Mentalizing and emotion recognition are impaired in behavioral variant frontotemporal dementia (bvFTD). It is not clear whether these abilities are also disturbed in other conditions with prominent frontal lobe involvement, such as progressive supranuclear palsy (PSP). Our aim was to investigate social cognition (facial emotion recognition, recognition of social norms violation and mentalizing) in bvFTD and PSP. The neural basis of these functions in PSP and bvFTD groups, by analysis of structural neuroimaging, were also investigated. Twenty-three bvFTD patients, 21 PSP patients and 23 healthy controls were included. All participants underwent 3T brain MRI and a full cognitive exam including the short version of Social and Emotional Assessment (Mini-SEA), which is composed of a facial emotion recognition test (FERT) and the faux pas test. Two components of the faux pas test were distinguished: a score assessing the recognition of social norms violation and a score assessing mentalizing. Compared to controls, bvFTD and PSP patients had significantly reduced scores in all tests of social cognition but did not differ on these measures. PSP and bvFTD had cerebral atrophy in critical regions for social cognition processes, when compared to controls. The cortical correlates of emotion recognition partially overlapped in bvFTD and PSP, with correlations retrieved within the frontal medial cortex, cingulate, insula and limbic structures. PSP and bvFTD patients also displayed similar patterns of brain correlations for the composite score of social norms, with a significant cluster in anterior temporal lobes. Mentalizing scores were associated with frontal and temporal poles bilaterally, in both bvFTD and PSP. These findings support previous observations that PSP patients exhibit impairment in complex cognitive abilities, such as mentalizing. Moreover, these data extend previous findings showing that PSP and bvFTD share key clinical, cognitive and neuroimaging features.
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http://dx.doi.org/10.1016/j.cortex.2022.07.015 | 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.
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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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