Checking ID‐cards for the sale of restricted goods: Age decisions bias face decisions

Matching unfamiliar faces is highly error‐prone, and most studies highlight the implications for real‐world ID‐checking. Here we study a particular instance of ID‐checking: proof of age for buying restricted goods such as alcohol. In this case, checkers must establish that an identity document is carried by its legitimate owner (i.e., that the ID photo matches the face of the bearer) and that the ID proves the bearer to be old enough to make the purchase. Across three experiments, using two common forms of photo‐ID (i.e., driving licenses, PASS+ cards) we show that observers produce very high error rates when age requirements are met, but faces mismatch. This bias away from detecting a face mismatch remained evident in experienced cashiers—though to a somewhat attenuated level. We discuss interactions between face matching and other tasks, and the practical consequences of a bias which favours those using photo‐ID with fraudulent intent.     

Investigating sex,masculinity and femininity in relation to impulsive driving and driving anger expression

Human factors constitute a class of prominent road safety related factors. In the present study, human factors of driving were studied by investigating sex differences and gender roles in relation to impulsive driving and driving anger expression. A total of 425 drivers between the ages of 18 and 56 (M = 25.46, SD = 7.58) participated to the study and completed a series of questionnaires including a demographic information form, the Bem Sex Roles Inventory, the Impulsive Driver Behaviour Scale and the Driving Anger Expression Inventory. According to the ANCOVA results, male drivers showed higher functional impulsivity, lack of premeditation and use of the vehicle to express anger than female drivers. Additionally, hierarchical regression analyses showed that masculinity was positively associated with functional impulsivity, urgency and the dimensions of aggressive anger expression. However, femininity was positively associated with functional impulsivity and adaptive/constructive anger expression, but negatively associated with the dimensions of dysfunctional impulsivity and aggressive anger expression. Overall, the results showed the significant solo effects of masculinity and femininity on impulsive driver behaviours and driving anger expression, over and above the effects of sex, and the interaction between sex and gender roles. In the present study, previously reported findings indicating the relationships between sex and gender roles and driving anger expression were supported and extended by providing the literature with the contribution of answering the question how sex and gender roles are related to impulsive driver behaviours. The findings of the two related concepts of impulsive driving and driving anger expression were discussed in light of the current literature. Contributions, implications and future research directions concerning road safety practices were presented.     

An expanded model for perceptual visual single object recognition system using expectation priming following neuroscientific evidence

Under numerous circumstances, humans recognize visual objects in their environment with remarkable response times and accuracy. Existing artificial visual object recognition systems have not yet surpassed human vision, especially in its universality of application. We argue that modeling the recognition process in an exclusive feedforward manner hinders those systems’ performance. To bridge that performance gap between them and human vision, we present a brief review of neuroscientific data, which suggests that considering an agent’s internal influences (from cognitive systems that peripherally interact with visual-perceptual processes) recognition can be improved. Then, we propose a model for visual object recognition which uses these systems’ information, such as affection, for generating expectation to prime the object recognition system, thus reducing its execution times. Later, an implementation of the model is described. Finally, we present and discuss an experiment and its results.     

词汇共现频率视角下语义联想效应及其神经机制

词汇识别与记忆受到词汇之间语义联想关系的影响。鉴于自由联想方法建立词汇语义联想关系的局限性, 研究者们提出用共现联想法建立词汇之间的语义联想关系。本文对词汇共现频率视角下的语义联想效应及其神经机制的研究进行分析发现, 语义联想的丰富程度和关联程度影响词汇的加工; 与少语义联想词相比, 多语义联想词导致P200波幅增大和N400波幅减小; 语义联想加工涉及的脑区主要是额上回和左内侧颞叶区域。未来研究需要探讨自由联想法和共现联想法建立语义联想关系的差异, 基于共现联想法进一步地探究语义联想的行为规律和神经机制, 并从共现联想的角度开展汉语语义联想效应及神经机制的研究。     

Understanding the role of configural processing in face emotion recognition in Parkinson’s disease

This investigation examined whether impairment in configural processing could explain deficits in face emotion recognition in people with Parkinson’s disease (PD). Stimuli from the Radboud Faces Database were used to compare recognition of four negative emotion expressions by older adults with PD (n = 16) and matched controls (n = 17). Participants were tasked with categorizing emotional expressions from upright and inverted whole faces and facial composites; it is difficult to derive configural information from these two types of stimuli so featural processing should play a larger than usual role in accurate recognition of emotional expressions. We found that the PD group were impaired relative to controls in recognizing anger, disgust and fearful expressions in upright faces. Then, consistent with a configural processing deficit, participants with PD showed no composite effect when attempting to identify facial expressions of anger, disgust and fear. A face inversion effect, however, was observed in the performance of all participants in both the whole faces and facial composites tasks. These findings can be explained in terms of a configural processing deficit if it is assumed that the disruption caused by facial composites was specific to configural processing, whereas inversion reduced performance by making it difficult to derive both featural and configural information from faces.     

