ArticleNature neuroscience2023
Robust estimation of cortical similarity networks from brain MRI.
Article in Nature neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 84 papers.
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Who cites it
84 citing papers in PubMed.
- Mapping topological abnormalities in cortical similarity networks to schizophrenia-associated gene expression.Dialogues in clinical neuroscience · 2026Article
- Subtyping OCD based on individual symptom networks: subtype-specific neural dynamics and morphometric similarity linked to molecular profiles.Molecular psychiatry · 2026Article
- Beyond statistical thresholds: Mapping sequential ATN cascade transitions via brain structural topography in Alzheimer's disease.Science advances · 2026Article
- 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
- Editorial for "Relationship Between Dp140 Genotype and Cortical Similarity Network Phenotype in Duchenne Muscular Dystrophy: Preliminary T1 Weighted Study".Journal of magnetic resonance imaging : JMRI · 2026Article
- Individual-level metabolic connectivity captures cortical morphology and their coupling strengthens in the ageing brain.European journal of nuclear medicine and molecular imaging · 2026Article
- Brain morphology network profiles in male and female youth with autism.Cerebral cortex (New York, N.Y. : 1991) · 2026Article
- Morphometric Inverse Divergence Networks Combined with HYDRA Identify Parkinson's Disease Subtypes with Distinct Transcriptomic and Serum Biomarker Profiles.International journal of molecular sciences · 2026Article
- Graph-Based White Matter Tractometry: Methods, Applications, and the Path to Validation.Neuroinformatics · 2026Review
- The Cerebellar Connectome.Cerebellum (London, England) · 2026Article
- Transcriptional signatures of cortical morphometric variability in temporal lobe epilepsy.Epilepsia open · 2026Article
- Associations between altered morphometric inverse divergence networks, choroid plexus volume, and perivascular space network in patients with Parkinson disease: a cross-sectional study.Quantitative imaging in medicine and surgery · 2026Article
- Regional, functional and transcriptomic decoding of multidimensional brain structure alterations in obsessive-compulsive disorder.Nature communications · 2026Article
- The genetic architecture of cortical similarity networks.Nature communications · 2026Article
- Gray Matter Morphological Networks are Associated with Neurobiological Features, Cognitive Status and Clinical Recovery in Traumatic Brain Injury.medRxiv : the preprint server for health sciences · 2026Article
- The cellular correlates and adolescent reorganisation of cortical myelination networks in the common marmoset.Communications biology · 2026Article
- Shared subcortical-default mode morphological dysconnectivity in adolescent bipolar disorder, major depressive disorder and schizophrenia.Communications biology · 2026Article
- Cortical morphometric inverse divergence in attention-deficit/hyperactivity disorder correlates with cell-type-specific, laminar-specific and developmental transcriptomic signatures.Psychological medicine · 2026Article
- Brain network analysis using morphological intrinsic divergence: differences in small-world properties of morphological similarity networks among healthy young adults with different chronotypes.Brain imaging and behavior · 2026Article
- Mapping ADHD Heterogeneity and Biotypes by Topological Deviations in Morphometric Similarity Networks.JAMA psychiatry · 2026Article
24 more citing papers are in PubMed but not listed here.
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Authors and funding
9 authors.
Funding
Abstract
Structural similarity is a growing focus for magnetic resonance imaging (MRI) of connectomes. Here we propose Morphometric INverse Divergence (MIND), a new method to estimate within-subject similarity between cortical areas based on the divergence between their multivariate distributions of multiple MRI features. Compared to the prior approach of morphometric similarity networks (MSNs) on n > 11,000 scans spanning three human datasets and one macaque dataset, MIND networks were more reliable, more consistent with cortical cytoarchitectonics and symmetry and more correlated with tract-tracing measures of axonal connectivity. MIND networks derived from human T1-weighted MRI were more sensitive to age-related changes than MSNs or networks derived by tractography of diffusion-weighted MRI. Gene co-expression between cortical areas was more strongly coupled to MIND networks than to MSNs or tractography. MIND network phenotypes were also more heritable, especially edges between structurally differentiated areas. MIND network analysis provides a biologically validated lens for cortical connectomics using readily available MRI data.
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