Structural Network Topology Revealed by White Matter Tractography in Cannabis Users

A Graph Theoretical Analysis

Dae Jin Kim, Patrick D. Skosnik, hu Cheng, Ben J. Pruce, Margaret S. Brumbaugh, Jennifer M. Vollmer, William P. Hetrick, Brian O'Donnell, Olaf Sporns, Aina Puce, Sharlene D. Newman

Research output: Contribution to journalArticle

21 Citations (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)473-483
Number of pages11
JournalBrain Connectivity
Volume1
Issue number6
DOIs
StatePublished - Dec 1 2011

Fingerprint

Cannabis
Brain
Neuronal Plasticity
Substance-Related Disorders
Cluster Analysis
Physiological Phenomena
Endocannabinoids
Diffusion Tensor Imaging
Gyrus Cinguli
White Matter
Neuroimaging
Personality
Healthy Volunteers

Keywords

  • cannabis
  • delta-9-tetrahydrocannabinol
  • deterministic tractography
  • diffusion tensor imaging
  • graph theory
  • network analysis

ASJC Scopus subject areas

  • Neuroscience(all)
  • Medicine(all)

Cite this

Kim, D. J., Skosnik, P. D., Cheng, H., Pruce, B. J., Brumbaugh, M. S., Vollmer, J. M., ... Newman, S. D. (2011). Structural Network Topology Revealed by White Matter Tractography in Cannabis Users: A Graph Theoretical Analysis. Brain Connectivity, 1(6), 473-483. https://doi.org/10.1089/brain.2011.0053

Structural Network Topology Revealed by White Matter Tractography in Cannabis Users : A Graph Theoretical Analysis. / Kim, Dae Jin; Skosnik, Patrick D.; Cheng, hu; Pruce, Ben J.; Brumbaugh, Margaret S.; Vollmer, Jennifer M.; Hetrick, William P.; O'Donnell, Brian; Sporns, Olaf; Puce, Aina; Newman, Sharlene D.

In: Brain Connectivity, Vol. 1, No. 6, 01.12.2011, p. 473-483.

Research output: Contribution to journalArticle

Kim, DJ, Skosnik, PD, Cheng, H, Pruce, BJ, Brumbaugh, MS, Vollmer, JM, Hetrick, WP, O'Donnell, B, Sporns, O, Puce, A & Newman, SD 2011, 'Structural Network Topology Revealed by White Matter Tractography in Cannabis Users: A Graph Theoretical Analysis', Brain Connectivity, vol. 1, no. 6, pp. 473-483. https://doi.org/10.1089/brain.2011.0053
Kim, Dae Jin ; Skosnik, Patrick D. ; Cheng, hu ; Pruce, Ben J. ; Brumbaugh, Margaret S. ; Vollmer, Jennifer M. ; Hetrick, William P. ; O'Donnell, Brian ; Sporns, Olaf ; Puce, Aina ; Newman, Sharlene D. / Structural Network Topology Revealed by White Matter Tractography in Cannabis Users : A Graph Theoretical Analysis. In: Brain Connectivity. 2011 ; Vol. 1, No. 6. pp. 473-483.
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