Quantifying the psychopathic stare: Automated assessment of head motion is related to antisocial traits in forensic interviews

Clinicians have long noted that individuals with high psychopathic traits exhibit unique interpersonal style often observable during forensic interviews. Here we develop an automated approach for quantifying head dynamics during video-recorded naturalistic clinical interviews. We expected head dynamics would be related to psychopathic traits. As predicted, dwell times indicate that those with higher levels of psychopathic traits are characterized by more stationary head positions, focused directly towards the camera/interviewer, than were individuals low in psychopathic traits. These associations were primarily driven by developmental/antisocial features of psychopathy, indicating that those with severe and life-course persistent antisocial behavior exhibit more rigid and focused orienting of their head during interpersonal communication. These results encourage more research into the automated quantification of behavioral manifestations of personality to support clinical observations that psychopaths exhibit unique qualities in non-verbal interpersonal communication.     

Prior sleep timing and visual recognition of emotional faces in 6-month-old infants

Face recognition is an important mnemonic ability for infants when navigating the social world. While age-related changes in face processing abilities are relatively well documented, less is known about short-term intra-individual fluctuations in this ability. Given that sleep deprivation in adults leads to impairments in information processing, we assessed the role of prior sleep on 6-month-old infants’ (N = 17) visual recognition of faces showing three emotional expressions (neutral, sad, angry). Visual recognition was inferred by assessing novelty preferences for unfamiliar relative to familiarized faces in a visual recognition memory paradigm. In a within-subject design, infants participated once after they had recently woken up from a nap (nap condition) and once after they had been awake for an extended period of time (awake condition). Infants failed to show visual recognition for the neutral faces in either condition. Infants showed recognition for the sad and angry faces when tested in the awake condition, but not in the nap condition. This suggests that timing of prior sleep shapes how effectively infants process emotionally relevant information in their environment.     

Going virtual in the early years: 30-month-old toddlers recognize commonly used emojis

People nowadays do not only display facial expressions in face to face communication but also in on-line communication using graphical symbols named emojis. The present study explored 30-month-old toddlers’ ability to recognize emojis that represented six basic human emotions. In the study, 38 toddlers first saw scenarios that elicited different emotions in an actor and were asked to visually identify the matching emoji in the presence of a distractor. Eye-tracking results showed that toddlers could correctly identify the emoji that represented the emotion in each scenario. Toddlers then heard different emotion words and were again found to be able to identify the matching emoji. These findings provide preliminary evidence that the ability to recognize and understand the emotional value of emotion symbols in the virtual world emerges early in development.     

Producing and recognizing words with two pronunciation variants: Evidence from novel schwa words

This study examined the lexical representations and psycholinguistic mechanisms underlying the production and recognition of novel words with two pronunciation variants in French. Participants first learned novel schwa words (e.g., /??nyk/), which varied in their alternating status (i.e., whether these words were learned with one or two variants) and, for alternating words, in the frequency of their variants. They were then tested in picture-naming (free or induced) and recognition memory tasks (i.e., deciding whether spoken items were learned during the experiment or not). Results for free naming show an influence of variant frequency on responses, more frequent variants being produced more often. Moreover, our data show an effect of the alternating status of the novel words on naming latencies, with longer latencies for alternating than for nonalternating novel words. These induced naming results suggest that both variants are stored as lexical entries and compete during the lexeme selection process. Results for recognition show an effect of variant frequency on reaction times and no effect of variant type (i.e., schwa versus reduced variant). Taken together, our findings suggest that participants both comprehend and produce novel French schwa words using two lexical representations, one for each variant.     

A quick eye to anger: An investigation of a differential effect of facial features in detecting angry and happy expressions

Detection of angry and happy faces is generally found to be easier and faster than that of faces expressing emotions other than anger or happiness. This can be explained by the threatening account and the feature account. Few empirical studies have explored the interaction between these two accounts which are seemingly, but not necessarily, mutually exclusive. The present studies hypothesised that prominent facial features are important in facilitating the detection process of both angry and happy expressions; yet the detection of happy faces was more facilitated by the prominent features than angry faces. Results confirmed the hypotheses and indicated that participants reacted faster to the emotional expressions with prominent features (in Study 1) and the detection of happy faces was more facilitated by the prominent feature than angry faces (in Study 2). The findings are compatible with evolutionary speculation which suggests that the angry expression is an alarming signal of potential threats to survival. Compared to the angry faces, the happy faces need more salient physical features to obtain a similar level of processing efficiency.     

Friends in Low-Entropy Places: Orthographic Neighbor Effects on Visual Word Identification Differ Across Letter Positions

Visual word recognition is facilitated by the presence of orthographic neighbors that mismatch the target word by a single letter substitution. However, researchers typically do not consider where neighbors mismatch the target. In light of evidence that some letter positions are more informative than others, we investigate whether the influence of orthographic neighbors differs across letter positions. To do so, we quantify the number of enemies at each letter position (how many neighbors mismatch the target word at that position). Analyses of reaction time data from a visual word naming task indicate that the influence of enemies differs across letter positions, with the negative impacts of enemies being most pronounced at letter positions where readers have low prior uncertainty about which letters they will encounter (i.e., positions with low entropy). To understand the computational mechanisms that give rise to such positional entropy effects, we introduce a new computational model, VOISeR (Visual Orthographic Input Serial Reader), which receives orthographic inputs in parallel and produces an over-time sequence of phonemes as output. VOISeR produces a similar pattern of results as in the human data, suggesting that positional entropy effects may emerge even when letters are not sampled serially. Finally, we demonstrate that these effects also emerge in human subjects' data from a lexical decision task, illustrating the generalizability of positional entropy effects across visual word recognition paradigms. Taken together, such work suggests that research into orthographic neighbor effects in visual word recognition should also consider differences between letter positions.     

“Do I Know You?” Altering hairstyle affects facial recognition

Background: Research has demonstrated that both internal features (e.g., eyes) and external features (e.g., hair) are important for recognizing unfamiliar faces; however, the impact of altering hairstyle on the recognition of unfamiliar faces has yet to be isolated and investigated in the absence of deep processing. Objectives: We sought to examine the extent to which altering hair impacts the recognition of a previously viewed face. Methods: Participants were presented with a series of face images followed by a recognition probe of either a new face or a face that was among the previously presented images with either the same hairstyle (identical face) or a different hairstyle (disguised face). Results: Participants showed significantly less accuracy in the disguised condition compared to the identical condition. Conclusions: Our results provide evidence that hairstyle plays a role in recognizing unfamiliar faces. This appears to hold true across race and sex, as well as across deep and shallow processing.     

Bidirectional feature selection with global and local structure preservation for small size samples

Collecting samples is a challenging task for face recognition, especially for some real-world applications such as law enhancement and ID card identification, where there is usually single sample per person (SSPS) used to train a face recognition system. To extract discriminative features from the small size samples, in this paper we propose virtual samples via bidirectional feature selection with global and local structure preservation (VS-BFS-GL) to augment the number of training samples. In VS-BFS-GL, bidirectional feature selection is developed, which introduces L_2,1 norm to explore the face variations from both horizontal and vertical directions. Further, to include more variations in the virtual images, the global structure information and sample-specified local structure information of the SSPP training set are considered. By integrating bidirectional feature selection, global and local structure, the limited training samples are fully utilized and more knowledge are mined. To further improve the effectiveness of VS-BFS-GL, an auxiliary database containing different face variations can be used to explore the local structure information. We extensively evaluated the proposed approach on AR and FERET database. The promising recognition results demonstrate that VS-BFS-GL is robust to expression, pose and partial occlusion variations in the faces.