{"doi":"10.1101/2022.10.12.511922","title":"MIND Networks: Robust Estimation of Structural Similarity from Brain MRI","abstract":"Abstract Structural similarity networks are a central focus of magnetic resonance imaging (MRI) research into human brain connectomes in health and disease. We present Morphometric INverse Divergence (MIND), a robust method to estimate within-subject structural similarity between cortical areas based on the Kullback-Leibler divergence between the multivariate distributions of their structural features. Compared to the prior approach of morphometric similarity networks (MSNs) on N>10,000 data from the ABCD cohort, MIND networks were more consistent with known cortical symmetry, cytoarchitecture, and (in N=19 macaques) gold-standard tract-tracing connectivity, and were more invariant to cortical parcellation. Importantly, MIND networks were remarkably coupled with cortical gene co-expression, providing fresh evidence for the unified architecture of brain structure and transcription. Using kinship (N=1282) and genetic data (N=4085), we characterized the heritability of MIND phenotypes, identifying stronger genetic influence on the relationship between structurally divergent regions compared to structurally similar regions. Overall, MIND presents a biologically-validated lens for analyzing the structural organization of the cortex using readily-available MRI measurements.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2022,"id":299554,"datarank":0.24141568686511508,"base_score":1.6094379124341003,"endowment":1.6094379124341003,"self_citation_contribution":0.24141568686511508,"citation_network_contribution":0.0,"self_endowment_contribution":0.24141568686511508,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":4,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9502,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":52331,"name":"Jakob Seidlitz","orcid":"0000-0002-8164-7476","position":1,"is_corresponding":false},{"id":52326,"name":"Varun Warrier","orcid":"0000-0003-4532-8571","position":2,"is_corresponding":false},{"id":52342,"name":"Richard A. I. Bethlehem","orcid":"0000-0002-0714-0685","position":3,"is_corresponding":false},{"id":52339,"name":"Aaron Alexander-Bloch","orcid":"0000-0001-6554-1893","position":4,"is_corresponding":false},{"id":52334,"name":"Travis T. Mallard","orcid":"0000-0002-3265-3001","position":5,"is_corresponding":false},{"id":989912,"name":"Rafael Romero García","orcid":null,"position":6,"is_corresponding":false},{"id":52341,"name":"Edward T. Bullmore","orcid":"0000-0002-8955-8283","position":7,"is_corresponding":false},{"id":232630,"name":"Sarah E. Morgan","orcid":"0000-0002-1261-5884","position":8,"is_corresponding":false},{"id":60817,"name":"Isaac Sebenius","orcid":"0000-0001-9927-2150","position":0,"is_corresponding":true}],"reference_count":66,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T00:31:44.904250Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}