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Background: Inflammation impairs cognitive function in healthy individuals and people with psychiatric disorders, such as bipolar disorder (BD). This effect may also impact emotion recognition, a fundamental element of social cognition. Our study aimed to investigate the relationships between pro-inflammatory cytokines and emotion recognition in euthymic BD patients and healthy controls (HCs).
Methods: We recruited forty-four euthymic BD patients and forty healthy controls (HCs) and measured their inflammatory markers, including high-sensitivity C-reactive protein (hs-CRP), interleukin-6 (IL-6), and TNF-α. We applied validated cognitive tasks, the Wisconsin Card-Sorting Test (WCST) and Continuous Performance Test (CPT), and a social cognitive task for emotion recognition, Diagnostic Analyses of Nonverbal Accuracy, Taiwanese Version (DANVA-2-TW). We analyzed the relationships between cytokines and cognition and then explored possible predictive factors of sadness recognition accuracy.
Results: Regarding pro-inflammatory cytokines, TNF-α was elevated in euthymic BD patients relative to HCs. In euthymic BD patients only, higher TNF-α levels were associated with lower accuracy of sadness recognition. Regression analysis revealed that TNF-α was an independent predictive factor of sadness recognition in patients with euthymic BD when neurocognition was controlled for.
Conclusions: We demonstrated that enhanced inflammation, indicated by increased TNF-α, was an independent predictive factor of impaired sadness recognition in BD patients but not in HCs. Our findings suggested a direct influence of TNF-α on sadness recognition and indicated vulnerability to depression in euthymic BD patients with chronic inflammation.
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http://dx.doi.org/10.1016/j.jpsychires.2024.03.049 | DOI Listing |
Int J Ment Health Nurs
October 2025
Cukurova State Hospital, Adana, Turkey.
As in all other traumas, children and adolescents are more sensitive and vulnerable to the effects of earthquakes. This study aimed to understand the earthquake experiences of adolescent survivors. This study is a qualitative study in which the photovoice method was used.
View Article and Find Full Text PDFDev Psychol
September 2025
University of California-Berkeley, Department of Psychology.
Emotion recognition, one key aspect of emotion reasoning, is crucial to socioemotional development in childhood. While much developmental research has focused on facial emotion recognition, studies on the recognition of emotions conveyed through vocal bursts remain relatively scarce, despite the voice being one of the primary channels for conveying emotion. To address this gap, we investigated (a) how recognition accuracy across six well-studied emotions in vocal bursts changes between the ages of 5 and 8 (N = 162, 47.
View Article and Find Full Text PDFCodas
August 2025
Departamento de Fonoaudiologia, Universidade Federal da Paraíba - UFPB - João Pessoa (PB), Brasil.
Purpose: To verify if there is a difference in acoustic-prosodic measures in different emotional states of speakers of Brazilian Portuguese (BP).
Methods: The data sample consisted of 182 audio signals produced by actors (professionals or students), from the semi-spontaneous speech task "Look at the blue plane" in the various emotions (joy, sadness, fear, anger, surprise, disgust) and neutral emission. Values were extracted from acoustic-prosodic measures of duration, fundamental frequency and intensity of the various emotions.
Sci Rep
August 2025
Faculty of Humanities and Arts, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, 999078, China.
Speech is one of the most efficient methods of communication among humans, inspiring advancements in machine speech processing under Natural Language Processing (NLP). This field aims to enable computers to analyze, comprehend, and generate human language naturally. Speech processing, as a subset of artificial intelligence, is rapidly expanding due to its applications in emotion recognition, human-computer interaction, and sentiment analysis.
View Article and Find Full Text PDFSci Rep
July 2025
Department of Computer Science and Technology, Kean University, Union, NJ, 07083, USA.
Understanding a driver's emotional state is critical for ensuring road safety and public well-being. Emotions such as anger, fear, disgust, sadness, or happiness can significantly influence driving behavior and decision-making. Facial micro-expressions reveal genuine feelings that people attempt to mask or conceal, offering valuable cues for detecting these emotional states, as they tend to be universally expressed across cultures.
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