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There is abundant evidence on the human ability to encode complex social networks and on the behavioral consequences of tracking social network structure. However, it remains largely understudied whether mental representations of direct (i.e., the connections between self and others) and indirect (i.e., the connections between third parties) social relations impact lower-level perceptual processing. Across three experiments, the current study addressed this issue by examining the role of both self-related (Experiment 1, n = 96) and allocentric (Experiment 2, n = 87; Experiment 3, n = 85) connections in low-level perception with a perceptual matching task. Our results revealed that the perceptual discrimination of stimuli associated with different nationalities corresponds to the closeness between two nationalities. Specifically, it was more difficult for participants to perceptually discriminate nationalities with closer relations. Notably, the effects of social ties are independent of whether the closeness in relations is self-related or allocentric. Together, our findings suggest that the encoding of nationality relations modulates human perceptual processing in a generic manner., Author(s): Wanghuan Lin [sup.1] [sup.2] [sup.3] [sup.4] , Zhixin Zhang [sup.1] [sup.2] [sup.3] [sup.4] , Xingmei Zhou [sup.5] , Yue-Jia Luo [sup.5] [sup.6] [sup.7] , Chunliang Feng [sup.1] [sup.2] [sup.3] [...]

Human moral reactions to artificial intelligence (AI) agents' behavior constitute an important aspect of modern-day human–AI relationships. Although previous studies have mainly focused on autonomy ethics, this study investigates how individuals judge AI agents' violations of community ethics (including betrayals and subversions) compared with human violations. Participants' behavioral responses, event-related potentials (ERPs), and individual differences were assessed. Behavioral findings reveal that participants rated AI agents' community-violating actions less morally negative than human transgressions, possibly because AI agents are commonly perceived as having less agency than human adults. The ERP N1 component showed the same pattern with moral rating scores, indicating the modulation effect of human–AI differences on initial moral intuitions. Moreover, the level of social withdrawal correlated with a smaller N1 in the human condition but not in the AI condition. The N2 and P2 components were sensitive to the difference between the loyalty/betrayal and authority/subversion domains but not human/AI differences. Individual levels of moral sense and autistic traits also influenced behavioral data, especially on the loyalty/betrayal domain. In our opinion, these findings offer insights for predicting moral responses to AI agents and guiding ethical AI development aligned with human moral values. [ABSTRACT FROM AUTHOR]

Emotion and executive control are often conceptualized as two distinct modes of human brain functioning. Little, however, is known about how the dynamic organization of large-scale functional brain networks that support flexible emotion processing and executive control, especially their interactions. The amygdala and prefrontal systems have long been thought to play crucial roles in these processes. Recent advances in human neuroimaging studies have begun to delineate functional organization principles among the large-scale brain networks underlying emotion, executive control, and their interactions. Here, we propose a dynamic brain network model to account for interactive competition between emotion and executive control by reviewing recent resting-state and task-related neuroimaging studies using network-based approaches. In this model, dynamic interactions among the executive control network, the salience network, the default mode network, and sensorimotor networks enable dynamic processes of emotion and support flexible executive control of multiple processes; neural oscillations across multiple frequency bands and the locus coeruleus−norepinephrine pathway serve as communicational mechanisms underlying dynamic synergy among large-scale functional brain networks. This model has important implications for understanding how the dynamic organization of complex brain systems and networks empowers flexible cognitive and affective functions. [ABSTRACT FROM AUTHOR]

Previous studies examining the relationship between ingroup bias and resource scarcity have produced heterogeneous findings, possibly due to their focus on the allocation of positive resources (e.g. money). This study aims to investigate whether ingroup bias would be amplified or eliminated when perceived survival resources for counteracting negative stimuli are scarce. For this purpose, we exposed the participants and another confederate of the experimenters (ingroup/outgroup member) to a potential threat of unpleasant noise. Participants received some 'relieving resources' to counteract noise administration, the amount of which may or may not be enough for them and the confederate in different conditions (i.e. abundance vs. scarcity). First, a behavioural experiment demonstrated that intergroup discrimination manifested only in the scarcity condition; in contrast, the participants allocated similar amounts of resource to ingroup and outgroup members in the abundance condition, indicating a context‐dependent allocation strategy. This behavioural pattern was replicated in a follow‐up neuroimaging experiment, which further revealed that when contrasting scarcity with abundance, there was higher activation in the anterior cingulate cortex (ACC) as well as stronger functional connectivity of the ACC with the empathy network (including the temporoparietal junction and medial prefrontal cortex) for ingroup compared to outgroup members. We suggest that ACC activation reflects the mentalizing process toward ingroup over outgroup members in the scarcity condition. Finally, the ACC activation level significantly predicted the influence of resource scarcity on ingroup bias in hypothetical real‐life situations according to a follow‐up examination. [ABSTRACT FROM AUTHOR]

Autobiographical memory (AM) is an important psychological phenomenon that has significance for self-development and mental health. The psychological mechanisms of emotional AM retrieval and their association with individual emotional symptoms remain largely unclear in the literature. For this purpose, the current study provided cue words to elicit emotional AMs. Event-related potentials (ERPs) associated with the retrieval process of AMs were recorded and analyzed. We found that the ERP component N400 was sensitive to both emotional valence and retrieval state, such that its amplitude was larger for negative compared to positive AMs, and larger responses for unrecalled compared to recalled AMs. Further, the N400 amplitude in the positive recalled condition was correlated with individual difference in depression (measured by the Beck Depression Inventory). Another ERP component, the late positive potential (LPP), was also sensitive to emotional valence, such that its amplitude was larger (i.e., more positive-going) for positive compared to negative cues. No significant effect was observed on the early ERP components P1, N1, or P2. The current findings bring new understanding on the difference between positive and negative AMs retrieval in the time domain. Also, the importance of this difference to the individual level of depression is worth noting. [ABSTRACT FROM AUTHOR]

The cognitive and behavioral development of children and adolescents is closely related to the maturation of brain morphology. Although the trajectory of brain development has been depicted in detail, the underlying biological mechanism of normal cortical morphological development in childhood and adolescence remains unclear. By combining the Allen Human Brain Atlas dataset with two single‐site magnetic resonance imaging data including 427 and 733 subjects from China and the United States, respectively, we performed partial least squares regression and enrichment analysis to explore the relationship between the gene transcriptional expression and the development of cortical thickness in childhood and adolescence. We found that the spatial model of normal cortical thinning during childhood and adolescence is associated with genes expressed predominantly in astrocytes, microglia, excitatory and inhibitory neurons. Top cortical development‐related genes are enriched for energy‐related and DNA‐related terms and are associated with psychological and cognitive disorders. Interestingly, there is a great deal of similarity between the findings derived from the two single‐site datasets. This fills the gap between early cortical development and transcriptomes, which promotes an integrative understanding of the potential biological neural mechanisms. [ABSTRACT FROM AUTHOR]