情绪具身观：情绪研究的新视角

情绪具身性有着广泛的理论假说与研究证据, 从情绪外周理论到面部反馈假说、躯体标记假说再到现在的情绪具身观, 都一致认为情绪是具身的。情绪具身观认为情绪是包括大脑在内的身体的情绪, 身体的解剖学结构、身体的活动方式、身体的感觉和运动体验决定了我们怎样加工情绪。相关的行为和脑机制研究均支持了情绪加工的具身性。目前关于具身情绪的理论解释主要有镜像神经元系统假说、具身模仿论和知觉符号系统理论等。作为一种新兴的理论观点, 情绪具身观为情绪研究提供了新的视角。     

具身模拟在汉语肢体动作动词理解中的作用

通过3个实验, 考察具身模拟在汉语肢体动作动词理解中的作用。实验1考察在整字启动下具身模拟对运动通道中箭头方向判断的影响, 发现理解肢体动作动词在运动通道中存在着动作-汉字相容效应, 汉字的具身方向与箭头方向一致促进被试对箭头方向的判断。实验2考察在整字启动下具身经验对视觉通道中字母位置判断的影响, 发现理解肢体动作动词在视觉通道中存在着动作-汉字相容效应, 汉字的具身方位与字母方位一致促进对字母方位的识别。实验3采用义符启动范式考察义符与整字的具身模拟, 发现理解汉语肢体动作动词不仅在整字层次上存在着具身模拟, 在部件层次上也存在着具身模拟。义符在汉字加工中期被激活了, 并且持续到加工晚期。整个研究表明, 汉语肢体动作动词理解是一个跨通道的具身模拟过程, 具身模拟在汉语肢体动作动词的理解中起着非常重要的作用。     

Investigating the Constrained Action Hypothesis: A Movement Coordination and Coordination Variability Approach

The purpose of this study was to examine the effects of focus of attention cues on movement coordination and coordination variability in the lower extremity. Twenty participants performed the standing long jump under both internal and external focus of attention conditions. A modified vector coding technique was used to evaluate the influence of attentional focus cues on lower extremity coordination patterns and coordination variability during the jumps. Participants jumped significantly further under an external focus of attention condition compared with an internal focus of attention condition (p = .035, effect size = .29). Focus of attention also influenced coordination between the ankle and knee, F(6, 19) = 2.87, p = .012, effect size = .388, with participants primarily using their knees under the internal focus of attention, and using both their ankles and knees under the external focus of attention. Attentional focus cues did not influence ankle-knee, F(1, 19) = 0.02, p = .98, effect size = .02, or hip-knee, F(1, 19) = 5.00, p = .49, effect size = .16, coordination variability. Results suggest that while attentional focus may not directly influence movement coordination condition, there is still a change in movement strategy resulting in greater jump distances following an external focus of attention.     

有性Penna模型:进化心理学的新工具

进化心理学家以进化论为基础,使用了许多不同的方法来研究人类的心灵。这些方法都有共同的缺陷,即无法直接对提出的假设进行验证,对复杂的系统进行研究难度很大,计算机模拟的方法可在一定程度上修补该问题。有性Penna模型能反映有性生殖种群的进化特点,能反映环境对生物进化的影响,通过该模型来模拟人类进化历程,则可以检验某一心理机制是否是适应的,它是研究生物进化的有力工具。本文在综述已有研究成果的基础上提出用有性Penna模型对进化心理学关于进化轨迹的假设进行验证的构想,并在此基础之上提出了用该模型进行研究的基本框架。     

Enhancing job-site training of supported workers with autism: a reemphasis on simulation

Currently recommended practice in supported work emphasizes training job skills to workers with severe disabilities while on the job. Early behavioral research indicated that skills needed in natural environments could also be trained in simulated settings. We compared job-site plus simulation training for teaching job skills to supported workers with autism to provision of training exclusively on the job. Job-site training occurred in a small publishing company during the regular work routine, and simulation training occurred in an adult education site for people with severe disabilities. Two pairs of workers received training on two job skills; one skill was trained at the job site and the other was trained using job-site plus simulation training. Results indicated that for 3 of the 4 comparisons, job-site plus simulation training resulted in a higher level of skill or more rapid skill acquisition than did job-site-only training. Results suggested that job-site training, the assumed best practice for teaching vocational skills, is likely to be more effective if supplemented with simulation training. Directions for future research include expanding applications of behavioral technologies to other aspects of the current support paradigm.     

