Attachment insecurity and strategies for regulation: when emotion triggers attention

Attachment-related strategies are thought to be critical for regulation and processing of emotional information. This study examined biases in selective attention to emotional stimuli as a function of insecure attachment. Participants searched for a single target image preceded by to-be-ignored distracters depicting emotional images varying in valence and arousal. Results revealed that, in general, negative distracters affected accuracy levels, and that the anxious attached participants showed a clear interference of the emotional distracters. In contrast, the avoidant group evinced a higher control on such interference. In addition, arousal ratings to distracter images indicated superior emotional activation only for anxious attached participants. Consistent with the evolutionary-based attachment theory threat-related stimuli prompted priority attentional responses. Present findings are in line with evidence showing the deployment of distinct strategies in insecurely attached individuals for the regulation of attention to emotional information.     

Distinct Facial Characteristics Differentiate Communicative Intent of Infant‐Directed Speech

Adults and infants can differentiate communicative messages using the nonlinguistic acoustic properties of infant‐directed (ID) speech. Although the distinct prosodic properties of ID speech have been explored extensively, it is currently unknown whether the visual properties of the face during ID speech similarly convey communicative intent and thus represent an additional source of social information for infants during early interactions. To examine whether the dynamic facial movement associated with ID speech confers affective information independent of the acoustic signal, adults' differentiation of the visual properties of speakers' communicative messages was examined in two experiments in which the adults rated silent videos of approving and comforting ID and neutral adult‐directed speech. In Experiment 1, adults differentiated the facial speech groups on ratings of the intended recipient and the speaker's message. In Experiment 2, an original coding scale identified facial characteristics of the speakers. Discriminant correspondence analysis revealed two factors differentiating the facial speech groups on various characteristics. Implications for perception of ID facial movements in relation to speakers' communicative intent are discussed for both typically and atypically developing infants. Copyright © 2012 John Wiley & Sons, Ltd.     

Can We Identify Emotion Over‐regulation in Infancy? Associations with Avoidant Attachment,Dyadic Emotional Interaction and Temperament

Emotion over‐regulation in infancy has seldom been the focus of empirical research. This study analysed the specificities of over‐regulation when compared with under‐regulation (maladaptive) and adaptive regulation by testing its association with attachment, dyadic emotional interaction, and temperament. The sample consisted of 52 low‐risk mother–infant dyads. During a home visit, dyadic emotional interaction was assessed in the daily routines and free play of 10‐month‐old infants. The infant's emotion regulation was assessed using the Shape Sorter Task, and a temperament questionnaire was completed by the mother. Attachment was assessed at 12 or 16 months using the Strange Situation. As hypothesized, (i) emotion over‐regulation (versus adaptive regulation) was predicted by a lower quality of dyadic emotional interaction and marginally by avoidant attachment; (ii) over‐regulation (versus under‐regulation) was predicted by avoidant attachment; and (iii) the predictive role of avoidant attachment was substantiated after controlling for another measure of mother–infant interaction. Contrary to expectations, temperament did not distinguish between emotion regulation styles. The link between over‐regulation and lower quality of mother–infant emotional interaction and avoidant attachment was demonstrated. There is empirical support to the claim that it is possible to identify emotion over‐regulation in infancy and that it is a maladaptive style of emotion regulation. Copyright © 2012 John Wiley & Sons, Ltd.     

Can you eat it? A link between categorization difficulty and food likability

In the present study we examined whether categorization difficulty regarding a food is related to its likability. For this purpose, we produced stimulus images by morphing photographs of a tomato and a strawberry. Subjects categorized these images as either a tomato or a strawberry and in separate sessions evaluated the food's eatability or the subject's willingness to eat (Experiments 1 and 2) and the likeliness of existence of each food (Experiment 2). The lowest score for ca- tegorization confidence coincided with the lowest scores for eatability, willingness to eat, and likeliness of existence. In Experiment 3, we found that food neophobia, a trait of ingestion avoidance of novel foods, modulated food likability but not categorization confidence. These findings suggest that a high categorization difficulty generally co-occurs with a decrease in food likability and that food neophobia modulates likability. This avoidance of difficult-to-categorize foods seems ecologically valid because before eating we have little information regarding whether a food is potentially harmful.     

Generation of referring expressions: assessing the Incremental Algorithm

A substantial amount of recent work in natural language generation has focused on the generation of 'one-shot' referring expressions whose only aim is to identify a target referent. Dale and Reiter's Incremental Algorithm (IA) is often thought to be the best algorithm for maximizing the similarity to referring expressions produced by people. We test this hypothesis by eliciting referring expressions from human subjects and computing the similarity between the expressions elicited and the ones generated by algorithms. It turns out that the success of the IA depends substantially on the 'preference order' (PO) employed by the IA, particularly in complex domains. While some POs cause the IA to produce referring expressions that are very similar to expressions produced by human subjects, others cause the IA to perform worse than its main competitors; moreover, it turns out to be difficult to predict the success of a PO on the basis of existing psycholinguistic findings or frequencies in corpora. We also examine the computational complexity of the algorithms in question and argue that there are no compelling reasons for preferring the IA over some of its main competitors on these grounds. We conclude that future research on the generation of referring expressions should explore alternatives to the IA, focusing on algorithms, inspired by the Greedy Algorithm, which do not work with a fixed PO.     

