Decision-making (DM) impairments are important predictors of cannabis initiation and continued use. In cannabis users, how decision-making abnormalities related to structural and functional connectivity in the brain are not fully understood. We employed a three-method multimodal image analysis and multivariate pattern analysis (MVPA) on high dimensional 7 tesla MRI images examining functional connectivity, white matter microstructure and gray matter volume in a group of cannabis users and non-users. Neuroimaging and cognitive analyses were performed on 92 CU and 92 age- matched NU from a total of 187 7T scans. CU were selected on the basis of their scores on the Semi-Structured Assessment for the Genetics of Alcoholism. The groups were first compared on a decision-making test and then on ICA based functional connectivity between corticocerebellar networks. An MVPA was done as a confirmatory analysis. The anatomy of these networks was then assessed using Diffusion Tensor imaging (DTI) and cortical volume analyses. Cannabis Users had significantly higher scores on the Iowa Gambling task (IGT) [Gambling task Percentage larger] and significantly lower scores on the [Gambling task reward Percentage smaller]. Left accumbens (L NAc) volume was significantly larger in cannabis users. DTI analysis between the groups yielded no significant (FWE corrected) differences. Resting state FC analysis of the left Cerebellum region 9 showed enhanced functional connectivity with the right nucleus accumbens and left pallidum and left putamen in CU. In addition, posterior cerebellum showed enhanced functional connectivity (FWE corrected) with 2 nodes of the DMN and left and right paracingulate (sub genual ACC) and the sub callosal cortex in CU. IGT percentage larger scores correlated with posterior cerebellar functional connectivity in non-user women. A multivariate pattern analysis confirmed this cerebellar hyperconnectivity in both groups. Our results demonstrate for the first time that deficits in DM observed in cannabis users are mirrored in hyper connectivity in corticocerebellar networks. Cortical volumes of some of the nodes of these networks showed increases in users. However, the underlying white matter was largely intact in CU. The observed DM deficits and hyper connectivity in resting networks may contribute to difficulties in quitting and/or facilitating relapse.
Keywords: 7 Tesla MRI imaging; Cannabis; Cerebellum; Cortical volume; Decision making; Diffusion Tensor imaging; Marijuana; Multimodal imaging; Multivariate pattern analysis; Networks; Resting state functional connectivity.
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