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dc.contributor.author Kim, Dae-Jin
dc.contributor.author Skosnik, Patrick D.
dc.contributor.author Cheng, Hu
dc.contributor.author Pruce, Ben J.
dc.contributor.author Brumbaugh, Margaret S.
dc.contributor.author Vollmer, Jennifer M.
dc.contributor.author Hetrick, William P.
dc.contributor.author O'Donnell, Brian F.
dc.contributor.author Sporns, Olaf
dc.contributor.author Puce, Aina
dc.contributor.author Newman, Sharlene D.
dc.date.accessioned 2019-03-04T17:51:36Z
dc.date.available 2019-03-04T17:51:36Z
dc.date.issued 2011-12
dc.identifier.uri http://hdl.handle.net/2022/22778
dc.description A freely accessible, full text version is available using the link(s) in "Other versions". en
dc.description.abstract Endocannabinoid receptors modulate synaptic plasticity in the brain and may therefore impact cortical connectivity not only during development but also in response to substance abuse in later life. Such alterations may not be evident in volumetric measures utilized in brain imaging, but could affect the local and global organization of brain networks. To test this hypothesis, we used a novel computational approach to estimate network measures of structural brain connectivity derived from diffusion tensor imaging (DTI) and white matter tractography. Twelve adult cannabis (CB) users and 13 healthy subjects were evaluated using a graph theoretic analysis of both global and local brain network properties. Structural brain networks in both CB subjects and controls exhibited robust small-world network attributes in both groups. However, CB subjects showed significantly decreased global network efficiency and significantly increased clustering coefficients (degree to which nodes tend to cluster around individual nodes). CB subjects also exhibited altered patterns of local network organization in the cingulate region. Among all subjects, schizotypal and impulsive personality characteristics correlated with global efficiency but not with the clustering coefficient. Our data indicate that structural brain networks in CB subjects are less efficiently integrated and exhibit altered regional connectivity. These differences in network properties may reflect physiological processes secondary to substance abuse-induced synaptic plasticity, or differences in brain organization that increase vulnerability to substance use. en
dc.language.iso en en
dc.relation.isversionof https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3604771/ en
dc.subject cannabis en
dc.subject delta-9-tetrahydrocannabinol en
dc.subject deterministic tractography en
dc.subject diffusion tensor imaging en
dc.subject graph theory en
dc.subject network analysis en
dc.title Structural Network Topology Revealed by White Matter Tractography in Cannabis Users: A Graph Theoretical Analysis en
dc.type Article en
dc.identifier.doi 10.1089/brain.2011.0053


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