理研CBS-トヨタ連携センター

研究成果

2022/10/05

Perceptions of social rigidity predict loneliness across the Japanese population

figure 1

Loneliness is associated with mental and physical health problems and elevated suicide risk, and is increasingly widespread in modern societies. However, identifying the primary factors underlying loneliness remains a major public health challenge. Historically, loneliness was thought to result from a lack of high-quality social connections, but broader cultural factors (e.g. social norms) are increasingly recognized to also influence loneliness. Here, we used a large-scale survey (N = 4977) to assess to what degree the loneliness epidemic in Japan is associated with traditional measures of social isolation (number of close friends), cultural factors (perceptions of social rigidity, as measured by relational mobility), and socioeconomic factors (e.g. income). We confirmed that a lack of close friends is a dominant factor underlying loneliness in Japan. We also found that perceptions of the social rigidity in one’s environment was a major correlate of loneliness. Subjects who perceived lower levels of rigidity in their social environments felt significantly less lonely than those who perceived higher levels of social rigidity, though the association was weak in low income males. Thus, Japanese society and other high social rigidity cultures may need to reflect on the possibility that inflexible traditional norms of socialization are exacerbating loneliness.

 

 

新しい論文が発表されました。

Subjective time compression induced by continuous action

Sayako Ueda and Shingo Shimoda

Abstract

Increasing evidence indicates that voluntary actions can modulate the subjective time experience of its outcomes to optimize dynamic interaction with the external environment. In the present study, using a temporal reproduction task where participants reproduced the duration of an auditory  stimulus to which they were previously exposed by performing different types of voluntary action, we examined how the subjective time experience of action outcomes changed with voluntary action types. Two experiments revealed that the subjective time experience of action outcomes was compressed, compared with physical time, if the action was performed continuously (Experiment 1), possibly enhancing the experience of controlling the action outcome, or if the action was added an extra task-unrelated continuous action (Experiment 2), possibly reflecting different underlying mechanisms from subjective time compression induced by the task-related continuous action. The majority of prior studies have focused on the subjective time experience of action outcomes when actions were performed voluntarily or not, and no previous study has examined the effects of differences in voluntary action types on the subjective time experience of action outcomes. These findings may be useful in situations in which people wish to intentionally compress their own time experience of daily events through their voluntary actions.

Multiscale Computation and Dynamic Attention in Biological and Artificial Intelligence

Ryan Paul Badman, Thomas Trenholm Hills & Rei Akaishi

Biological and artificial intelligence (AI) are often defined by their capacity to achieve a hierarchy of short-term and long-term goals that require incorporating information over time and space at both local and global scales. More advanced forms of this capacity involve the adaptive modulation of integration across scales, which resolve computational inefficiency and explore-exploit dilemmas at the same time. Research in neuroscience and AI have both made progress towards understanding architectures that achieve this. Insight into biological computations come from phenomena such as decision inertia, habit formation, information search, risky choices and foraging. Across these domains, the brain is equipped with mechanisms (such as the dorsal anterior cingulate and dorsolateral prefrontal cortex) that can represent and modulate across scales, both with top-down control processes and by local to global consolidation as information progresses from sensory to prefrontal areas. Paralleling these biological architectures, progress in AI is marked by innovations in dynamic multiscale modulation, moving from recurrent and convolutional neural networks—with fixed scalings—to attention, transformers, dynamic convolutions, and consciousness priors—which modulate scale to input and increase scale breadth. The use and development of these multiscale innovations in robotic agents, game AI, and natural language processing (NLP) are pushing the boundaries of AI achievements. By juxtaposing biological and artificial intelligence, the present work underscores the critical importance of multiscale processing to general intelligence, as well as highlighting innovations and differences between the future of biological and artificial intelligence. View Full-Text