{"title":"From Dyadic to Higher-Order Interactions: Enhanced Representation of Homotopic Functional Connectivity Through Control of Intervening Variables.","authors":"Behdad Khodabandehloo, Payam Jannatdoust, Babak Nadjar Araabi","doi":"10.1089/brain.2024.0056","DOIUrl":null,"url":null,"abstract":"<p><p><b><i>Background:</i></b> The brain's complex functionality emerges from network interactions that go beyond dyadic connections, with higher-order interactions significantly contributing to this complexity. Homotopic functional connectivity (HoFC) is a key neurophysiological characteristic of the human brain, reflecting synchronized activity between corresponding regions in the brain's hemispheres. <b><i>Materials and Methods:</i></b> Using resting-state functional magnetic resonance imaging data from the Human Connectome Project, we evaluate dyadic and higher-order interactions of three functional connectivity (FC) parameterizations-bivariate correlation, partial correlation, and tangent space embedding-in their effectiveness at capturing HoFC through the inter-hemispheric analogy test. <b><i>Results:</i></b> Higher-order feature vectors are generated through node2vec, a random walk-based node embedding technique applied to FC networks. Our results show that higher-order feature vectors derived from partial correlation most effectively represent HoFC, while tangent space embedding performs best for dyadic interactions. <b><i>Discussion:</i></b> These findings validate HoFC and underscore the importance of the FC construction method in capturing intrinsic characteristics of the human brain.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Brain connectivity","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1089/brain.2024.0056","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Background: The brain's complex functionality emerges from network interactions that go beyond dyadic connections, with higher-order interactions significantly contributing to this complexity. Homotopic functional connectivity (HoFC) is a key neurophysiological characteristic of the human brain, reflecting synchronized activity between corresponding regions in the brain's hemispheres. Materials and Methods: Using resting-state functional magnetic resonance imaging data from the Human Connectome Project, we evaluate dyadic and higher-order interactions of three functional connectivity (FC) parameterizations-bivariate correlation, partial correlation, and tangent space embedding-in their effectiveness at capturing HoFC through the inter-hemispheric analogy test. Results: Higher-order feature vectors are generated through node2vec, a random walk-based node embedding technique applied to FC networks. Our results show that higher-order feature vectors derived from partial correlation most effectively represent HoFC, while tangent space embedding performs best for dyadic interactions. Discussion: These findings validate HoFC and underscore the importance of the FC construction method in capturing intrinsic characteristics of the human brain.
期刊介绍:
Brain Connectivity provides groundbreaking findings in the rapidly advancing field of connectivity research at the systems and network levels. The Journal disseminates information on brain mapping, modeling, novel research techniques, new imaging modalities, preclinical animal studies, and the translation of research discoveries from the laboratory to the clinic.
This essential journal fosters the application of basic biological discoveries and contributes to the development of novel diagnostic and therapeutic interventions to recognize and treat a broad range of neurodegenerative and psychiatric disorders such as: Alzheimer’s disease, attention-deficit hyperactivity disorder, posttraumatic stress disorder, epilepsy, traumatic brain injury, stroke, dementia, and depression.