network approach, which is tailored to extract features from multiple networks. We applied this strategy to analyze the triad condition during social behavior processes to identify group interaction indices. Additionally, to validate our methodology, we compared the multilayer networks of triad conditions with group synchrony to paired conditions without group synchrony, focusing on statistical differences between alpha and beta waves. Correlation analysis between inter-brain and group networks revealed that this methodology accurately reflects the characteristics of actual behavioral synchrony. The findings of our study suggest that measures of paired brain synchrony and group interaction may exhibit distinct trends, offering valuable insights into interpreting group synchrony.

Prior research has supported some aspects of a theorized prejudice self-regulation model. We provide the first test of the full model-based process of bias regulation as it unfolds in real time. Event-related potentials (ERPs) were recorded from White undergraduates at two large American universities (N = 130; 40% female) during a racial stereotype priming task. Attention to Black male face primes, indexed by the P2 ERP, increased following self-regulation failures. In turn, within-person, trial-to-trial variability in attention to Black male faces predicted variability in bias expression. The latter effect was moderated by individual differences in internal motivation to respond without prejudice (IMS). Specifically, among lower-IMS individuals, trials in which Black faces elicited relatively larger P2 amplitudes (relative to an individual's own average P2 amplitude) were associated with increased behavioral race bias. In contrast, and consistent with theory, among higher-IMS individuals trials in which Black faces elicited larger relative P2 amplitudes were associated with decreased bias. Findings provide direct evidence supporting the temporal sequencing of race-bias regulation and identify within-person variability in attention to race as a potential mechanism for determining when and in whom bias will be regulated.

Prior research has supported some aspects of a theorized prejudice self-regulation model. We provide the first test of the full model-based process of bias regulation as it unfolds in real time. Event-related potentials (ERPs) were recorded from White undergraduates at two large American universities (N = 130; 40% female) during a racial stereotype priming task. Attention to Black male face primes, indexed by the P2 ERP, increased following self-regulation failures. In turn, within-person, trial-to-trial variability in attention to Black male faces predicted variability in bias expression. The latter effect was moderated by individual differences in internal motivation to respond without prejudice (IMS). Specifically, among lower-IMS individuals, trials in which Black faces elicited relatively larger P2 amplitudes (relative to an individual's own average P2 amplitude) were associated with increased behavioral race bias. In contrast, and consistent with theory, among higher-IMS individuals trials in which Black faces elicited larger relative P2 amplitudes were associated with decreased bias. Findings provide direct evidence supporting the temporal sequencing of race-bias regulation and identify within-person variability in attention to race as a potential mechanism for determining when and in whom bias will be regulated.

The interplay of mind attribution and emotional responses is considered crucial in shaping human trust and acceptance of social robots. Understanding this interplay can help us create the right conditions for successful human-robot social interaction in alignment with societal goals. Our study shows that affective information about robots describing positive, negative, or neutral behaviour leads participants (N = 90) to attribute mental states to robot faces, modulating impressions of trustworthiness, facial expression, and intentionality. Electroencephalography recordings from 30 participants revealed that affective information influenced specific processing stages in the brain associated with early face perception (N170 component) and more elaborate stimulus evaluation (late positive potential). However, a modulation of fast emotional brain responses, typically found for human faces (early posterior negativity), was not observed. These findings suggest that neural processing of robot faces alternates between being perceived as mindless machines and intentional agents: people rapidly attribute mental states during perception, literally seeing good or bad intentions in robot faces, but are emotionally less affected than when facing humans. These nuanced insights into the fundamental psychological and neural processes underlying mind attribution can enhance our understanding of human-robot social interactions and inform policies surrounding the moral responsibility of artificial agents.

The interplay of mind attribution and emotional responses is considered crucial in shaping human trust and acceptance of social robots. Understanding this interplay can help us create the right conditions for successful human-robot social interaction in alignment with societal goals. Our study shows that affective information about robots describing positive, negative, or neutral behaviour leads participants (N = 90) to attribute mental states to robot faces, modulating impressions of trustworthiness, facial expression, and intentionality. Electroencephalography recordings from 30 participants revealed that affective information influenced specific processing stages in the brain associated with early face perception (N170 component) and more elaborate stimulus evaluation (late positive potential). However, a modulation of fast emotional brain responses, typically found for human faces (early posterior negativity), was not observed. These findings suggest that neural processing of robot faces alternates between being perceived as mindless machines and intentional agents: people rapidly attribute mental states during perception, literally seeing good or bad intentions in robot faces, but are emotionally less affected than when facing humans. These nuanced insights into the fundamental psychological and neural processes underlying mind attribution can enhance our understanding of human-robot social interactions and inform policies surrounding the moral responsibility of artificial agents.

From both social and life perspectives, gratitude is essential for managing social relationships and fostering cooperation. This study investigated the dynamic influence of gratitude on two modalities of cooperative interactions and the associated interpersonal dynamic neural mechanism by integrating a dyadic ecological paradigm with functional near-infrared spectroscopy). Several critical findings emerged: the gratitude group exhibited better cooperative behaviors compared to the joy and neutral groups in both the Prisoner's Dilemma Game (PDG) and the Button-press Game (BPG). The dynamic cooperative behaviors further elucidated that gratitude dynamically facilitates cooperation by boosting inclusivity towards the benefactor's slight defect in the PDG and heightening action coordination in the BPG. Accordingly, higher inter-brain synchronization (IBS) was predominantly observed in the left and right middle frontal gyrus and the right sensorimotor cortex in the gratitude, compared to the joy and neutral groups. Moreover, the gratitude group exhibited increased IBS over time (across blocks) in the left and right middle frontal gyrus and the right superior temporal gyrus. These findings substantiate that gratitude facilitates widespread social cooperation and progressively enhances IBS among individuals. This work advances our understanding of gratitude-induced large-scale cooperative behaviors in societies.

From both social and life perspectives, gratitude is essential for managing social relationships and fostering cooperation. This study investigated the dynamic influence of gratitude on two modalities of cooperative interactions and the associated interpersonal dynamic neural mechanism by integrating a dyadic ecological paradigm with functional near-infrared spectroscopy). Several critical findings emerged: the gratitude group exhibited better cooperative behaviors compared to the joy and neutral groups in both the Prisoner's Dilemma Game (PDG) and the Button-press Game (BPG). The dynamic cooperative behaviors further elucidated that gratitude dynamically facilitates cooperation by boosting inclusivity towards the benefactor's slight defect in the PDG and heightening action coordination in the BPG. Accordingly, higher inter-brain synchronization (IBS) was predominantly observed in the left and right middle frontal gyrus and the right sensorimotor cortex in the gratitude, compared to the joy and neutral groups. Moreover, the gratitude group exhibited increased IBS over time (across blocks) in the left and right middle frontal gyrus and the right superior temporal gyrus. These findings substantiate that gratitude facilitates widespread social cooperation and progressively enhances IBS among individuals. This work advances our understanding of gratitude-induced large-scale cooperative behaviors in societies.