Belief reasoning is typical mental state reasoning in Theory of Mind (ToM). Although previous studies have explored the neural bases of belief reasoning, the neural correlates of belief reasoning for self and for others are rarely addressed. The decoupling mechanism of distinguishing the mental state of others from one’s own is essential for ToM processing. To address the electrophysiological bases underlying the decoupling mechanism, the present event-related potential study compared the time course of neural activities associated with belief reasoning for self and for others when the belief belonging to self was consistent or inconsistent with others. Results showed that during a 450-600 ms period, belief reasoning for self elicited a larger late positive component (LPC) than for others when beliefs were inconsistent with each other. The LPC divergence is assumed to reflect the categorization of agencies in ToM processes.

Developmental and neuroscience works have demonstrated that the moral judgment is influenced by theory of mind (ToM), which refers to the ability to represent the mental states of different agents. However, the neural and cognitive time course of interactions between moral judgment and ToM remains unclear. The present event-related potential (ERP) study investigated the underlying neural substrate of the interaction between moral judgment and ToM by contrasting the ERPs elicited by moral judgments for self and for others in moral dilemmas. In classic moral dilemmas, the agents must choose between the utilitarian choice (taking the action to kill or harm an innocent person but saving more people) and the non-utilitarian choice (taking no action to kill or harm the innocent person but letting some people die). The ERPs were recorded from participants who made moral judgments for self and for others when the agent made utilitarian or non-utilitarian choices during the dilemma. The results revealed that the moral judgment for others elicited a larger frontal late positive component (LPC, 500–900 ms) than that for self when the agents made utilitarian choices, while no difference was observed on early components of N1, P2, and N2. Moreover, individual differences in mentalizing ability were negatively correlated with the LPC amplitudes. These findings suggested that ToM modulated the late controlled process but not the early automatic process during moral judgments.

Intention is a typical mental state in the theory of mind. However, to date, there have been theoretical debates on the conceptual structure of intention. The neural and cognitive time course of intention reasoning remains unclear. The present event-related potential (ERP) study had two purposes: first, to investigate the neural correlates of intention reasoning based on a differentiated conceptual structure distinguishing desire and intention; second, to investigate the neural basis of intention reasoning for different agents. Thus, we compared the neural activity elicited by intention reasoning for self and for others when the intention matched or mismatched the desire of the agent. The results revealed that three ERP components distinguished among different types of intention reasoning. A negative-going ERP deflection with right frontal distribution between 400 and 500 ms might reflect the cognitive conflict involved in intention reasoning, a right frontal late positive component might be associated with the categorisation of agents, and a centro-parietal late slow wave might indicate the conceptual mental operations associated with decoupling mechanisms in intention processing. These findings implied the neural and cognitive time course of intention reasoning and provided neural evidence for the differentiated conception of intention.

This study sought to identify key factors in university students’ physical and mental health by using a combination of methods, including classical statistical analysis and machine learning techniques. Physical and mental health test data were collected from undergraduates of the 2020 to 2023 cohorts at a university. A self-designed questionnaire on factors associated with physical and mental health was also sent to randomly selected undergraduate students from the same university. The study data were analyzed by one-way analysis of variance, Pearson correlation analysis, hierarchical regression analysis, and a machine learning model. The results revealed that participation in school sports clubs (β = −0.111, p < 0.001) and amount of exercise (β = 0.182, p < 0.001) were significant predictors of physical health status. Difficult family economic situation (β = 0.162, p < 0.001), major satisfaction (β = −0.092, p = 0.02), the quality of a romantic relationship (β = −0.121, p = 0.003), the quality of interpersonal relationships (β = −0.157, p < 0.001), and an overprotective family parenting style (β = 0.109, p = 0.011) were significant predictors of mental health status. The results of regression analysis and application of the machine learning model identified that the amount of exercise, quality of interpersonal relationships, and family parenting style had consistent effects on both the physical and mental health of university students.