Recognizing images: The role of motivational significance,complexity, social content,age, and gender

Memory for affective events plays an important role in determining people’s behavior and well-being. Its determinants are far from being completely understood. We investigated how recognition memory for affective pictures depends on pictures’ motivational significance (valence and arousal), complexity (figure-ground compositions vs. scenes), and social content (pictures with people vs. without people) and on observers’ age and gender. Younger, middle-aged, and older adults viewed 84 pictures depicting real-life situations. After a break, the participants viewed 72 pictures, half of which had been viewed previously and half of which were novel, and were asked to endorse whether each picture was novel or had been presented previously. Hits, false alarms, and overall performance (discrimination accuracy) were our dependent variables. The main findings were that, across participants, recognition memory was better for unpleasant than pleasant pictures and for pictures depicting people than pictures without people. Low-arousal pictures were more accurately recognized than high-arousal pictures, and this effect was significantly larger among middle-aged and older adults than younger adults. Recognition memory worsened across adulthood, and this decline was steeper among men than women. Middle-aged and older women outperformed their male counterparts. This study suggests that how well we are able to successfully discriminate previously seen pictorial stimuli from novel stimuli depends on several pictures’ properties related to their motivational significance and content, and on observer’s age and gender.     

EARSHOT: A Minimal Neural Network Model of Incremental Human Speech Recognition

Despite the lack of invariance problem (the many-to-many mapping between acoustics and percepts), human listeners experience phonetic constancy and typically perceive what a speaker intends. Most models of human speech recognition (HSR) have side-stepped this problem, working with abstract, idealized inputs and deferring the challenge of working with real speech. In contrast, carefully engineered deep learning networks allow robust, real-world automatic speech recognition (ASR). However, the complexities of deep learning architectures and training regimens make it difficult to use them to provide direct insights into mechanisms that may support HSR. In this brief article, we report preliminary results from a two-layer network that borrows one element from ASR, long short-term memory nodes, which provide dynamic memory for a range of temporal spans. This allows the model to learn to map real speech from multiple talkers to semantic targets with high accuracy, with human-like timecourse of lexical access and phonological competition. Internal representations emerge that resemble phonetically organized responses in human superior temporal gyrus, suggesting that the model develops a distributed phonological code despite no explicit training on phonetic or phonemic targets. The ability to work with real speech is a major advance for cognitive models of HSR.     

Individual differences in visual acuity and face matching ability

The visual acuity of the eyes varies outside the range of normal vision, requiring corrective lenses, but also within the normal range. This study investigated whether both types of variation relate to individual differences in face-identity matching, considering this applied task requires perception of detail. Across two experiments, face-matching accuracy correlated with variation in acuity when this fell outside the normal range of vision and was uncorrected with glasses or contact lenses. In contrast, variation in visual acuity within the normal range did not affect face-matching accuracy, whereas matching accuracy at a given level of acuity could vary substantially. These results indicate that visual acuity is only a problem for occupations performing face-identity matching when below-normal acuity is not diagnosed or adequately corrected. In turn, these findings suggest that variation in acuity within the normal range is not a contributing factor to individual differences in face matching accuracy.     

‘Personality in Its Natural Habitat’ Revisited: A Pooled,Multi-sample Examination of the Relationships Between the Big Five Personality Traits and Daily Behaviour and Language Use

Past research using the Electronically Activated Recorder (EAR), an observational ambulatory assessment method for the real-world measurement of daily behaviour, has identified several behavioural manifestations of the Big Five domains in a small college sample (N = 96). With the use of a larger and more diverse sample of pooled data from N = 462 participants from a total of four community samples who wore the EAR from 2 to 6 days, the primary purpose of the present study was to obtain more precise and generalizable effect estimates of the Big Five–behaviour relationships and to re-examine the degree to which these relationships are gender specific. In an extension of the original article, the secondary purpose of the present study was to examine if the Big Five–behaviour relationships differed across two facets of each Big Five domain. Overall, while several of the behavioural manifestations of the Big Five were generally consistent with the trait definitions (replicating some findings from the original article), we found little evidence of gender differences (not replicating a basic finding from the original article). Unique to the present study, the Big Five–behaviour relationships were not always comparable across the two facets of each Big Five domain. © 2020 European Association of Personality Psychology     

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。