ArticleNetwork neuroscience (Cambridge, Mass.)2020
Clinically feasible brain morphometric similarity network construction approaches with restricted magnetic resonance imaging acquisitions.
Article in Network neuroscience (Cambridge, Mass.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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27 citing papers in PubMed.
- Parent-Child Cortical Similarity Indexes Multiple Dimensions of Sensitivity in the Association Between Family Environment and Adolescent Internalizing Symptoms.bioRxiv : the preprint server for biology · 2026Article
- Spatial analysis of paraneoplastic cerebellar degeneration in ovarian cancer with anti-Yo syndrome and SCA1.Journal of neurology · 2026Article
- Associations between anterior hypothalamic subunits and ADHD and autistic traits revealed by deep learning MRI segmentation.Discover mental health · 2026Article
- Morphometric Similarity Loss and Gray Matter Atrophy Align with Neurotransmitter and Mitochondrial Maps in Drug-Resistant Epilepsy.Neuropsychiatric disease and treatment · 2026Article
- Neurobiological subtypes of adolescent depression: a multimodal integration of morphometric similarity network and spatial transcriptomics.Molecular psychiatry · 2025Article
- Morphometric similarity network-based graph convolutional networks for schizophrenia classification.Scientific reports · 2025Article
- Reduced brain structural similarity is associated with maturation, neurobiological features, and clinical status in schizophrenia.Nature communications · 2025Article
- Cortical Morphometric Similarity Remodeling in Traumatic Brain Injury Links Cognitive Impairments with Transcriptional Changes and Type-Specific Cells.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Early Development and Co-Evolution of Microstructural and Functional Brain Connectomes: A Multi-Modal MRI Study in Preterm and Full-Term Infants.Human brain mapping · 2025Article
- Cortical morphometric similarity gradient in schizophrenia and its association with transcriptional profiles and clinical phenotype.Psychological medicine · 2025Article
- Structural MRI of brain similarity networks.Nature reviews. Neuroscience · 2025Review
- Alteration of multilayer network perspective on gray and white matter connectivity in obstructive sleep apnea.Sleep & breathing = Schlaf & Atmung · 2024Article
- Multilayer network analysis in patients with juvenile myoclonic epilepsy.Neuroradiology · 2024Article
- Altered morphometric similarity networks in insomnia disorder.Brain structure & function · 2024Article
- Relationship between brain structural network integrity and emotional symptoms in youth with perinatally-acquired HIV.Brain, behavior, and immunity · 2024Article
- Disinhibition in dementia related to reduced morphometric similarity of cognitive control network.Brain communications · 2024Article
- Involvement of the default mode network in patients with transient global amnesia: multilayer network.Neuroradiology · 2023Article
- Multilayer network changes in patients with migraine.Brain and behavior · 2023Article
- Predicting 'Brainage' in late childhood to adolescence (6-17yrs) using structural MRI, morphometric similarity, and machine learning.Scientific reports · 2023Article
- Morphometric dis-similarity between cortical and subcortical areas underlies cognitive function and psychiatric symptomatology: a preadolescence study from ABCD.Molecular psychiatry · 2023Article
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2 authors.
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Abstract
Morphometric similarity networks (MSNs) estimate organization of the cortex as a biologically meaningful set of similarities between anatomical features at the macro- and microstructural level, derived from multiple structural MRI (sMRI) sequences. These networks are clinically relevant, predicting 40% variance in IQ. However, the sequences required (T1w, T2w, DWI) to produce these networks are longer acquisitions, less feasible in some populations. Thus, estimating MSNs using features from T1w sMRI is attractive to clinical and developmental neuroscience. We studied whether reduced-feature approaches approximate the original MSN model as a potential tool to investigate brain structure. In a large, homogenous dataset of healthy young adults (from the Human Connectome Project, HCP), we extended previous investigations of reduced-feature MSNs by comparing not only T1w-derived networks, but also additional MSNs generated with fewer MR sequences, to their full acquisition counterparts. We produce MSNs that are highly similar at the edge level to those generated with multimodal imaging; however, the nodal topology of the networks differed. These networks had limited predictive validity of generalized cognitive ability. Overall, when multimodal imaging is not available or appropriate, T1w-restricted MSN construction is feasible, provides an appropriate estimate of the MSN, and could be a useful approach to examine outcomes in future studies.
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