Irrelevant‐action imitation is short‐term and contextual: Evidence from two under‐studied populations

Across the lifespan and across populations, humans ‘overimitate’ causally unnecessary behaviors. Such irrelevant‐action imitation facilitates faithful cultural transmission, but its immediate benefits to the imitator are controversial. Over short time scales, irrelevant‐action imitation may bootstrap artifact exploration or interpersonal affiliation, and over longer time scales it may facilitate acquisition of either causal models or social conventions. To investigate these putative functions, we recruited community samples from two under‐studied populations: Yasawa, Fiji, and Huatasani, Peru. We use a two‐action puzzle box: first after a video demonstration, and again one month later. Treating age as a continuous variable, we reveal divergent developmental trajectories across sites. Yasawans (44 adults, M = 39.9 years, 23 women; 42 children, M = 9.8 years, 26 girls) resemble documented patterns, with irrelevant‐action imitation increasing across childhood and plateauing in adulthood. In contrast, Huatasaneños (48 adults, M = 37.6 years, 33 women; 47 children, M = 9.3 years, 13 girls) evince a parabolic trajectory: adults at the site show the lowest irrelevant‐action imitation of any demographic set in our sample. In addition, all age sets in both populations reduce their irrelevant actions at Time 2, but do not reduce their relevant‐action imitation or goal attainment. Taken together, and considering the local cultural contexts, our results suggest that irrelevant‐action imitation serves a short‐term function and is sensitive to the social context of the demonstration.     

Statistical learning of multiple speech streams: A challenge for monolingual infants

Language acquisition depends on the ability to detect and track the distributional properties of speech. Successful acquisition also necessitates detecting changes in those properties, which can occur when the learner encounters different speakers, topics, dialects, or languages. When encountering multiple speech streams with different underlying statistics but overlapping features, how do infants keep track of the properties of each speech stream separately? In four experiments, we tested whether 8‐month‐old monolingual infants (N = 144) can track the underlying statistics of two artificial speech streams that share a portion of their syllables. We first presented each stream individually. We then presented the two speech streams in sequence, without contextual cues signaling the different speech streams, and subsequently added pitch and accent cues to help learners track each stream separately. The results reveal that monolingual infants experience difficulty tracking the statistical regularities in two speech streams presented sequentially, even when provided with contextual cues intended to facilitate separation of the speech streams. We discuss the implications of our findings for understanding how infants learn and separate the input when confronted with multiple statistical structures.     

ELM-HTM guided bio-inspired unsupervised learning for anomalous trajectory classification

Artificial intelligent systems often model the solutions of typical machine learning problems, inspired by biological processes, because of the biological system is faster and much adaptive than deep learning. The utility of bio-inspired learning methods lie in its ability to discover unknown patterns, and its less dependence on mathematical modeling or exhaustive training. In this paper, we propose a new bio-inspired learning model for a single-class classifier to detect abnormality in video object trajectories. The method uses a simple but dynamic extreme learning machine (ELM) and hierarchical temporal memory (HTM) together referred to as ELM-HTM in an unsupervised way to learn and classify time series patterns. The method has been tested on trajectory sequences in traffic surveillance to find abnormal behaviors such as high-speed, unusual stops, driving in wrong directions, loitering, etc. Experiments have also been performed with 3D air signatures captured using sensors and used for biometric authentication(forged/genuine). The results indicate a significant gain over training time and classification accuracy. The proposed method outperforms in predicting long-time patterns by observing small steps with an average accuracy gain of 15% as compared to the state-of-the-art HTM. The method has applications in detecting abnormal activities in videos by learning the movement patterns as well as in biometric authentication.     

Socially emotional brain-inspired cognitive architecture framework for artificial intelligence

Artificial Intelligence of the next generation needs to interact with users socially, convincing them in its ability to understand human minds, including emotions. For this to happen, an artificial emotional intelligence is needed, capable of adequate, believable behavior in social emotional interactions. Building on previous developments, the present work extends the general framework of emotional Biologically Inspired Cognitive Architecture (eBICA: Samsonovich, 2013, 2018), endowing it with fluents describing, in addition to appraisals, somatic markers, feelings, emotions, moods, emotional reactions and biases. Key building blocks that integrate them are moral schemas and semantic maps. The model describes interaction of three factors: plans and commitments, moral and ethical values, and somatic comfort. Learning in this framework includes self-organization of semantic maps that in turn may provide guidance for active humanlike learning. Implications for empirical studies and practical applications are discussed together with the expected impact.     