On simulating non-normal distributions

Six different algorithms to generate widely different non-normal distributions are reviewed. These algorithms are compared in terms of speed, simplicity and generality of the technique. The advantages and disadvantages of using these algorithms are briefly discussed.The author would like to thank an anonymous referee for his comments and suggestions which lead to the inclusion of the section A Comparative Study.     

RECENT TRENDS IN THE COGNITIVE SCIENCE OF RELIGION: NEUROSCIENCE,RELIGIOUS EXPERIENCE,AND THE CONFLUENCE OF COGNITIVE AND EVOLUTIONARY RESEARCH

Cognitive science of religion (CSR) has increased influence in religious studies, the resistance of religious protectionists notwithstanding. CSR's most provocative work stresses the role of implicit cognition in explaining religious thought and conduct. Exhibiting explanatory pluralism, CSR seeks integrative accounts across the social, psychological, and brain sciences. CSR reflects prominent trends in the cognitive sciences generally. First, CSR is giving greater attention to the new tools and findings of cognitive neuroscience. Second, CSR researchers have done carefully designed, nonlaboratory studies of experience, incorporating precise physiological measures, obtaining astonishing findings about the experiences of ritual participants and observers. Third, CSR theorists have advanced evolutionary hypotheses about religions from eight perspectives (cross-indexing three levels of selection with three mechanisms of selection). Cultural group selectionists headline credibility enhancing displays and Big Gods in the religious consolidation of large-scale societies. Other CSR researchers marshal counterevidence and advance alternative hypotheses. CSR findings are incompatible with the New Atheists’ projects on two fronts.     

Models for ordinal hierarchical classes analysis

This paper proposes an ordinal generalization of the hierarchical classes model originally proposed by De Boeck and Rosenberg (1998). Any hierarchical classes model implies a decomposition of a two-way two-mode binary arrayM into two component matrices, called bundle matrices, which represent the association relation and the set-theoretical relations among the elements of both modes inM. Whereas the original model restricts the bundle matrices to be binary, the ordinal hierarchical classes model assumes that the bundles are ordinal variables with a prespecified number of values. This generalization results in a classification model with classes ordered along ordinal dimensions. The ordinal hierarchical classes model is shown to subsume Coombs and Kao's (1955) model for nonmetric factor analysis. An algorithm is described to fit the model to a given data set and is subsequently evaluated in an extensive simulation study. An application of the model to student housing data is discussed.     

Does Agrammatic Speech Constitute a Regression to Child Language? A Three-Way Comparison between Agrammatic, Child, and Normal Ellipsis

When children are in the process of learning their mother tongue, they show frequent use of nonfinite clauses, even though they produce finite clauses at the same time, thereby demonstrating the availability of the functional domain associated with finiteness. In this study the hypothesis was tested that this behavior results from an overuse of the normal elliptical repertoire that has also been observed in agrammatic aphasia. The purpose of this overuse is prevention of computational overload. In support of the hypothesis it was found that children behaved very similar to aphasics and normal adults with respect to the following parameters: (a) distribution of types of ellipsis, (b) elaboration of ellipses, (c) word order, (d) subject omission, (e) frequency of weak subject pronouns, and (f) verb type (eventivity). The results also support the Jackson/Jakobson regression hypothesis, at least at the grammatical level.     

Learning the form of causal relationships using hierarchical bayesian models

People learn quickly when reasoning about causal relationships, making inferences from limited data and avoiding spurious inferences. Efficient learning depends on abstract knowledge, which is often domain or context specific, and much of it must be learned. While such knowledge effects are well documented, little is known about exactly how we acquire knowledge that constrains learning. This work focuses on knowledge of the functional form of causal relationships; there are many kinds of relationships that can apply between causes and their effects, and knowledge of the form such a relationship takes is important in order to quickly identify the real causes of an observed effect. We developed a hierarchical Bayesian model of the acquisition of knowledge of the functional form of causal relationships and tested it in five experimental studies, considering disjunctive and conjunctive relationships, failure rates, and cross-domain effects. The Bayesian model accurately predicted human judgments and outperformed several alternative models.