Analyzing complex functional brain networks: fusing statistics and network science to understand the brain

DOI10.1214/13-SS103zbMath1279.92021arXiv1302.5721WikidataQ34303942 ScholiaQ34303942MaRDI QIDQ389932

F. DuBois Bowman, Sean L. Simpson, Paul J. Laurienti

Publication date: 22 January 2014

Published in: Statistics Surveys (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1302.5721

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Neural biology (92C20) Systems biology, networks (92C42)

Related Items (11)

Identifying functional co‐activation patterns in neuroimaging studies via poisson graphical models ⋮ Convergence of covariance and spectral density estimates for high-dimensional locally stationary processes ⋮ Network Structure Learning Under Uncertain Interventions ⋮ A random effects stochastic block model for joint community detection in multiple networks with applications to neuroimaging ⋮ THE AVERAGE WEIGHTED PATH LENGTH FOR A CLASS OF HIERARCHICAL NETWORKS ⋮ Exponential-family models of random graphs: inference in finite, super and infinite population scenarios ⋮ Bayesian inference and testing of group differences in brain networks ⋮ A Bayesian hierarchical framework for modeling brain connectivity for neuroimaging data ⋮ Model-free two-sample test for network-valued data ⋮ Exploring dependence structures in the international arms trade network: A network autocorrelation approach ⋮ Online network monitoring

Uses Software

• GenLouvain
• Brain Connectivity Toolbox

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