The priming effect of emotional words on body expressions: Two ERP studies.

The impact of emotional words on the recognition of body expression and the underlying neurodynamic mechanisms remain poorly understood. This study used a classic supraliminal priming paradigm and event related potential (ERP) to investigate the effect of emotion-label words (experiment 1) and emotional verbs (experiment 2) on the recognition of body expressions. The behavioral results revealed that individuals exhibited a higher accuracy in recognizing happy expressions when presented with a happy-label word condition, in contrast to neutral expressions. Furthermore, it was observed that the accuracy of recognizing happy body expressions was reduced when preceded by angry verb priming, compared to happy and neutral priming conditions. Conversely, the accuracy of recognizing angry body expressions was higher in response to angry verb priming than happy and neutral primings. The ERP results showed that, in the recognition of happy body expressions, the P300 amplitude elicited by angry-label words was more positive, while a congruent verb-expression condition elicited more positive P300 amplitude than an incongruent condition in the left hemisphere and midline. However, in the recognition of angry body expressions, the N400 amplitude elicited by a congruent verb-expression condition was smaller than that elicited by an incongruent condition. These results suggest that both abstract emotion-label words and specific emotional verbs influence the recognition of body expressions. In addition, integrating happy semantic context and body expression might occur at the P300 stage, whereas integrating angry semantic context and body expression might occur at the N400 stage. These findings present novel evidence regarding the criticality of emotional context in the recognition of emotions.

Construction and validation of the Dalian emotional movement open-source set (DEMOS).

Human body movements are important for emotion recognition and social communication and have received extensive attention from researchers. In this field, emotional biological motion stimuli, as depicted by point-light displays, are widely used. However, the number of stimuli in the existing material library is small, and there is a lack of standardized indicators, which subsequently limits experimental design and conduction. Therefore, based on our prior kinematic dataset, we constructed the Dalian Emotional Movement Open-source Set (DEMOS) using computational modeling. The DEMOS has three views (i.e., frontal 0°, left 45°, and left 90°) and in total comprises 2664 high-quality videos of emotional biological motion, each displaying happiness, sadness, anger, fear, disgust, and neutral. All stimuli were validated in terms of recognition accuracy, emotional intensity, and subjective movement. The objective movement for each expression was also calculated. The DEMOS can be downloaded for free from https://osf.io/83fst/ . To our knowledge, this is the largest multi-view emotional biological motion set based on the whole body. The DEMOS can be applied in many fields, including affective computing, social cognition, and psychiatry.

Body-Posture Recognition by Undergraduate Students Majoring in Physical Education and Other Disciplines.

Humans are more proficient at processing visual display of body posture when the body is in upright orientation, compared to when inverted (inversion effect). Here we investigated whether extensive exposure or expertise on body posture recognition would affect the efficiency with which body-posture is processed. Using whole-body and piecemeal-body postures as stimuli, we performed two experiments to investigate whether body-posture recognition differed between two groups of participants: undergraduates majoring in physical education (PE) and those in other subjects (non-PE), respectively. These two groups differed significantly in the frequency and intensity of exercise per day and/or accumulated exercise time. In our experiments, following initial presentation of an image of a body posture, participants were shown the same or a different stimulus and were asked to report whether or not they had been previously shown the same image. The orientations of the body postures were also varied between trials. Our results showed that, in Experiment 1, for whole-body posture recognition, both the PE and non-PE groups showed a robust body-inversion effect in terms of both error rate and reaction time (RT), but the magnitude of the body-inversion effect in the RT measure was greater in the PE than the non-PE group. In Experiment 2, for piecemeal-body postures, both groups showed the inversion effect in terms of both error rate and RT measures and the PE group made fewer overall errors than the non-PE group. These cumulative results suggest that a superiority effect exists for PE participants compared with non-PE participants. Our results are generally consistent with the expertise hypothesis.

Kinematic dataset of actors expressing emotions.

Human body movements can convey a variety of emotions and even create advantages in some special life situations. However, how emotion is encoded in body movements has remained unclear. One reason is that there is a lack of public human body kinematic dataset regarding the expressing of various emotions. Therefore, we aimed to produce a comprehensive dataset to assist in recognizing cues from all parts of the body that indicate six basic emotions (happiness, sadness, anger, fear, disgust, surprise) and neutral expression. The present dataset was created using a portable wireless motion capture system. Twenty-two semi-professional actors (half male) completed performances according to the standardized guidance and preferred daily events. A total of 1402 recordings at 125 Hz were collected, consisting of the position and rotation data of 72 anatomical nodes. To our knowledge, this is now the largest emotional kinematic dataset of the human body. We hope this dataset will contribute to multiple fields of research and practice, including social neuroscience, psychiatry, computer vision, and biometric and information forensics.

Attention Capture of Non-target Emotional Faces: An Evidence From Reward Learning.

The aim of this study was to explore whether reward learning would affect the processing of targets when an emotional stimulus was task irrelevant. In the current study, using a visual search paradigm to establish an association between emotional faces and reward, an emotional face appeared as a task-irrelevant distractor during the test after reward learning, and participants were asked to judge the orientation of a line on the face. In experiment 1, no significant difference was found between the high reward-fear distractor condition and the no reward-neutral condition, but the response times of the high reward-fear condition were significantly longer than those of the low reward-happy condition. In experiment 2, there was no significant difference in participants' performance between high reward-happy and no reward-neutral responses. In addition, response times of the low reward-fear condition wear significantly longer than those of the high reward-happy and no reward-neutral conditions. The results show that reward learning affects attention bias of task-irrelevant emotional faces even when reward is absent. Moreover, the high reward selection history is more effective in weakening the emotional advantage of the processing advantage than the low reward.