Background: Previous studies have suggested increased sensitivity for emotional facial expressions and subtle impairments in emotion recognition from facial expressions in borderline personality disorder (BPD). It has been proposed that facial mimicry contributes to emotion recognition of and emotional response to facial expressions. This study investigated whether BPD patients differ in facial reactions, emotion recognition and their subjective emotional response to faces showing different emotional expressions.
Method: Twenty-eight female BPD patients and 28 healthy controls underwent a facial recognition task with dynamic facial pictures while facial muscle activity (occipitofrontalis, corrugator supercilii, levator labii superioris, zygomaticus major and orbicularis oculi) was recorded. Furthermore, participants rated the emotional intensity of the presented faces and the intensity of their subjective feeling of this emotion.
Results: Compared to controls, BPD patients showed enhanced responses of the corrugator supercilii muscle in response to angry, sad and disgusted facial expressions, and attenuated responses of the levator labii superioris in response to happy and surprised faces. There were no overall group differences regarding emotion recognition performance or intensity ratings.
Conclusion: These results do not support the view that facial recognition in BPD is impaired or that there is a general hypersensitivity to the emotional state of others. Instead, they suggest a negativity bias in BPD, expressed by reduced facial responding to positive social signals and increased facial responding to negative social signals. This is a pattern of facial reactions that might contribute to the difficulties in social interactions frequently reported by patients with this disorder.
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http://dx.doi.org/10.1159/000351122 | DOI Listing |
Neural Netw
December 2024
The school of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China. Electronic address:
Emotion recognition via electroencephalogram (EEG) signals holds significant promise across various domains, including the detection of emotions in patients with consciousness disorders, assisting in the diagnosis of depression, and assessing cognitive load. This process is critically important in the development and research of brain-computer interfaces, where precise and efficient recognition of emotions is paramount. In this work, we introduce a novel approach for emotion recognition employing multi-scale EEG features, denominated as the Dynamic Spatial-Spectral-Temporal Network (DSSTNet).
View Article and Find Full Text PDFFront Hum Neurosci
December 2024
School of Computer Sciences, Universiti Sains Malaysia, Penang, Malaysia.
Emotion recognition is a critical research topic within affective computing, with potential applications across various domains. Currently, EEG-based emotion recognition, utilizing deep learning frameworks, has been effectively applied and achieved commendable performance. However, existing deep learning-based models face challenges in capturing both the spatial activity features and spatial topology features of EEG signals simultaneously.
View Article and Find Full Text PDFFront Neurosci
December 2024
Department of Military Medical Psychology, Fourth Military Medical University, Xi'an, China.
Background: This study aimed to explore the neural mechanisms underlying gender differences in recognizing emotional expressions conveyed through body language. Utilizing electroencephalogram (EEG) recordings, we examined the impact of gender on neural responses through time-frequency analysis and network analysis to uncover gender disparities in bodily emotion recognition.
Methods: The study included 34 participants, consisting of 18 males and 16 females.
J Adv Nurs
December 2024
Department of Community Health Nursing, College of Nursing, Jouf University, Sakaka, Saudi Arabia.
Aim(s): To explore the perceptions of resilience among nurses using the Society-to-Cells Resilience Theory and examine how multilevel factors influence their ability to maintain resilience in high-stress environments.
Design: A qualitative study using semi-structured interviews.
Methods: Sixteen registered nurses from various healthcare settings in the Asir region, Saudi Arabia, participated in face-to-face interviews conducted from February to April 2024.
Neurol Sci
December 2024
Memory Clinic, Department of Neurology, Onze-Lieve-Vrouwziekenhuis, Aalst, Belgium.
Background And Objectives: POLR3-related disorders are a group of autosomal recessive neurodegenerative diseases that usually cause leukodystrophy and can lead to cognitive dysfunction. Literature reporting comprehensive neuropsychological assessment in POLR3A-related diseases is sparse. Here we describe the neuropsychological profile of a case of childhood-onset POLR3A-related spastic ataxia without leukodystrophy.
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