Temporal and spatial variability of large-scale dynamic brain networks in ASD.
Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by significant impairments in social-cognitive functioning. Prior studies have identified abnormal brain functional connectivity (FC) patterns in individuals with ASD, which are associated with core symptoms and serve as p...
| Publicado en: | European Child & Adolescent Psychiatry Vol. 34; no. 8; pp. 2555 - 2570 |
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| Autores principales: | , , , , , , , , , , , |
| Formato: | diagnostic images equations & formulas research tables/charts Journal Article |
| Publicado: |
Springer Nature
Aug2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=187670763&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 187670763 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10188827 EJ3 jtl: European Child & Adolescent Psychiatry issn: 10188827 maglogo: N pubinfo: dt: Aug2025 vid: 34 iid: 8 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 187670763 183314682 187670763 187670763 10.1007/s00787-025-02679-9 187670763 ppf: 2555 ppct: 15 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Temporal and spatial variability of large-scale dynamic brain networks in ASD. aug: au: Yin, Shunjie Sun, Shan Li, Jia Feng, Yu Zheng, Liqin Chen, Kai Ma, Jiwang Xu, Fen Yao, Dezhong Xu, Peng Liang, X. San Zhang, Tao affil: https://ror.org/04gwtvf26 Mental Health Education Center, School of Science, Xihua University, 610039, Chengdu, PR China sug: subj: Large-Scale Brain Networks Autism Spectrum Disorder Diagnosis Funding Source Human Case Control Studies Magnetic Resonance Imaging Functional Connectivity Interview Guides Male Female Child Adolescence T-Tests Chi Square Test Intelligence Tests Comparative Studies Amygdala Thalamus Child: 6-12 years Adolescent: 13-18 years Male Female ab: Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by significant impairments in social-cognitive functioning. Prior studies have identified abnormal brain functional connectivity (FC) patterns in individuals with ASD, which are associated with core symptoms and serve as potential biomarkers for diagnosis. However, the patterns of temporal and spatial variability in dynamic functional connectivity networks (dFCNs) in ASD and their relationship with ASD behaviors remain underexplored. This study uses fuzzy entropy to analyze the temporal variability and spatial variability of dFCNs, aiming to reveal distinctive FC patterns in ASD and identify new biomarkers. We conducted a comparative analysis between ASD and healthy controls (HCs), examining the association with clinical symptoms. Our findings indicate increased FC temporal variability in sensorimotor, subcortical, and cerebellar networks in ASD compared to HCs. Additionally, increased spatial variability was observed primarily in visual, limbic, subcortical, and cerebellar networks. Notably, these variability patterns correlated with symptom severity in ASD. Utilizing these spatiotemporal variability features, we developed multi-site classification models that achieved high accuracy (81.25%) in identifying ASD. These results provide novel insights into the neural mechanisms and clinical characteristics of ASD, suggesting that integrated spatiotemporal dFCN features may enhance diagnostic accuracy. pubtype: Academic Journal doctype: diagnostic images equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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