Corticostriatal oscillations predict high vs. low drinkers in a preclinical model of limited access alcohol consumption

Abstract

Alcohol use disorders (AUDs) affect a large proportion of individuals in the United States.Unfortunately, the current therapies to treat AUDs are largely ineffective. Deep brain stimulation (DBS) has been proposed as a promising therapy for AUDs, but the high individual variability in treatment response limits broader implementation of this approach.The corticostriatal circuit is key in processing the rewarding properties of alcohol and we hypothesize that we can identify neural features within this circuit that will predict individual response to DBS in order to maximize treatment outcomes. In the current experiment, local field potentials (LFPs) were recorded from the nucleus accumbens shell (NAcSh) and medial prefrontal cortex (mPFC) of male Sprague-Dawley rats (n=13). The impact of NAcSh and mPFC DBS on levels of alcohol consumption was subsequently evaluated. On a population level, DBS in either region failed to significantly alter alcohol drinking behavior due to high individual variability in response. However, when individual features of corticostriatal LFPs were used as predictors of alcohol drinking outcomes (decreasers, increasers, or nonresponders to DBS) for each rat using a machine-learning approach (lasso), response to DBS could be predicted with greater accuracy than expected by chance. These data suggest that individual differences in corticostriatal circuit activity prior to stimulation likely contributes to the variable responses to DBS therapy. Ultimately, we hope to use knowledge gained from these data to tailor DBS therapies to individuals, further enhancing treatment efficacy.All rights reserved. No reuse allowed without permission.was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.