The development of children’s social function is influenced by the social environment, and children also play an active role in shaping and nurturing this environment. The present study investigated the potential reciprocal dynamic impact of mothers’ mental state talk (MST) and the development of theory of mind (ToM) in children. Using a cross-sectional design, we explored the development of ToM in 3- to 5-year-old children using an unexpected location task, an unexpected content task, an appearance–reality task, and mothers’ MST during mother–child reading. The results showed the following: (1) the mothers’ MST exhibited a shift from a predilection for subjective terms (such as desires) to a preference for objective terms (such as cognitions) as their children matured; (2) the development of the children’s ToM was closely related to their mothers’ MST. The overall MST scores, as well as the different categories and referents used in MST, were closely associated with the children’s ToM development. Notably, at the age of four, a critical period emerged where the correlation between maternal MST and ToM became significantly pronounced. These findings highlight the reciprocal nature of mother–child interactions as a two-way adaptive process.

In this study, the complete mitochondrial genome sequence of Japanese macaque, Macaca fuscata fuscata, with the total length of 16,565 bp, is determined for the first time. This mitogenome harbors 13 protein-coding genes, 22 transfer RNA genes, 2 ribosomal RNA genes, and 1 control region (D-loop). The overall base composition is A (31.7%), C (30.5%), G (12.9%), and T (24.9%), so the slight A-T bias (56.6%) was detected. Most of the genes are distributed on H-strand, except for the ND6 subunit gene and eight tRNA genes. The complete mitochondrial genome sequence reported here will provide new genetic resource to uncover the monkey’s evolution.

Artificial intelligence (AI) is profoundly reshaping labor market structures and occupational value evaluation systems. As a core group about to enter the workplace, university students’ perceptions of occupational social status are crucial for their career development and the alignment between education and the labor market. Study 1 explores how layoff risks and AI as a threat shape status evaluation. Study 2 investigates how AI’s role in jobs alters perceptions of status indicators and cognitive work type. The results show that students primarily attribute occupational social status to personal ability and organizational hierarchy rather than AI; A more positive attitude toward AI is associated with a greater propensity for pursuing routine cognitive occupations in the future; AI exerts an inverted U-shaped influence on occupational status indicators, with non-routine cognitive occupations experiencing an earlier decline in status but still maintaining higher ratings than routine cognitive occupations. These findings indicate that university students hold an overall positive yet contradictory attitude toward AI’s impact on occupational social status, which is inconsistent with actual employment trends. Therefore, researchers and policymakers should provide more comprehensive guidance to help students understand and adapt to AI-driven changes.

The constant challenge in social interactions involves making informed decisions in the face of competitive and cooperative dilemmas. The decision-making process can be influenced by various factors present in the social context. According to the behavior-pattern-categorization framework of information acquisition, potential biases may develop at all stages of decision-making as information about social context is progressively entered and integrated. In this study, employing the Chicken Game, we investigated the influence of varying information levels within the behavior-pattern-categorization framework (i.e., competitiveness of behavior choice, uncertainty of behavior pattern, and sociality of category) on decision-making in the dilemma of competition and cooperation. Combined with reinforcement learning models, our findings from three experiments showed that participants exhibited basic complementary behavior, becoming less competitive against highly competitive opponents and vice versa. Notably, individuals exhibited varying adaptation rates to different levels of opponent competitiveness and fluctuations. Specifically, participants adapted slower to highly competitive opponents and faster to cooperative opponents. This asymmetric adaptation in social learning is related to the rate at which various levels of information are updated. The current study disentangles the different levels of information acquisition and highlights the asymmetric processing that can occur during the updating of information within each level.

Social status, as a prominent social characteristic, exerts a significant influence on various aspects of life. However, there is only limited behavioral and neural evidence regarding the relationship between social status and the construction of trust. In this study, we used computational modeling and functional magnetic resonance imaging to unveil the trajectory of trust-related processing by using a repeated trust game. Human participants assumed the role of trustor and engaged in interactions with fictitious partners (trustees) who varied in social status. Participants were more inclined to trust Superiors than Inferiors and gradually modified their trust decisions based on their partners’ reciprocity. Furthermore, we unveiled the neurocomputational mechanisms of two cognitive processes: (i) prior-based static modulation supported by the ventromedial prefrontal cortex (vmPFC), amygdala, and their neural coupling, and (ii) the reward network engaged in feedback-based dynamic modulation. We also found that prior bias in the social value of social status can reduce the reliance on the feedback-based dynamic modulation rooted in the vmPFC and ventral striatum. The present findings enhance the understanding of the neural representations of how social status modulates trust-related processing and trustworthiness updating.

In the auditory domain, the role of auditory working memory in shaping strategy selection and performance within both auditory rule-based and information-integration tasks remains unclear. To address this issue, the present study utilized a concurrent auditory working memory paradigm to investigate the impact of working memory on rule-based and information-integration category learning within the auditory domain. Additionally, we employed a categorization strategy model and drift-diffusion model to examine the impact of auditory working memory on auditory category learning. The categorization strategies model revealed that significantly more participants employed the optimal strategy in the control condition compared to the concurrent working memory condition in both the rule-based and information-integration tasks. Furthermore, given that most participants used the rule-based strategy in the information-integration task, the results showed a decrease in accuracy and an increase in reaction time for the concurrent working memory condition relative to the control condition in rule-based category learning. According to the drift-diffusion model, this decline observed under the concurrent working memory condition can be attributed to a reduction in information accumulation speed, increased cautious decision-making, and longer nondecision time. This study suggests that the concurrent working memory task interfered with participants’ strategy selection and performance, with decreased performance in the concurrent working memory condition stemming from slower information accumulation and extended nondecision time for the rule-based strategy, while more cautious decision-making was related to the information-integration strategy.