Japanese and British Children's Understanding of the Social Function of Pretend Crying

The purpose of this study was to investigate cross-cultural differences in children's understanding of pretend crying. Five- and 6-year-olds from Japan and the United Kingdom (N = 71) heard two hypothetical stories in which the protagonist of each story pretended to cry in front of another person. Children were asked about the appearance–reality distinction of pretend crying, the other character's thoughts and behavior, and the children's own moral judgment of pretend crying. Cultural differences were found in their understanding of the social function of pretend crying. Japanese children judged that pretend crying elicited another's concern and prosocial behavior more than British children. There were no significant differences in appearance–reality distinction or moral judgments between Japanese and British children. All participants successfully discriminated between pretend crying and real crying, and most participants judged pretend crying as “not good” behavior. These results suggested that Japanese children might be more expected to be sensitive to others’ feelings, and that such cultural differences in communication and socialization lead to different patterns in expectations of the social consequences of pretend crying.     

不同情绪载体的神经活动及其异同——脑成像研究的ALE元分析

情绪识别一直是学界关注的热点。虽然已有研究探讨了动态面孔表情、动态身体表情和声音情绪的脑机制, 但对每种情绪载体的整体认识相对不完善, 同时对不同情绪载体之间神经机制的共性和区别知之甚少。因此, 本研究首先通过三项独立的激活似然估计元分析来识别每种情绪模式的大脑激活区域, 然后进行对比分析以评估三种情绪载体之间共同的和独特的神经活动。结果显示, 动态面孔表情的大脑活动包括广泛的额叶、枕叶、颞叶和部分顶叶皮层以及海马、小脑、丘脑、杏仁核等皮层下区域; 动态身体表情的激活集中于颞/枕叶相关脑区以及小脑和海马; 声音情绪则引起了颞叶、额叶、杏仁核、尾状核和脑岛的激活。联合分析表明, 三种情绪载体跨模态激活了左侧颞中回和右侧颞上回。对比分析的结果证明了视觉刺激比听觉刺激更占优势, 动态面孔表情尤为突出, 同时动态身体表情也发挥着重要作用, 但声音情绪有其独特性。总之, 这些发现验证和拓展了三种情绪载体的现有神经模型, 揭示了情绪处理中心的、普遍性的区域, 但每种情绪载体又有自己可靠的特异性神经回路。     

An intelligent facial expression recognition system with emotion intensity classification

Facial expressions play a crucial role in emotion recognition as compared to other modalities. In this work, an integrated network, which is capable of recognizing emotion intensity levels from facial images in real time using deep learning technique is proposed. The cognitive study of facial expressions based on expression intensity levels are useful in applications such as healthcare, coboting, Industry 4.0 etc. This work proposes to augment emotion recognition with 2 other important parameters, valence and emotion intensity. This helps in better automated responses by a machine to an emotion. The valence model helps in classifying emotion as positive and negative emotions and discrete model classifies emotions as happy, anger, disgust, surprise and neutral state using Convolution Neural Network (CNN). Feature extraction and classification are carried out using CMU Multi-PIE database. The proposed architecture achieves 99.1% and 99.11% accuracy for valence model and discrete model respectively for offline image data with 5-fold cross validation. The average accuracy achieved in real time for valance model and discrete model is 95% & 95.6% respectively. Also, this work contributes to build a new database using facial landmarks, with three intensity levels of facial expressions which helps to classify expressions into low, mild and high intensities. The performance is also tested for different classifiers. The proposed integrated system is configured for real time Human Robot Interaction (HRI) applications on a test bed consisting of Raspberry Pi and RPA platform to assess its performance.     

负性情绪对不同语义、空间关系联结记忆的影响

以负性项目-中性场景以及中性项目-中性场景组成的图片对为材料,通过操控项目-场景之间的语义联系和空间距离,考察了负性情绪对不同语义、空间关系联结记忆的影响。结果显示,当项目-场景空间距离较近时,无论项目-场景之间的语义是否相关,负性情绪始终不会影响项目-场景联结记忆;当项目-场景空间距离较远且语义不相关时,负性情绪会削弱项目-场景联结记忆;而当项目-场景空间距离较远且语义相关时,负性情绪会促进项目-场景联结记忆。结果表明,负性情绪对项目-场景联结记忆的影响会受到项目与场景之间语义关系和空间关系的调节,且语义关系在项目-场景空间距离较远时的作用更为突出。     

基本情绪的神经基础：来自fMRI与机器视觉技术研究的证据

基本情绪理论(basic emotion theory)是情绪科学领域最具代表性的理论, 该理论认为人类情绪是由有限的几种基本情绪组成的, 如恐惧、愤怒、喜悦、悲伤等。基本情绪是为了完成基本生命任务(fundamental life task)进化而来的, 每一种基本情绪都有独特的神经结构和生理基础。尽管基本情绪理论被广泛接受, 但是对于基本情绪的种类却莫衷一是。近几十年来, 许多fMRI研究试图确定各种基本情绪的独特神经结构基础, 而且取得了许多重要发现, 比如厌恶和脑岛有关, 悲伤和前扣带回有关, 杏仁核是与恐惧有关的重要边缘结构等。但是, 最近有人进行了元分析研究, 发现许多基本情绪存在混淆的大脑区域, 因此对基本情绪的特定脑区理论提出质疑, 甚至否定基本情绪理论。通过对基本情绪及其神经基础的探讨, 以及对基本情绪理论的最新功能性磁共振成像研究进行梳理分析, 提出有关基本情绪理论的争论来源于基本情绪种类的确定, 因为许多所谓的不同基本情绪实际上是同一种基本情绪, 提出人类可能只有3种基本情绪。未来研究可以利用机器视觉技术进一步推动基本情绪脑影像研究。