Background: Although impairment in empathy has been reported in schizophrenia spectrum disorders, little is known about the relationship between empathy and schizotypal traits. This study examines this relationship by applying network analysis to a large sample collected at 18-months follow-up in a longitudinal dataset.
Methods: One thousand four hundred and eighty-six college students were recruited and completed a set of self-reported questionnaires on empathy, schizotypy, depression, anxiety and stress. Networks were constructed by taking the subscale scores of these measures as nodes and partial correlations between each pair of nodes as edges. Network Comparison Tests were performed to investigate the differences between individuals with high and low schizotypy.
Results: Cognitive and affective empathy were strongly connected with negative schizotypy in the network. Physical and social anhedonia showed high centrality measured by strength, closeness and betweenness while anxiety and stress showed high expected influence. Predictability ranged from 22.4% (personal distress) to 79.9% (anxiety) with an average of 54.4%. Compared with the low schizotypy group, the high schizotypy group showed higher global strength (S = 0.813, p < 0.05) and significant differences in network structure (M = 0.531, p < 0.001) and strength of edges connecting empathy with schizotypy (adjusted ps < 0.05).
Limitations: Only self-rating scales were used, and disorganized schizotypy was not included.
Conclusions: Our findings suggest that the cognitive and affective components of empathy and dimensions of schizotypy are closely related in the general population and their network interactions may play an important role in individuals with high schizotypy.
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http://dx.doi.org/10.1016/j.jad.2020.08.030 | DOI Listing |
J Affect Disord
January 2025
Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610072, China; Key Laboratory of Psychosomatic Medicine, Chinese Academy of Medical Sciences, Chengdu 610072, China; Department of Psychiatry, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand; Medical Laboratory Technology Department, College of Medical Technology, The Islamic University, Najaf, Iraq. Electronic address:
Background: A recent study conducted by the laboratory of the first author revealed that major depression is composed of two distinct subtypes: major dysmood disorder (MDMD) and simple dysmood disorder (SDMD). The latter is a less severe phenotype with fewer aberrant biological pathways. MDMD, but not SDMD, patients were identified to have highly sensitized cytokine/growth factor networks using stimulated whole blood cultures.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Department of Psychology, City College, City University of New York, New York, NY 10031.
Looking at the world often involves not just seeing things, but feeling things. Modern feedforward machine vision systems that learn to perceive the world in the absence of active physiology, deliberative thought, or any form of feedback that resembles human affective experience offer tools to demystify the relationship between seeing and feeling, and to assess how much of visually evoked affective experiences may be a straightforward function of representation learning over natural image statistics. In this work, we deploy a diverse sample of 180 state-of-the-art deep neural network models trained only on canonical computer vision tasks to predict human ratings of arousal, valence, and beauty for images from multiple categories (objects, faces, landscapes, art) across two datasets.
View Article and Find Full Text PDFFront Syst Neurosci
January 2025
International research center for Cognitive Applied Neuroscience (IrcCAN), Università Cattolica del Sacro Cuore, Milan, Italy.
This study examines the impact of positive and negative feedback on recall of past decisions, focusing on behavioral performance and electrophysiological (EEG) responses. Participants completed a decision-making task involving 10 real-life scenarios, each followed by immediate positive or negative feedback. In a recall phase, participants' accuracy (ACC), errors (ERRs), and response times (RTs) were recorded alongside EEG data to analyze brain activity patterns related to recall.
View Article and Find Full Text PDFClin Psychol Sci
November 2024
Department of Psychology, Michigan State University, USA.
Internalizing (e.g., anxiety, depression) and disordered eating (DE; e.
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