Multiple sclerosis (MS) may be associated with impaired perception of facial emotions. However, emotion recognition mediated by bodily postures has never been examined in these patients. Moreover, several studies have suggested a relation between emotion recognition impairments and alexithymia. This is in line with the idea that the ability to recognize emotions requires the individuals to be able to understand their own emotions. Despite a deficit in emotion recognition has been observed in MS patients, the association between impaired emotion recognition and alexithymia has received little attention. The aim of this study was, first, to investigate MS patient's abilities to recognize emotions mediated by both facial and bodily expressions and, second, to examine whether any observed deficits in emotions recognition could be explained by the presence of alexithymia. Thirty patients with MS and 30 healthy matched controls performed experimental tasks assessing emotion discrimination and recognition of facial expressions and bodily postures. Moreover, they completed questionnaires evaluating alexithymia, depression, and fatigue. First, facial emotion recognition and, to a lesser extent, bodily emotion recognition can be impaired in MS patients. In particular, patients with higher disability showed an impairment in emotion recognition compared with patients with lower disability and controls. Second, their deficit in emotion recognition was not predicted by alexithymia. Instead, the disease's characteristics and the performance on some cognitive tasks significantly correlated with emotion recognition. Impaired facial emotion recognition is a cognitive signature of MS that is not dependent on alexithymia.
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http://dx.doi.org/10.1017/S1355617714000939 | DOI Listing |
J Integr Neurosci
January 2025
Department of Psychology, The Affiliated Hospital of Jiangnan University, 214151 Wuxi, Jiangsu, China.
Background: Deficits in emotion recognition have been shown to be closely related to social-cognitive functioning in schizophrenic. This study aimed to investigate the event-related potential (ERP) characteristics of social perception in schizophrenia patients and to explore the neural mechanisms underlying these abnormal cognitive processes related to social perception.
Methods: Participants included 33 schizophrenia patients and 35 healthy controls (HCs).
Sensors (Basel)
January 2025
Department of Psychological and Cognitive Sciences, Tsinghua University, Beijing 100084, China.
The objective identification of depression using physiological data has emerged as a significant research focus within the field of psychiatry. The advancement of wearable physiological measurement devices has opened new avenues for the identification of individuals with depression in everyday-life contexts. Compared to other objective measurement methods, wearables offer the potential for continuous, unobtrusive monitoring, which can capture subtle physiological changes indicative of depressive states.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Department of Electronics and Electrical Engineering, Faculty of Science and Technology, Keio University, 3-14-1, Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan.
In recent years, advancements in the interaction and collaboration between humans and have garnered significant attention. Social intelligence plays a crucial role in facilitating natural interactions and seamless communication between humans and Artificial Intelligence (AI). To assess AI's ability to understand human interactions and the components necessary for such comprehension, datasets like Social-IQ have been developed.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Faculty of Artificial Intelligence in Education, Central China Normal University, Wuhan 430079, China.
Behavioral computing based on visual cues has become increasingly important, as it can capture and annotate teachers' and students' classroom states on a large scale and in real time. However, there is a lack of consensus on the research status and future trends of computer vision-based classroom behavior recognition. The present study conducted a systematic literature review of 80 peer-reviewed journal articles following the Preferred Reporting Items for Systematic Assessment and Meta-Analysis (PRISMA) guidelines.
View Article and Find Full Text PDFPLoS One
January 2025
Faculty of Engineering, Free University of Bozen-Bolzano, Bolzano, South Tyrol, Italy.
Appraisal models, such as the Scherer's Component Process Model (CPM), represent an elegant framework for the interpretation of emotion processes, advocating for computational models that capture emotion dynamics. Today's emotion recognition research, however, typically classifies discrete qualities or categorised dimensions, neglecting the dynamic nature of emotional processes and thus limiting interpretability based on appraisal theory. In our research, we estimate emotion intensity from multiple physiological features associated to the CPM's neurophysiological component using dynamical models with the aim of bringing insights into the relationship between physiological dynamics and perceived emotion intensity.
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