The role of instruction preference in analogy learning: Brain activity and motor performance

This study examined the role of verbal instruction preference when learning motor skills by analogy. During skill learning, analogies are a useful tool for providing knowledge about how to move. It has been argued that analogy instructions reduce reliance on verbal information processes during motor planning, compared to traditional forms of instruction (i.e., explicit rules about how to move). This may be reflected by reduced verbal activity in the brain, measured by EEG alpha power at the temporal region, as well as reduced verbal-motor cross-communication (EEG T7-Fz coherence) during the preparation phase of a movement. Preference for using verbal or visual instructions is likely to influence the efficacy of analogy instructions. This study investigated whether preference for verbal instructions was related to a) changes in performance and b) changes in verbal-cognitive information processing during performance of an adapted basketball task after instruction by analogy. Basketball novices with a high preference for verbal instructions (n = 15) showed significantly decreased activation of verbal brain regions when they used the analogy (high-alpha power), but their performance remained stable. Novices with a low preference for verbal instructions (n = 13) did not show a significant decrease in activation of verbal regions, and their performance deteriorated significantly after introduction of the analogy instruction. It is likely that both cognitive and performance changes after analogy instruction depend on personal aspects of information processing, such as verbal preference.     

Motivational climate,psychological needs,and personal and social responsibility in youth soccer: Comparisons by age group and competitive level

ObjectivesWe used a developmental lens to examine age group and competitive level differences on motivational climate dimensions, psychological needs satisfaction, and personal and social responsibility as well as relationships among variables, in line with basic psychological needs theory.DesignWe used a cross-sectional, correlational design.MethodGirls and boys age 8–13 on recreational and select soccer teams completed a survey.ResultsA 2 × 2 MANOVA showed main effects for age group and competitive level: early adolescents reported greater punishment for mistakes and autonomy compared to children; select players reported greater mastery climate dimensions and personal responsibility compared to recreational players. For all groups, path analyses revealed perceptions of cooperative learning were indirectly associated with personal and social responsibility, through coach and/or teammate relatedness.ConclusionsPatterns of relationships by age group and competitive level are discussed in reference to developmental literature. Results highlight the value of using a developmental approach to understand how coaches can promote youth soccer players’ psychological and social well-being.     

指尖上的学习：触屏学习的作用

触屏学习是通过触屏软硬件设备呈现学习内容,并以手势触屏交互方式获取知识或技能的过程。目前触屏学习基础性研究处于探索阶段,在有效性上,研究发现触屏学习本身可能是有效的,但在相对优势上结果具有较大异质性;在学习后效上,触屏学习有助于提高学习动机,但没有稳定地促进知识保持、知识理解以及二维到三维的学习迁移。针对触屏学习的促进或阻碍作用,以往研究分别从具身认知或认知负荷等理论视角给予解释。学习者、学习材料、学习环境等可能是影响触屏学习效果的重要因素。广泛地将触屏设备应用于学习或课堂场景为时尚早,呼吁未来研究从理论建构、影响因素、特点分析及行为/神经机制角度考察触屏学习的作用。     

基于助推的健康饮食行为干预策略

在干预国民健康饮食行为方面, 更“隐性”的助推策略因其针对直觉思维系统发挥作用, 比传统的干预政策更具优势。基于助推策略对食物选择决策影响机制的不同, 健康饮食助推策略可构建为提供决策信息、改善决策选项、影响决策结构和提醒决策方向4个大类及9个小类的框架体系。助推策略在实践中仍存在争议, 因而在中国实施时需与传统政策结合使用, 充分考虑中国国情和消费群体特征, 并充分利用信息技术和大数据优势, 助力健康中国。     

统计学习的认知神经机制及其与语言的关系

统计学习是指个体在连续刺激流中发现转移概率等统计规律的过程, 在Saffran等(1996)的经典婴儿语音切分研究中首次被提出。大量研究证实了统计学习的普遍存在, 近期学界开始关注统计学习的特异性及其对认知的影响, 尤其是从学习过程及其特异性两个方面阐述统计学习的认知神经机制并揭示其和语言的交互作用。未来应从脑和行为的多模态数据视角, 丰富统计学习结果的行为和神经指标, 考察不同类型统计学习过程的动态神经活动模式, 建立统计学习行为和脑的关联, 深化对统计学习认知神经机制的认识, 在统计学习与语言交互作用的基础上, 从成人二语学习切入结合音乐统计学习训练探讨促进语言学习的统计学习干预手段。     

隐藏情绪分析与识别方法

隐藏情绪识别对公共安全防范与预警具有重要的意义。微表情是揭示隐藏情绪的一条重要通道。但目前隐藏情绪研究较少且微表情因其细微幅度与快速出现等特性难以识别, 其研究尚未在实际中广泛应用。因为, 隐藏情绪的认知与表达机理亟需系统的研究,采集实际场景中的微表情数据, 并以脑电信号辅助微表情的精确标注是提高微表情标注效率的有效途径。深入研究微表情识别方法, 并辅以人脸颜色、注视估计和非接触生理信号等多通道数据, 以检测与识别隐藏情绪。社会公共安全是隐藏情绪分析和识别的典型场景。面向精神疾病患者两害行为(即危害自身或他人的危险行为)风险评估和服刑人员会见场景隐藏情绪检测, 可以有效地对相应系统和方法进行验证和修正。