ArticleNeuropsychopharmacology : official publication of the American College of Neuropsychopharmacology2018
Brain-Behavior Participant Similarity Networks Among Youth and Emerging Adults with Schizophrenia Spectrum, Autism Spectrum, or Bipolar Disorder and Matched Controls.
Article in Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed.
- From heterogeneity to translation: data‑driven subtyping of autism in a multilevel framework.Translational psychiatry · 2026Review
- Brain-clinical biotyping in patients with idiopathic REM sleep behavior disorder.NPJ Parkinson's disease · 2025Article
- Interpretable and integrative deep learning for discovering brain-behaviour associations.Scientific reports · 2025Article
- Functional magnetic resonance imaging in schizophrenia: current evidence, methodological advances, limitations and future directions.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2024Article
- Similarity network fusion to identify phenotypes of small-for-gestational-age fetuses.iScience · 2023Article
- Neurobiological Clusters Are Associated With Trajectories of Overall Psychopathology in Youth.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2023Article
- Shared and distinct white matter abnormalities in adolescent-onset schizophrenia and adolescent-onset psychotic bipolar disorder.Psychological medicine · 2023Article
- Parsing brain-behavior heterogeneity in very preterm born children using integrated similarity networks.Translational psychiatry · 2023Article
- A machine learning approach on whole blood immunomarkers to identify an inflammation-associated psychosis onset subgroup.Molecular psychiatry · 2023Article
- Multi-omic integration via similarity network fusion to detect molecular subtypes of ageing.Brain communications · 2023Article
- Whole Person Modeling: a transdisciplinary approach to mental health research.Discover mental health · 2023Review
- Multi-modal intermediate integrative methods in neuropsychiatric disorders: A review.Computational and structural biotechnology journal · 2022Review
- Social Cognitive Networks and Social Cognitive Performance Across Individuals With Schizophrenia Spectrum Disorders and Healthy Control Participants.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2021Article
- Evidence of shared and distinct functional and structural brain signatures in schizophrenia and autism spectrum disorder.Communications biology · 2021Article
- Potential scalp stimulation targets for mental disorders: evidence from neuroimaging studies.Journal of translational medicine · 2021Article
- Structural and functional brain alterations revealed by neuroimaging in CNV carriers.Current opinion in genetics & development · 2021Review
- Decomposing complex links between the childhood environment and brain structure in school-aged youth.Developmental cognitive neuroscience · 2021Article
- Integration of brain and behavior measures for identification of data-driven groups cutting across children with ASD, ADHD, or OCD.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2021Article
- Multimodal phenotypic axes of Parkinson's disease.NPJ Parkinson's disease · 2021Article
- Neuroimaging Heterogeneity in Psychosis: Neurobiological Underpinnings and Opportunities for Prognostic and Therapeutic Innovation.Biological psychiatry · 2020Review
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9 authors.
Funding
Abstract
There is considerable heterogeneity in social cognitive and neurocognitive performance among people with schizophrenia spectrum disorders (SSD), autism spectrum disorders (ASD), bipolar disorder (BD), and healthy individuals. This study used Similarity Network Fusion (SNF), a novel data-driven approach, to identify participant similarity networks based on relationships among demographic, brain imaging, and behavioral data. T1-weighted and diffusion-weighted magnetic resonance images were obtained for 174 adolescents and young adults (aged 16-35 years) with an SSD (n=51), an ASD without intellectual disability (n=38), euthymic BD (n=34), and healthy controls (n=51). A battery of social cognitive and neurocognitive tasks were administered. Data integration, cluster determination, and biological group formation were then obtained using SNF. We identified four new groups of individuals, each with distinct neural circuit-cognitive profiles. The most influential variables driving the formation of the new groups were robustly reliable across embedded resampling techniques. The data-driven groups showed considerably greater differentiation on key social and neurocognitive circuit nodes than groups generated by diagnostic analyses or dimensional social cognitive analyses. The data-driven groups were validated through functional outcome and brain network property measures not included in the SNF model. Cutting across diagnostic boundaries, our approach can effectively identify new groups of people based on a profile of neuroimaging and behavioral data. Our findings bring us closer to disease subtyping that can be leveraged toward the targeting of specific neural circuitry among participant subgroups to ameliorate social cognitive and neurocognitive deficits.
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