Статьи

Voluntary, flexible stopping of speech output is an essential aspect of speech motor control, especially during natural conversations. The cognitive and neural mechanisms of speech inhibition are not well understood. Here we have recorded direct high-density cortical activity while participants engaged in continuous speech production and were visually cued to stop speaking. Neural recordings revealed distinct activity in the premotor frontal cortex correlated with stopping speech. This activity was found in largely separate cortical sites from regions encoding vocal tract articulatory movements. Moreover, this activity primarily occurred with abrupt stopping in the middle of an utterance, rather than naturally completing a phrase. Electrocortical stimulation at many premotor sites with inhibitory stop activity caused involuntary speech arrest, which contradicts previous clinical interpretations of this effect as evidence for critical centres of speech production. Together, these results suggest a previously unknown premotor cortical network that supports the inhibitory control of speech, providing implications for understanding both natural and altered speech production.

Humans lack memories for specific events from the first few years of life. We investigated the mechanistic basis of this infantile amnesia by scanning the brains of awake infants with functional magnetic resonance imaging while they performed a subsequent memory task. Greater activity in the hippocampus during the viewing of previously unseen photographs was related to later memory-based looking behavior beginning around 1 year of age, suggesting that the capacity to encode individual memories comes online during infancy. The availability of encoding mechanisms for episodic memory during a period of human life that is later lost from our autobiographical record implies that postencoding mechanisms, whereby memories from infancy become inaccessible for retrieval, may be more responsible for infantile amnesia.

Background. Fluid intelligence is an integral cognitive ability that involves solving new non-standard problems. It strongly predicts academic and professional achievement, whereas a low level of fluid intelligence is an important predictor of learning problems. Clinical studies of fluid intelligence are of interest for the development of training programs in various groups of children with special needs. This article presents a study on fluid intelligence in children with learning disabilities. Objective. This study aimed to investigate characteristics of fluid intelligence and its relationships with other cognitive characteristics in children with learning disabilities. Design. This study involved 93 children, divided into two groups: 55 typically developing children (control group) and 38 children with learning disabilities (clinical group). To assess intelligence characteristics, this study employed the Kaufman Assessment Battery for Children (KABC-II) and the Wechsler Intelligence Scale for Children Fifth Edition (WISC-V). Results. A reduction was found in fluid intelligence, working memory, short-term memory, long-term memory, processing speed, visual-spatial abilities, and verbal abilities in the group of children with learning disabilities compared to the control group. In the clinical group, fluid intelligence was strongly associated with a greater number of cognitive parameters compared to the control group. Conclusions. It is possible to assume that a close connection of fluid intelligence with the assessed cognitive characteristics in the group of children with learning disabilities may be due to general challenges in cognitive development.

By adulthood, humans rapidly identify objects from sparse visual displays and across large disruptions to their appearance. What are the minimal conditions needed to achieve robust recognition abilities and when might these abilities develop? To answer these questions, we investigated the upper limits of children’s object recognition abilities. We found that children as young as 3 years successfully identified objects at speeds of 100 milliseconds (both forward and backward masked) under sparse and disrupted viewing conditions. By contrast, a range of computational models implemented with biologically informed properties or optimized for visual recognition did not reach child-level performance. Models only matched children if they received more object examples than children are capable of experiencing. These findings highlight the robustness of the human visual system in the absence of extensive experience and identify important developmental constraints for building biologically plausible machines.

This study aims to investigate the impact of avatar identification on the intention to share by examining the mediating role of user immersion and the moderating effect of perceived social distance. For this, we collected 228 higher education students in South Korea through a survey and used hierarchical regression with SPSS 24.0. In the results, first, it showed that participants who perceived higher levels of similarity identification, wishful identification, and embodied presence in their avatars in the metaverse platform were more immersed in their avatars. Second, participants who perceived greater embodied presence in their avatars had a stronger intention to share their avatars through immersion. Finally, the positive relationship between perceived embodied presence and immersion was more significant for participants in metaverse platforms with higher perceived social distance compared to those with lower perceived social distance. This study is the first to examine the integral model of avatar identification factors in the metaverse platform. And, this study’s results show the mechanism by which avatar identification enhances the intention to share.

Emotion regulation (ER) plays a central role in mental health, but the effect differs across cultures. Here, expanding from extant literature’s focus on Western–Eastern dichotomy or individualism–collectivism, this meta-analysis synthesized evidence on the associations between the two most-studied ER strategies (cognitive reappraisal and expressive suppression) and two mental health outcomes (psychopathology and positive functioning) and investigated the moderating roles of several cultural dimensions: Hofstede’s national cultures dimensions, education, industrialization, richness and democracy (EIRDness), and sample demographics. A comprehensive literature search was conducted using electronic databases (CINAHL, Scopus, Web of Science, PsycINFO and MEDLINE) to identify eligible studies reporting relationships between ER and mental health outcomes (PROSPERO: CRD42021258190, 249 articles, n = 150,474, 861 effect sizes, 37 countries/regions). For Hofstede’s national cultures and EIRDness, multimodel inference revealed that greater reappraisal propensity was more adaptive in more short-term-oriented, uncertainty-tolerant and competition-driven cultures, whereas greater suppression propensity was more maladaptive in more indulgent and competition-driven cultures. For demographics, greater reappraisal propensity was more adaptive for samples with more female (B = −0.19, 95% confidence interval (CI) −0.29 to −0.09) and more racial minority participants (B = −0.32, 95% CI −0.51 to −0.13), whereas greater suppression propensity was more maladaptive in younger samples (B = −0.004, 95% CI −0.005 to −0.002). These findings elucidate how cultures are associated with the function of ER and suggests ways in which future studies can integrate cultural characteristics when examining ER and psychological adjustment.

