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Research Articles

Functional connectivity in inhibitory control networks and severity of cannabis use disorder

, PhD & , PhD
Pages 382-391 | Received 06 Mar 2013, Accepted 29 Aug 2013, Published online: 07 Nov 2013
 

Abstract

Background: Loss of control is a prominent feature of cannabis use disorders (CUD) and involves orchestrated activity from several brain inhibitory control networks. Objectives: In this study, we determined the associations between inhibitory control network activation and connectivity and CUD severity. Methods: To that end, we compared cannabis-dependent (N = 44) vs. nondependent (N = 30) users during a Stop Signal Task. First, we compared differences in neural response during response inhibition via general linear model analysis within a priori regions of interest. Second, we examined functional connectivity via psychophysiological interaction (PPI) analysis between the right frontal control network (seed region) and inhibitory control networks. Results: There was no significant difference in network activation between cannabis-dependent and nondependent users in any of the inhibitory control networks. However, preliminary findings using the PPI analysis showed that during successful response inhibition, cannabis-dependent users had greater connectivity between right frontal control network and substantia nigra/subthalamic nucleus (STN) network compared to nondependent users (small volume correction, FWE-corrected p < 0.05). Further, multiple regression analyses on the PPI maps showed modulatory effects of age of onset and quantity of cannabis use in the nondependent users. Conclusions: Taken together, these findings suggest that functional connectivity between frontal control and substantia nigra/STN networks during response inhibition is sensitive to the effects of CUD severity unlike behavioral task performance and neural activation in inhibitory control networks. Further, modulators of this connectivity, such as onset and quantity of cannabis use, show attenuated effects with progression of CUD.

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