Positive mood boosts the expression of a dispositional need for closure

Three studies (N=539) examined the hypothesis that positive mood increases the degree to which epistemic motivation, i.e., the need for closure (NFC), affects the way in which an individual processes information (heuristic vs. systematic processing). In each of the studies, different methods of operationalising mood were used: in Study 1, mood was measured as a state; in Study 2, mood was induced by asking participants to recall emotional events; and in Study 3, mood was induced by emotional pictures. The styles of information processing that were utilised by our participants were operationalised in terms of their preferences for (Study 1) and ability to recall (Studies 2 and 3) schema-consistent and schema-inconsistent information. Taken together, the results of the three studies show that only under positive mood, NFC level of an individual is consistent with his or her style of information processing, that is, only under positive mood is there a negative relationship between the NFC level of an individual and the utilisation of schema-inconsistent information. Our results can be explained in terms of the effect that mood has on an individual's perceived ability to achieve NFC.     

Examining the Latent Structure of Posttraumatic Growth Between Male and Female Survivors in the Immediate Aftermath of a Flash Flood Disaster

The study examined and compared the latent structure of posttraumatic growth (PTG) based on three proposed models: 1-factor, 3-factor and 5-factor models in order to (1) find out the factor structure that has the best fit for the Filipino sample; (2) find out the factor structure that best represents PTG in the immediate aftermath of a flash flood disaster; and (3) examine the generalizability of the best-fitted model across gender. A sample of 895 survivor-respondents answered the Posttraumatic Growth Inventory (PTGI) within a month after a deadly flash flood. Based on the best-fitted model, a multi-group comparison between male and female was conducted to determine gender generalizability. Results showed that the 3-factor model comprising of Changes in Self/Positive Life Attitudes, Philosophy of Life, and Relating to Others fitted best in contrast to the other two models. The data also demonstrated the generalizability of the 3-factor model across gender, with invariance in factor loadings, item intercepts, factor variance and covariance, and factor means.     

Bimodal emotion congruency is critical to preverbal infants’ abstract rule learning

Extracting general rules from specific examples is important, as we must face the same challenge displayed in various formats. Previous studies have found that bimodal presentation of grammar‐like rules (e.g. ABA) enhanced 5‐month‐olds’ capacity to acquire a rule that infants failed to learn when the rule was presented with visual presentation of the shapes alone (circle‐triangle‐circle) or auditory presentation of the syllables (la‐ba‐la) alone. However, the mechanisms and constraints for this bimodal learning facilitation are still unknown. In this study, we used audio‐visual relation congruency between bimodal stimulation to disentangle possible facilitation sources. We exposed 8‐ to 10‐month‐old infants to an AAB sequence consisting of visual faces with affective expressions and/or auditory voices conveying emotions. Our results showed that infants were able to distinguish the learned AAB rule from other novel rules under bimodal stimulation when the affects in audio and visual stimuli were congruently paired (Experiments 1A and 2A). Infants failed to acquire the same rule when audio‐visual stimuli were incongruently matched (Experiment 2B) and when only the visual (Experiment 1B) or the audio (Experiment 1C) stimuli were presented. Our results highlight that bimodal facilitation in infant rule learning is not only dependent on better statistical probability and redundant sensory information, but also the relational congruency of audio‐visual information. A video abstract of this article can be viewed at https://m.youtube.com/watch?v=KYTyjH1k9RQ     

Would You Be Happier If You Looked Better? A Focusing Illusion

Some people might believe that individuals who are more satisfied with their body are also happier. However, people tend to overrate the influence of some factors (e.g. money or health) on their happiness; a phenomenon termed the focusing illusion. Our aim was to examine the focusing illusion in relation to body satisfaction. We experimentally manipulated body satisfaction and life satisfaction focus by varying the order of relevant measurement scales. Volunteers (N = 97) completed two questionnaires placed in separate envelopes to control the order of scales administration. Participants either completed the Body Satisfaction Scale followed by the Satisfaction with Life Scale or vice versa. In line with the focusing illusion the association between body satisfaction and life satisfaction was significantly stronger when participants were asked about their body satisfaction first. Body satisfaction as a focusing illusion may need to be considered by scientist as well as lay people who try to look better and be happier.     

睡眠不足对人际交互的影响及其认知神经机制

睡眠不足会对人的认知、情感和人际交互产生诸多影响。这种影响在社会情绪层面表现为个体情绪共情和认知共情的减少,易激惹性与愤怒情绪的增加;在社会行为层面则表现为亲社会行为的减少和攻击行为的增加。在睡眠不足状态下,情绪系统和认知系统功能连接的减弱可能是这些变化的潜在机制。未来应结合生态效度较高的睡眠操作手段,系统考察睡眠不足如何导致各种高级社会情绪的改变,以及这些社会情绪的变化如何导致社会行为的变化。     

自我损耗、情绪动机对冲动决策的影响

以大学生为被试,探讨自我损耗、情绪动机对冲动决策的影响。采用2×2×2的混合实验设计,组内变量为自我损耗,组间变量为情绪动机方向和强度,使用双任务范式操作自我损耗,使用情绪动机图片启动被试的情绪动机,使用延迟折扣任务的指标k值测量冲动决策。结果发现,高趋近动机的k值大于低趋近动机,高回避动机的k值大于低回避动机。结果表明,自我损耗、情绪动机对冲动决策有明显影响。     

How Do Artificial Neural Networks Classify Musical Triads? A Case Study in Eluding Bonini's Paradox

How might artificial neural networks (ANNs) inform cognitive science? Often cognitive scientists use ANNs but do not examine their internal structures. In this paper, we use ANNs to explore how cognition might represent musical properties. We train ANNs to classify musical chords, and we interpret network structure to determine what representations ANNs discover and use. We find connection weights between input units and hidden units can be described using Fourier phase spaces, a representation studied in musical set theory. We find the total signal coming through these weighted connection weights is a measure of the similarity between two Fourier structures: the structure of the hidden unit's weights and the structure of the stimulus. This is surprising because neither of these Fourier structures is computed by the hidden unit. We then show how output units use such similarity measures to classify chords. However, we also find different types of units—units that use different activation functions—use this similarity measure very differently. This result, combined with other findings, indicates that while our networks are related to the Fourier analysis of musical sets, they do not perform Fourier analyses of the kind usually described in musical set theory. Our results show Fourier representations of music are not limited to musical set theory. Our results also suggest how cognitive psychologists might explore Fourier representations in musical cognition. Critically, such theoretical and empirical implications require researchers to understand how network structure converts stimuli into responses.     

An empirical Q-matrix validation method for the sequential generalized DINA model

As a core component of most cognitive diagnosis models, the Q-matrix, or item and attribute association matrix, is typically developed by domain experts, and tends to be subjective. It is critical to validate the Q-matrix empirically because a misspecified Q-matrix could result in erroneous attribute estimation. Most existing Q-matrix validation procedures are developed for dichotomous responses. However, in this paper, we propose a method to empirically detect and correct the misspecifications in the Q-matrix for graded response data based on the sequential generalized deterministic inputs, noisy ‘and’ gate (G-DINA) model. The proposed Q-matrix validation procedure is implemented in a stepwise manner based on the Wald test and an effect size measure. The feasibility of the proposed method is examined using simulation studies. Also, a set of data from the Trends in International Mathematics and Science Study (TIMSS) 2011 mathematics assessment is analysed for illustration.