ArticleNeuroImage2016
Classification of schizophrenia and bipolar patients using static and dynamic resting-state fMRI brain connectivity.
Article in NeuroImage, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 181 papers, 4 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
181 citing papers in PubMed, 4 syntheses or guidelines pooled it, 373 citations in OpenAlex.
- Linking Polygenic Risk of Schizophrenia to Variation in Magnetic Resonance Imaging Brain Measures: A Comprehensive Systematic Review.Schizophrenia bulletin · 2024Pooled it
- A meta-analysis and systematic review of single vs. multimodal neuroimaging techniques in the classification of psychosis.Molecular psychiatry · 2023Pooled it
- Evaluation of Risk of Bias in Neuroimaging-Based Artificial Intelligence Models for Psychiatric Diagnosis: A Systematic Review.JAMA network open · 2023Pooled it
- Towards a brain-based predictome of mental illness.Human brain mapping · 2020Pooled it
- Brain network dynamics reflect psychiatric illness status and transdiagnostic symptom profiles across health and disease.Nature communications · 2026Article
- Reduced mediodorsal thalamus activity underlies aberrant belief dynamics in a genetic mouse model of schizophrenia.Nature neuroscience · 2026Article
- Dynamic Resting-State Network Markers of Disruptive Behavior Problems in Youth.Biological psychiatry global open science · 2026Article
- Dynamic Fusion of Genomics and Functional Network Connectivity in UK Biobank Reveals Schizophrenia-Related SNP Manifolds.Human brain mapping · 2026Article
- Brain functional network connectivity interpolation characterizes the neuropsychiatric continuum and heterogeneity.bioRxiv : the preprint server for biology · 2026Article
- When Randomness Becomes Rigid: Dynamic Connectivity Entropy and Symptom-Linked Network Dysfunction in Schizophrenia.bioRxiv : the preprint server for biology · 2026Article
- Effects of light on brain-state dynamics and energy landscape.Network neuroscience (Cambridge, Mass.) · 2026Article
- Sex Similarities and Differences in Brain Dynamic Functional Connectivity Among Individuals With and Without Autism Spectrum Disorders.Human brain mapping · 2025Article
- Mutualistic Multi-Network Noisy Label Learning (MMNNLL) Method and Its Application to Transdiagnostic Classification of Bipolar Disorder and Schizophrenia.IEEE transactions on medical imaging · 2025Article
- Morphometric similarity network-based graph convolutional networks for schizophrenia classification.Scientific reports · 2025Article
- Intervention on Modifiable Lifestyle and Physiological Factors via Variational Autoencoder Reveals Changes in Functional Connectivity-Mediated Risk for Alzheimer's Disease.medRxiv : the preprint server for health sciences · 2025Article
- Dysregulated connectivity configuration of triple-network model in obsessive-compulsive disorder.Molecular psychiatry · 2025Article
- Classification of schizophrenia spectrum disorder using machine learning and functional connectivity: reconsidering the clinical application.BMC psychiatry · 2025Article
- Functional dysconnectivity of visual and somatomotor networks yields a simple and robust biomarker for psychosis.Molecular psychiatry · 2025Article
- A Statistical Characterization of Dynamic Brain Functional Connectivity.Human brain mapping · 2025Article
- Symptom-based depression subtypes: brain dynamic specificity and its association with gene expression profiles.Translational psychiatry · 2025Article
121 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
Recently, functional network connectivity (FNC, defined as the temporal correlation among spatially distant brain networks) has been used to examine the functional organization of brain networks in various psychiatric illnesses. Dynamic FNC is a recent extension of the conventional FNC analysis that takes into account FNC changes over short periods of time. While such dynamic FNC measures may be more informative about various aspects of connectivity, there has been no detailed head-to-head comparison of the ability of static and dynamic FNC to perform classification in complex mental illnesses. This paper proposes a framework for automatic classification of schizophrenia, bipolar and healthy subjects based on their static and dynamic FNC features. Also, we compare cross-validated classification performance between static and dynamic FNC. Results show that the dynamic FNC significantly outperforms the static FNC in terms of predictive accuracy, indicating that features from dynamic FNC have distinct advantages over static FNC for classification purposes. Moreover, combining static and dynamic FNC features does not significantly improve the classification performance over the dynamic FNC features alone, suggesting that static FNC does not add any significant information when combined with dynamic FNC for classification purposes. A three-way classification methodology based on static and dynamic FNC features discriminates individual subjects into appropriate diagnostic groups with high accuracy. Our proposed classification framework is potentially applicable to additional mental disorders.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.