There is growing interest in non-invasive brain stimulation (NIBS) as a novel treatment option for substance-use disorders (SUDs). Recent momentum stems from a foundation of preclinical neuroscience demonstrating links between neural circuits and drug consuming behavior, as well as recent FDA-approval of NIBS treatments for mental health disorders that share overlapping pathology with SUDs. As with any emerging field, enthusiasm must be tempered by reason; lessons learned from the past should be prudently applied to future therapies. Here, an international ensemble of experts provides an overview of the state of transcranial-electrical (tES) and transcranial-magnetic (TMS) stimulation applied in SUDs. This consensus paper provides a systematic literature review on published data-emphasizing the heterogeneity of methods and outcome measures while suggesting strategies to help bridge knowledge gaps. The goal of this effort is to provide the community with guidelines for best practices in tES/TMS SUD research. We hope this will accelerate the speed at which the community translates basic neuroscience into advanced neuromodulation tools for clinical practice in addiction medicine.

Based upon previous reports of alterations in white matter integrity and gray matter density in smokers, we examined these markers in a large, well-matched sample of smokers and non-smokers. We further investigated the effect of heavy cigarette exposure by using pack-years and the effects of two relatively stable, highly heritable traits in smokers (Fagerström Test of Nicotine Dependence (FTND), a measure of severity of nicotine dependence so and Toronto Alexithymia Scale (TAS-20), measuring a stable personality trait related to smoking. Forty-eight nicotine-dependent subjects and 48 matched controls were included in the analyses, with smokers also subdivided into high/low dependence and high/low pack-years smokers. White matter integrity (fractional anisotropy (FA)) and gray matter density (voxel-based morphometry (VBM)) were measured and compared across groups. Gray matter density was lower in left prefrontal cortex (PFC) in high pack-years smokers and was inversely related to pack-years. In contrast, left insular cortex gray matter density was higher in smokers and associated with TAS-20 total score and with difficulty-identifying-feelings factor. Further, the most highly dependent smokers showed lower prefrontal FA, which was negatively correlated with FTND. There was no correlation between pack-years and FTND in our smoker population. These data suggest chronic tobacco use is correlated with prefrontal gray matter damage , while differences in insula gray matter and PFC white matter appear to reflect stable and heritable differences between smokers and non-smokers.

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Increasing neuroimaging evidence suggests an association between impulsive decision-making behavior and task-related brain activity. However, the relationship between impulsivity in decision-making and resting-state brain activity remains unknown. To address this issue, we used functional MRI to record brain activity from human adults during a resting state and during a delay discounting task (DDT) that requires choosing between an immediate smaller reward and a larger delayed reward. In experiment I, we identified four DDTrelated brain networks. The money network (the striatum, posterior cingulate cortex, etc.) and the time network (the medial and dorsolateral prefrontal cortices, etc.) were associated with the valuation process; the frontoparietal network and the dorsal anterior cingulate cortex-anterior insular cortex network were related to the choice process. Moreover, we found that the resting-state functional connectivity of the brain regions in these networks was significantly correlated with participants' discounting rate, a behavioral index of impulsivity during the DDT. In experiment II, we tested an independent group of subjects and demonstrated that this resting-state functional connectivity was able to predict individuals' discounting rates. Together, these findings suggest that resting-state functional organization of the human brain may be a biomarker of impulsivity and can predict economic decision-making behavior.