ArticleNeuroImage. Clinical2018
Identifying functional network changing patterns in individuals at clinical high-risk for psychosis and patients with early illness schizophrenia: A group ICA study.
Article in NeuroImage. Clinical, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 49 citations in OpenAlex.
- Mapping the psychosis spectrum - imaging neurosubtypes from multiscale functional network connectivity.Molecular psychiatry · 2026Article
- Using the excitation/inhibition ratio to optimize the classification of autism and schizophrenia.Translational psychiatry · 2025Article
- A whole-brain neuromark resting-state fMRI analysis of first-episode and early psychosis: Evidence of aberrant cortical-subcortical-cerebellar functional circuitry.NeuroImage. Clinical · 2024Article
- Interactions between the cortical midline structures and sensorimotor network track maladaptive self-beliefs in clinical high risk for psychosis.Schizophrenia (Heidelberg, Germany) · 2022Article
- A new multimodality fusion classification approach to explore the uniqueness of schizophrenia and autism spectrum disorder.Human brain mapping · 2022Article
- Atypical Dynamic Functional Network Connectivity State Engagement during Social-Emotional Processing in Schizophrenia and Autism.Cerebral cortex (New York, N.Y. : 1991) · 2022Article
- Evidence of shared and distinct functional and structural brain signatures in schizophrenia and autism spectrum disorder.Communications biology · 2021Article
- Altered dynamics of the prefrontal networks are associated with the risk for postpartum psychosis: a functional magnetic resonance imaging study.Translational psychiatry · 2021Article
- A deep learning fusion model for brain disorder classification: Application to distinguishing schizophrenia and autism spectrum disorder.ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine · 2020Article
- Functional network connectivity (FNC)-based generative adversarial network (GAN) and its applications in classification of mental disorders.Journal of neuroscience methods · 2020Article
- Default mode network modulation by mentalizing in young adults with autism spectrum disorder or schizophrenia.NeuroImage. Clinical · 2020Article
- Approaches to attenuated psychosis syndrome treatments: A perspective on the regulatory issues.Schizophrenia research. Cognition · 2019Review
- Resting-State Functional Connectivity and Psychotic-like Experiences in Childhood: Results From the Adolescent Brain Cognitive Development Study.Biological psychiatry · 2019Article
- A method for building a genome-connectome bipartite graph model.Journal of neuroscience methods · 2019Article
- Transient Patterns of Functional Dysconnectivity in Clinical High Risk and Early Illness Schizophrenia Individuals Compared with Healthy Controls.Brain connectivity · 2019Article
- Group ICA for identifying biomarkers in schizophrenia: 'Adaptive' networks via spatially constrained ICA show more sensitivity to group differences than spatio-temporal regression.NeuroImage. Clinical · 2019Article
- A multicenter study of ketamine effects on functional connectivity: Large scale network relationships, hubs and symptom mechanisms.NeuroImage. Clinical · 2019Article
- Reduced higher-dimensional resting state fMRI dynamism in clinical high-risk individuals for schizophrenia identified by meta-state analysis.Schizophrenia research · 2018Article
- Classification and Prediction of Brain Disorders Using Functional Connectivity: Promising but Challenging.Frontiers in neuroscience · 2018Review
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 2 countries.
Funding
Abstract
Although individuals at clinical high risk (CHR) for psychosis exhibit a psychosis-risk syndrome involving attenuated forms of the positive symptoms typical of schizophrenia (SZ), it remains unclear whether their resting-state brain intrinsic functional networks (INs) show attenuated or qualitatively distinct patterns of functional dysconnectivity relative to SZ patients. Based on resting-state functional magnetic imaging data from 70 healthy controls (HCs), 53 CHR individuals (among which 41 subjects were antipsychotic medication-naive), and 58 early illness SZ (ESZ) patients (among which 53 patients took antipsychotic medication) within five years of illness onset, we estimated subject-specific INs using a novel group information guided independent component analysis (GIG-ICA) and investigated group differences in INs. We found that when compared to HCs, both CHR and ESZ groups showed significant differences, primarily in default mode, salience, auditory-related, visuospatial, sensory-motor, and parietal INs. Our findings suggest that widespread INs were diversely impacted. More than 25% of voxels in the identified significant discriminative regions (obtained using all 19 possible changing patterns excepting the no-difference pattern) from six of the 15 interrogated INs exhibited monotonically decreasing Z-scores (in INs) from the HC to CHR to ESZ, and the related regions included the left lingual gyrus of two vision-related networks, the right postcentral cortex of the visuospatial network, the left thalamus region of the salience network, the left calcarine region of the fronto-occipital network and fronto-parieto-occipital network. Compared to HCs and CHR individuals, ESZ patients showed both increasing and decreasing connectivity, mainly hypo-connectivity involving 15% of the altered voxels from four INs. The left supplementary motor area from the sensory-motor network and the right inferior occipital gyrus in the vision-related network showed a common abnormality in CHR and ESZ groups. Some brain regions also showed a CHR-unique alteration (primarily the CHR-increasing connectivity). In summary, CHR individuals generally showed intermediate connectivity between HCs and ESZ patients across multiple INs, suggesting that some dysconnectivity patterns evident in ESZ predate psychosis in attenuated form during the psychosis risk stage. Hence, these connectivity measures may serve as possible biomarkers to predict schizophrenia progression.
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