Background. After decades of research, gender differences in spatial abilities (SA) remain poorly understood. Among factors that may contribute to these differences are self-perceived SA, inclinations, everyday behaviour and interests in SA-related activities, and related personality characteristics. In order to understand these links, a multifactorial approach is needed. Objective. This study explored the relationships among SA, spatial interests, and personality among adolescent boys and girls. Design. The study recruited 660 participants (mean age = 15.04, SD = 1.08; 48% females) from public schools. Participants contributed data on a battery of SA tests; 8 personality traits: Big Five and Dark Triad; as well as SA-related activities: spatial interests and school commute information (mode and time) as a proxy for everyday spatial behaviour. Results. Weak-to-moderate mean gender differences were observed: males scored higher on spatial ability, spatial interests, machiavellianism, and psychopathy; and females on agreeableness, openness to experience, and neuroticism. Hierarchical regression analyses revealed some gender differences in associations among personality traits and SA. In males, openness to experience and conscientiousness were significantly related to SA test performance. In females, openness to experience, extraversion, agreeableness, and machiavellianism contributed to SA performance. Although spatially-related interests were linked to SA, they were not significantly predicted by personality traits. Everyday spatial behaviour showed no relationship with personality traits or SA. Conclusion. The study replicated patterns of gender differences in spatial ability, spatial interests, and personality reported in previous literature. The results showed differential links between personality traits and spatial ability for males and females. However, the overall amount of variance explained in spatial ability was very small, suggesting that other factors are more prominent sources of gender differences in spatial ability.

Understanding how animals and humans learn from experience to make adaptive decisions is a fundamental goal of neuroscience and psychology. Normative modelling frameworks such as Bayesian inference1 and reinforcement learning2 provide valuable insights into the principles governing adaptive behaviour. However, the simplicity of these frameworks often limits their ability to capture realistic biological behaviour, leading to cycles of handcrafted adjustments that are prone to researcher subjectivity. Here we present a novel modelling approach that leverages recurrent neural networks to discover the cognitive algorithms governing biological decision-making. We show that neural networks with just one to four units often outperform classical cognitive models and match larger neural networks in predicting the choices of individual animals and humans, across six well-studied reward-learning tasks. Critically, we can interpret the trained networks using dynamical systems concepts, enabling a unified comparison of cognitive models and revealing detailed mechanisms underlying choice behaviour. Our approach also estimates the dimensionality of behaviour3 and offers insights into algorithms learned by meta-reinforcement learning artificial intelligence agents. Overall, we present a systematic approach for discovering interpretable cognitive strategies in decision-making, offering insights into neural mechanisms and a foundation for studying healthy and dysfunctional cognition.

Scientific research is often characterized by schools of thought. We investigate whether these divisions are associated with differences in researchers’ cognitive traits such as tolerance for ambiguity. These differences may guide researchers to prefer different problems, tackle identical problems in different ways, and even reach different conclusions when studying the same problems in the same way. We surveyed 7,973 researchers in psychological sciences and investigated links between what they research, their stances on open questions in the field, and their cognitive traits and dispositions. Our results show that researchers’ stances on scientific questions are associated with what they research and with their cognitive traits. Further, these associations are detectable in their publication histories. These findings support the idea that divisions in scientific fields reflect differences in the researchers themselves, hinting that some divisions may be more difficult to bridge than suggested by a traditional view of data-driven scientific consensus.

Many children from low-income backgrounds worldwide fail to master school mathematics1; however, some children extensively use mental arithmetic outside school2,3. Here we surveyed children in Kolkata and Delhi, India, who work in markets (n = 1,436), to investigate whether maths skills acquired in real-world settings transfer to the classroom and vice versa. Nearly all these children used complex arithmetic calculations effectively at work. They were also proficient in solving hypothetical market maths problems and verbal maths problems that were anchored to concrete contexts. However, they were unable to solve arithmetic problems of equal or lesser complexity when presented in the abstract format typically used in school. The children’s performance in market maths problems was not explained by memorization, access to help, reduced stress with more familiar formats or high incentives for correct performance. By contrast, children with no market-selling experience (n = 471), enrolled in nearby schools, showed the opposite pattern. These children performed more accurately on simple abstract problems, but only 1% could correctly answer an applied market maths problem that more than one third of working children solved (β = 0.35, s.e.m. = 0.03; 95% confidence interval = 0.30–0.40, P < 0.001). School children used highly inefficient written calculations, could not combine different operations and arrived at answers too slowly to be useful in real-life or in higher maths. These findings highlight the importance of educational curricula that bridge the gap between intuitive and formal maths.