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Brain Structure and Function

, Volume 223, Issue 7, pp 3317–3326 | Cite as

Differential associations of combined vs. isolated cannabis and nicotine on brain resting state networks

  • Francesca M. FilbeyEmail author
  • Suril Gohel
  • Shikha Prashad
  • Bharat B. Biswal
Original Article

Abstract

Concomitant cannabis and nicotine use is more prevalent than cannabis use alone; however, to date, most of the literature has focused on associations of isolated cannabis and nicotine use limiting the generalizability of existing research. To determine differential associations of concomitant use of cannabis and nicotine, isolated cannabis use and isolated nicotine use on brain network connectivity, we examined systems-level neural functioning via independent components analysis (ICA) on resting state networks (RSNs) in cannabis users (CAN, n = 53), nicotine users (NIC, n = 28), concomitant nicotine and cannabis users (NIC + CAN, n = 26), and non-users (CTRL, n = 30). Our results indicated that the CTRL group and NIC + CAN users had the greatest functional connectivity relative to CAN users and NIC users in 12 RSNs: anterior default mode network (DMN), posterior DMN, left frontal parietal network, lingual gyrus, salience network, right frontal parietal network, higher visual network, insular cortex, cuneus/precuneus, posterior cingulate gyrus/middle temporal gyrus, dorsal attention network, and basal ganglia network. Post hoc tests showed no significant differences between (1) CTRL and NIC + CAN and (2) NIC and CAN users. These findings of differential associations of isolated vs. combined nicotine and cannabis use demonstrate an interaction between cannabis and nicotine use on RSNs. These unique and combined mechanisms through which cannabis and nicotine influence cortical network functional connectivity are important to consider when evaluating the neurobiological pathways associated with cannabis and nicotine use.

Keywords

Addiction Cannabis Nicotine Resting state fMRI Functional connectivity Independent component analysis 

Notes

Acknowledgements

This study was funded by the National Institutes of Health (grants K01 DA021632, R01DA030344-01A1, and R01 DA038895).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Francesca M. Filbey
    • 1
    Email author
  • Suril Gohel
    • 3
  • Shikha Prashad
    • 1
  • Bharat B. Biswal
    • 2
  1. 1.Center for BrainHealth, School of Behavioral and Brain SciencesUniversity of Texas at DallasDallasUSA
  2. 2.Department of Biomedical EngineeringNew Jersey Institute of TechnologyNewarkUSA
  3. 3.Department of Health Informatics, School of Health ProfessionsRutgers UniversityNewarkUSA

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