ArticleHuman brain mapping2017
On the integrity of functional brain networks in schizophrenia, Parkinson's disease, and advanced age: Evidence from connectivity-based single-subject classification.
Article in Human brain mapping, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 26 papers, 2 of them syntheses that pooled it.
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Who cites it
26 citing papers in PubMed, 2 syntheses or guidelines pooled it, 46 citations in OpenAlex.
- Social cognition in Parkinson's disease: a comprehensive systematic review and integrative conceptual framework.Frontiers in aging neuroscience · 2026Pooled it
- Application of Support Vector Machine on fMRI Data as Biomarkers in Schizophrenia Diagnosis: A Systematic Review.Frontiers in psychiatry · 2020Pooled it
- Weaker top-down cognitive control and stronger bottom-up signaling transmission as a pathogenesis of schizophrenia.Schizophrenia (Heidelberg, Germany) · 2025Article
- Inter- and intra-subject similarity in network functional connectivity across a full narrative movie.Human brain mapping · 2024Article
- Network and state specificity in connectivity-based predictions of individual behavior.Human brain mapping · 2024Article
- Simulated brain networks reflecting progression of Parkinson's disease.Network neuroscience (Cambridge, Mass.) · 2024Article
- Network and State Specificity in Connectivity-Based Predictions of Individual Behavior.bioRxiv : the preprint server for biology · 2023Article
- Whole-brain dynamical modelling for classification of Parkinson's disease.Brain communications · 2023Article
- Classification and prediction of cognitive performance differences in older age based on brain network patterns using a machine learning approach.Network neuroscience (Cambridge, Mass.) · 2023Article
- A multiple-tissue-specific magnetic resonance imaging model for diagnosing Parkinson's disease: a brain radiomics study.Neural regeneration research · 2022Article
- Towards an efficient validation of dynamical whole-brain models.Scientific reports · 2022Article
- Mining imaging and clinical data with machine learning approaches for the diagnosis and early detection of Parkinson's disease.NPJ Parkinson's disease · 2022Review
- Shared Genetic Background between Parkinson's Disease and Schizophrenia: A Two-Sample Mendelian Randomization Study.Brain sciences · 2021Article
- Application of Artificial Intelligence in the MRI Classification Task of Human Brain Neurological and Psychiatric Diseases: A Scoping Review.Diagnostics (Basel, Switzerland) · 2021Article
- Functional parcellation of human and macaque striatum reveals human-specific connectivity in the dorsal caudate.NeuroImage · 2021Article
- Reconfiguration of Dynamic Functional Connectivity States in Patients With Lifelong Premature Ejaculation.Frontiers in neuroscience · 2021Article
- Age differences in predicting working memory performance from network-based functional connectivity.Cortex; a journal devoted to the study of the nervous system and behavior · 2020Article
- Joint Multi-modal Parcellation of the Human Striatum: Functions and Clinical Relevance.Neuroscience bulletin · 2020Article
- Machine learning techniques in a structural and functional MRI diagnostic approach in schizophrenia: a systematic review.Neuropsychiatric disease and treatment · 2019Review
- Abnormal Resting-State Functional Connectivity in the Whole Brain in Lifelong Premature Ejaculation Patients Based on Machine Learning Approach.Frontiers in neuroscience · 2019Article
Corrections and comments
- Erratum issued
Authors and funding
22 authors at 6 institutions in 1 country.
Funding
Abstract
Previous whole-brain functional connectivity studies achieved successful classifications of patients and healthy controls but only offered limited specificity as to affected brain systems. Here, we examined whether the connectivity patterns of functional systems affected in schizophrenia (SCZ), Parkinson's disease (PD), or normal aging equally translate into high classification accuracies for these conditions. We compared classification performance between pre-defined networks for each group and, for any given network, between groups. Separate support vector machine classifications of 86 SCZ patients, 80 PD patients, and 95 older adults relative to their matched healthy/young controls, respectively, were performed on functional connectivity in 12 task-based, meta-analytically defined networks using 25 replications of a nested 10-fold cross-validation scheme. Classification performance of the various networks clearly differed between conditions, as those networks that best classified one disease were usually non-informative for the other. For SCZ, but not PD, emotion-processing, empathy, and cognitive action control networks distinguished patients most accurately from controls. For PD, but not SCZ, networks subserving autobiographical or semantic memory, motor execution, and theory-of-mind cognition yielded the best classifications. In contrast, young-old classification was excellent based on all networks and outperformed both clinical classifications. Our pattern-classification approach captured associations between clinical and developmental conditions and functional network integrity with a higher level of specificity than did previous whole-brain analyses. Taken together, our results support resting-state connectivity as a marker of functional dysregulation in specific networks known to be affected by SCZ and PD, while suggesting that aging affects network integrity in a more global way. Hum Brain Mapp 38:5845-5858, 2017. © 2017 Wiley Periodicals, Inc.
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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.