Group cohesiveness in children free-play activity: A social network analysis

Despite the ethnic diversity and presence of Amerindian communities in all Brazilian states, the indigenous population suffers from a long process of invisibility and stereotyping. Aiming to increase interethnic associations, together with Mbya-Guarani leaders we promoted interventions in which indigenous and non-indigenous children shared free playtime. We hypothesised that free play activity would stimulate group cohesiveness, mitigating ethnic group avoidance in children's playgroups. Twenty-one Mbya-Guarani and 61 non-indigenous children participated in two “Encounters for Play.” We recorded children's social interactions during the free playtimes. We selected the first and last 10 minutes of each encounter and performed scans every 30s registering spatial proximity (children who were up to 1 m of each other) and play. Then, we applied Social Network Analysis to explore the children's association pattern at the beginning and end of playtime in each encounter. Our results show free play activity was effective in stimulating group cohesiveness. Children' proximity association pattern and playgroup configuration changed between clips, and there was a significant correlation between both categories' associations. We conclude that the encounters have potential applicability as an intervention to mitigate ethnic group avoidance in children.     

Centrality in children's best friend networks: The role of social behaviour

Centrality is an indicator of an individual's relative importance within a social group. Predictors of centrality in best friendship networks were examined in 146 children (70 boys and 76 girls, M_age = 9.95). Children completed measures of social confidence, social desirability, friendship quality, school liking, and loneliness and nominated their best friends from within their class at two time points, 3 months apart. Multigroup path analysis revealed gender differences in the antecedents of centrality. Social confidence, social desirability, and friendship quality predicted changes in the indicators of centrality in best friend networks over time. Boys' social behaviour positively predicted changes in centrality, whereas girls' social behaviour negatively predicted changes in centrality. Together, these findings suggest that some aspects of social behaviour are influential for centrality in best friend groups.     

汉字部件与英文字母相容性的数学模型──一种群体模板相容性的数学表达

该文运用相容性研究中的维度重叠模型以及Ｆｏｒｋ－Ｊｏｉｎ网络模型，得出群体模板的相容性定义与Ｓ－Ｒ相容性的元素匹配之间的关系式，详细讨论了汉字编码输入法研究中的学习遍数、反应时与汉字部件－英文字母相容性的关系，理论模拟与实验结果所显示的趋势符合。     

The minimal self hypothesis

For millennia self has been conjectured to be necessary for consciousness. But scant empirical evidence has been adduced to support this hypothesis. Inconsistent explications of “self” and failure to design apt experiments have impeded progress. Advocates of phenomenological psychiatry, however, have helped explicate “self,” and employed it to explain some psychopathological symptoms. In those studies, “self” is understood in a minimalist sense, sheer “for-me-ness.” Unfortunately, explication of the “minimal self” (MS) has relied on conceptual analysis, and applications to psychopathology have been hermeneutic, allowing for many degrees of interpretive latitude. The result is that MS’s current scientific status is analogous to that of the “atom,” at the time when “atom” was just beginning to undergo transformation from a philosophical to a scientific concept. Fortunately, there is now an opportunity to promote a similar transformation for “MS.” Discovery of the brain’s Default Mode Network (DMN) opened the door to neuroimaging investigations of self. Taking the DMN and other forms of intrinsic activity as a starting point, an empirical foothold can be established, one that spurs experimental research and that enables extension of research into multiple phenomena. New experimental protocols that posit “MS” can help explain phenomena hitherto not thought to be related to self, thereby hastening development of a mature science of self. In particular, targeting phenomena wherein consciousness is lost and recovered, as in some cases of Unresponsive Wakefulness Syndrome (UWS), allow for design of neuroimaging probes that enable detection of MS during non-conscious states. These probes, as well as other experimental protocols applied to NREM Sleep, General Anesthesia (GA), and the waking state, provide some evidence to suggest that not only can self and consciousness dissociate, MS might be a necessary precondition for conscious experience. Finally, these findings have implications for the science of consciousness: it has been suggested that “levels of consciousness” (LoC) is not a legitimate concept for the science of consciousness. But because we have the conceptual and methodological tools with which to refine investigations of MS, we have the means to identify a possible foundation—a bifurcation point—for consciousness, as well as the means by which to measure degrees of distance from that foundation. These neuroimaging investigations of MS position us to better assess whether LoC has a role to play in a mature science of consciousness.     

