Prevalence of smokeless tobacco use among individuals with comorbid other substance dependence

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Aims: Functional magnetic resonance imaging (fMRI) research has indicated the involvement of frontal network in cocaine addiction. Resting-state f MRI approaches have revealed reduced (Kelly, 2011;Munier, 2012) aswell as enhanced (Camchong, 2011) resting state functional connectivity (RSFC) in frontal network in cocaine users relative to control participants. Also, task fMRI research has identified the insula as an important region activated during cocaine craving (Bonson, 2002). We examined the relationship between resting state networks and measures of cocaine use [frequency, money spent per week; duration] in nontreatmentseeking, chronic cocaine smokers. Methods: Ten participants (39–53yrs; 6M;4F) abstinent from cocaine for 72h completed a resting state scan and an anatomical MPRAGE scan. Whole-brain Independent component analysis was performed on resting state fMRI data using FSL’sMELODIC program that identified brain networks representing RSFC of frontalparietal, dorsal-attention, and insula networks. FSL’s regression model then determined any correlations between the activity of these brain networks and cocaine use measures. Results: Activity in frontal-parietal and insula networks was positively correlated with all three outcomes: frequency of use, money spent/week and cocaine use duration. Medial frontal gyrus and inferior parietal lobule [a part of dorsal-attention network (DAN)] positively correlated with each measure. Thus, the increased activity in these brain regions was associated with increased cocaine use. Conclusions: To the best of our knowledge, this is the first study to demonstrate a relationship between RSFC in frontal and insula networks and measures of cocaine use in chronic cocaine smokers. Relationship between the DAN and cocaine use may suggest increased attentional bias to cocaine cues in the environment. As potential network level biomarkers of chronic cocaine use, these identified resting state networks may be usefully applied in treatment development. Financial support: Research supported byNIDAK01DA029047.