Abstract
Individuals differ in their vulnerability to develop alcohol dependence, which is determined by innate and environmental factors. The corticostriatal circuit is heavily involved in the development of alcohol dependence and may contain neural information regarding vulnerability to drink excessively. In the current experiment, we hypothesized that we could characterize high and low alcohol-drinking rats (HD and LD, respectively) based on corticostriatal oscillations and that these subgroups would differentially respond to corticostriatal brain stimulation. Male Sprague–Dawley rats (n = 13) were trained to drink 10% alcohol in a limited access paradigm. In separate sessions, local field potentials (LFPs) were recorded from the nucleus accumbens shell (NAcSh) and medial prefrontal cortex (mPFC). Based on training alcohol consumption levels, we classified rats using a median split as HD or LD. Then, using machine-learning, we built predictive models to classify rats as HD or LD by corticostriatal LFPs and compared the model performance from real data to the performance of models built on data permutations. Additionally, we explored the impact of NAcSh or mPFC stimulation on alcohol consumption in HD vs. LD. Corticostriatal LFPs were able to predict HD vs. LD group classification with greater accuracy than expected by chance (>80% accuracy). Moreover, NAcSh stimulation significantly reduced alcohol consumption in HD, but not LD (p < 0.05), while mPFC stimulation did not alter drinking behavior in either HD or LD (p > 0.05). These data collectively show that the corticostriatal circuit is differentially involved in regulating alcohol intake in HD vs. LD rats, and suggests that corticostriatal activity may have the potential to predict a vulnerability to develop alcohol dependence in a clinical population.
Highlights
Excessive alcohol consumption is a major health concern in the United States, leading to approximately 88,000 deaths per year (Centers for Disease Control and Prevention, 2013), but only a small proportion of individuals who drink alcohol become dependent later in adulthood (Costanzo et al, 2007)
Using single feature logistic regression models, we identified the following neural features as containing significant information regarding HD vs. LD: right nucleus accumbens shell (NAcSh) lγ, right medial prefrontal cortex (mPFC) lγ, right NAcSh—left NAcSh α, right NAcSh—right mPFC hγ, and left mPFC—right mPFC hγ
We show that corticostriatal oscillations can be used to classify rats as HD or LD better than chance predictions, indicating that information regarding vulnerability to excessive alcohol consumption can be extracted from neural oscillations
Summary
Excessive alcohol consumption is a major health concern in the United States, leading to approximately 88,000 deaths per year (Centers for Disease Control and Prevention, 2013), but only a small proportion of individuals who drink alcohol become dependent later in adulthood (Costanzo et al, 2007). A combination of environmental and genetic risk factors are associated with the development of alcohol dependence in humans, and these risk factors produce significant characteristic neurobiological effects (Hägele et al, 2014; Matosicet al., 2016). Rats selectively bred to be high drinkers show neural and behavioral phenotypes related to alcohol dependence (e.g., relapse behavior, altered dopamine signaling in the striatum, etc; McBride and Li, 1998; Crabbe, 2014). There are significant variations in alcohol intake levels, so rodent models of limited access alcohol consumption have been employed to attempt to further study the neurobiological readouts of risk factors associated with the development of alcohol dependence. Additional work is needed, to understand how systems-level neural activity relates to the HD phenotype in rats
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