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Graphical Structural Learning of rs-fMRI data in Heavy Smokers

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arxiv 2409.08395 v2 pith:5STDEU2R submitted 2024-09-12 q-bio.QM cs.LGstat.AP

classification q-bio.QMcs.LGstat.AP
keywords brainchangessmokersconnectionsdatagraphicalgraphsheavy
verification ladder T0 review T1 audit T2 compute T3 formal
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Recent studies revealed structural and functional brain changes in heavy smokers. However, the specific changes in topological brain connections are not well understood. We used Gaussian Undirected Graphs with the graphical lasso algorithm on rs-fMRI data from smokers and non-smokers to identify significant changes in brain connections. Our results indicate high stability in the estimated graphs and identify several brain regions significantly affected by smoking, providing valuable insights for future clinical research.

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Cited by 3 Pith papers

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