A Principled Framework to Assess the Information-Theoretic Fitness of Brain Functional Sub-Circuits
Duong-Tran D, Nguyen N, Mu S, Chen J, Bao J, Xu F, Garai S, Cadena-Pico J, Kaplan A, Chen T, Zhao Y, Shen L, Goñi J. A Principled Framework to Assess the Information-Theoretic Fitness of Brain Functional Sub-Circuits. Mathematics 2024, 12: 2967. PMID: 38979488, PMCID: PMC11230349, DOI: 10.3390/math12192967.Peer-Reviewed Original ResearchStochastic block modelMultiple levels of granularityLevels of granularityFunctional networksInformation-theoreticThreshold methodThreshold strategyFunctional connectomeSub-circuitsGranularityHuman brain connectomeNetworkHuman Connectome ProjectBlock modelBrain connectome analysisFunctional sub-circuitsTopological featuresFrameworkPrinciples frameworkConnectome ProjectBrain connectomeNetwork neuroscienceThreshold valueMultiple levelsPartitioningBayesian mixed model inference for genetic association under related samples with brain network phenotype
Tian X, Wang Y, Wang S, Zhao Y, Zhao Y. Bayesian mixed model inference for genetic association under related samples with brain network phenotype. Biostatistics 2024, kxae008. PMID: 38494649, DOI: 10.1093/biostatistics/kxae008.Peer-Reviewed Original ResearchSample relatednessGenetic studiesGenetic association studiesRisk genetic variantsImaging genetics studiesPopulation structureAssociation studiesQuantitative phenotypesQuantitative geneticsGenetic basisGenetic variantsGenetic associationGenetic contributionPhenotypeRelatednessConnectivity traitsNetwork phenotypesConnectivity phenotypesMarkov chain Monte CarloMixed-effects modelsPedigreeGeneticsBiological structuresTraitsHuman Connectome Project