Functional connectivity associated with five different categories of Autonomous Sensory Meridian Response (ASMR) triggers

Autonomous sensory meridian response (ASMR) is a sensory-emotional phenomenon in which specific sensory stimuli (“ASMR triggers”) reliably elicit feelings of relaxation and tingling sensations on the head, neck, and shoulders. However, there are individual differences in which stimuli elicit ASMR and in the intensity of these responses. In the current research, we used resting-state fMRI to examine the functional connectivity associated with these differences. Fifteen individuals with self-reported ASMR completed the ASMR Checklist, which measures sensitivity to different ASMR triggers, and a resting-state fMRI scan. Checklist scores were entered as covariates to determine whether the functional connectivity of eight resting-state networks differed as a function of participants’ sensitivity to five categories of triggers. The results indicated unique patterns of functional connectivity associated with sensitivity to each ASMR trigger category. Sensitivity to two trigger categories was positively correlated with the dorsal attention network, suggesting that ASMR may involve atypical attentional processing.     

Perceiving college peers’ alcohol consumption: temporal patterns and individual differences in overestimation

Objective: This study examines temporal patterns and individual differences of overestimation in alcohol norm perception within a social network.

Design: Hundred psychology freshmen indicated biweekly during their first semester the drinks they consumed, the perceived average of their peers’ consumption, and with whom they were acquainted. At baseline, trait self-control was assessed.

Main outcome: The moderation of alcohol consumption overestimation by time and individual characteristics was explored.

Results: Results show that students overestimated alcohol consumption of their acquainted peers by 1.22 drinks (p?<?.001). For time periods at which peers reported high consumption, overestimation decreased. Additionally, individuals reporting high alcohol consumption (b?=??0.25, p?<?.001) and low self-control (b?=?0.27, p?=?.010) showed higher overestimation.

Conclusions: Students overestimate the alcohol consumption of peers not fully accounting for changes in peer-reports. Furthermore, individual differences suggest informational and motivational processes underlying overestimation.     

Applying Deutsch’s concept of good explanations to artificial intelligence and neuroscience – An initial exploration

Artificial intelligence has made great strides since the deep learning revolution, but AI systems remain incapable of learning principles and rules which allow them to extrapolate outside of their training data to new situations. For inspiration we look to the domain of science, where scientists have been able to develop theories which show remarkable ability to extrapolate and sometimes even predict the existence of phenomena which have never been observed before. According to David Deutsch, this type of extrapolation, which he calls “reach”, is due to scientific theories being hard to vary. In this work we investigate Deutsch’s hard-to-vary principle and how it relates to more formalized principles in deep learning such as the bias-variance trade-off and Occam’s razor. We distinguish internal variability, how much a model/theory can be varied internally while still yielding the same predictions, with external variability, which is how much a model must be varied to predict new, out-of-distribution data. We discuss how to measure internal variability using the notion of the Rashomon set and how to measure external variability using Kolmogorov complexity. We explore what role hard-to-vary explanations play in intelligence by looking at the human brain, the only example of highly general purpose intelligence known. We distinguish two learning systems in the brain – the first operates similar to deep learning and likely underlies most of perception while the second is a more creative system capable of generating hard-to-vary models and explanations of the world. We make contact with Popperian epistemology which suggests that the generation of scientific theories is a not an inductive process but rather an evolutionary process which proceeds through conjecture and refutation. We argue that figuring out how replicate this second system, which is capable of generating hard-to-vary explanations, is a key challenge which needs to be solved in order to realize artificial general intelligence.