ArticleFrontiers in psychiatry2022
Prediction of Facial Emotion Recognition Ability in Patients With First-Episode Schizophrenia Using Amplitude of Low-Frequency Fluctuation-Based Support Vector Regression Model.
Article in Frontiers in psychiatry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review on dysconnectivity in face and emotion processing networks in schizophrenia.Cognitive, affective & behavioral neuroscience · 2026Pooled it
- Transdiagnostic alterations of intrinsic brain activity in major psychiatric disorders.European archives of psychiatry and clinical neuroscience · 2026Article
- Functional magnetic resonance imaging study on short-term memory changes in children after congenital heart surgery.Journal of cardiothoracic surgery · 2026Article
- Selective impairment and a positive recognition bias of the facial emotion recognition after propofol anesthesia during gastrointestinal endoscopy.Frontiers in psychology · 2025Article
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Authors and funding
7 authors.
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Abstract
Objective: There were few studies that had attempted to predict facial emotion recognition (FER) ability at the individual level in schizophrenia patients. In this study, we developed a model for the prediction of FER ability in Chinese Han patients with the first-episode schizophrenia (FSZ). Materials and Methods: A total of 28 patients with FSZ and 33 healthy controls (HCs) were recruited. All subjects underwent resting-state fMRI (rs-fMRI). The amplitude of low-frequency fluctuation (ALFF) method was selected to analyze voxel-level spontaneous neuronal activity. The visual search experiments were selected to evaluate the FER, while the support vector regression (SVR) model was selected to develop a model based on individual rs-fMRI brain scan. Results: Group difference in FER ability showed statistical significance ( Conclusion: Our study provides an evidence that abnormal spontaneous activity in specific brain regions may serve as a predictive biomarker for fearful FER ability in schizophrenia.
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