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Introduction: Emotion processing deficits often occur in patients with schizophrenia. We investigate whether patients and controls differ in the association between facial emotion recognition and experience of affective empathy and whether performance on these emotion processing domains differently relates to white matter connectivity.
Materials And Methods: Forty-seven patients with schizophrenia and 47 controls performed an emotion recognition and affective empathy task. T1-weighted and diffusion-tensor images (DTI) of the brain were acquired. Using Tracula 5.3, ten fibers were reconstructed and fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were extracted. Groups were compared on task performance, white matter measures and their interactions using ANCOVAs. Correction for multiple comparisons was applied.
Results: Patients scored lower on emotion recognition ( = 0.037) and reported higher levels of affective empathy ( < 0.001) than controls. Patients with poor emotion recognition (PT-low) experienced stronger affective empathy than patients with similar emotion recognition performance as controls (PT-normal; = 0.011), who in turn reported stronger affective empathy than controls ( = 0.043). We found a significant interaction between emotion recognition, affective empathy and anterior thalamic radiation AD ( = 0.017, = 0.43). analyses revealed that the correlation between AD and empathy differed significantly between all groups (empathy/AD in PT-low < empathy/AD in PT-normal < empathy/AD in controls).
Discussion: In patients with poor emotion recognition, the negative association between anterior thalamic radiation AD and affective empathy was stronger than in patients with normal emotion recognition capacity. Possibly, axonal damage in fronto-thalamic structural connections, as part of a larger frontotemporal network, underlies the association between poor emotion recognition and higher levels of affective empathy in schizophrenia patients.
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http://dx.doi.org/10.3389/fpsyt.2022.910985 | DOI Listing |
Front Psychol
December 2024
F. C. Copenhagen, Copenhagen, Denmark.
This paper presents a general model of the cognitive processes involved in each play situation of soccer at the elite level. Theoretically the model draws on general frameworks from cognitive psychology and neuroscience, in particular the affordance competition hypothesis and the reward prediction error theory. The model includes three functional stages: situational assessment, action selection and execution, and outcome assessment.
View Article and Find Full Text PDFFront Psychol
December 2024
Neuropsychological and Speech Therapy Unit, Neurocenter of Southern Switzerland, Lugano, Switzerland.
[This corrects the article DOI: 10.3389/fpsyg.2022.
View Article and Find Full Text PDFFront Neurosci
December 2024
Department of Tuina, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China.
Introduction: Emotion recognition using electroencephalography (EEG) is a key aspect of brain-computer interface research. Achieving precision requires effectively extracting and integrating both spatial and temporal features. However, many studies focus on a single dimension, neglecting the interplay and complementarity of multi-feature information, and the importance of fully integrating spatial and temporal dynamics to enhance performance.
View Article and Find Full Text PDFDis Model Mech
December 2024
CNRS, Institut des Neurosciences Paris-Saclay, Université Paris-Saclay, 91400 Saclay, France.
The severity of brain comorbidities in Duchenne muscular dystrophy (DMD) depends on the mutation position within the DMD gene and differential loss of distinct brain dystrophin isoforms (i.e. Dp427, Dp140, Dp71).
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December 2024
Aspect Research Centre for Autism Practice, Autism Spectrum Australia, Level 5, Tower B, The Zenith, 821 Pacific Highway, Chatswood, NSW, 2067, Australia.
This study aimed to validate the Mandarin translation of the Stanford Social Dimensions Scale (SSDS). The initial validation sample consisted of 480 children with Autism Spectrum Disorder (ASD) (M = 9.35).
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