Abstract
BACKGROUND: Alcohol withdrawal syndrome (AWS) results from the sudden cessation of chronic alcohol use and is associated with high morbidity and mortality. Alcohol withdrawal-induced central nervous system (CNS) hyperexcitability results from complex, compensatory changes in synaptic efficacy and intrinsic excitability. These changes in excitability counteract the depressing effects of chronic ethanol on neural transmission and underlie symptoms of AWS, which range from mild anxiety to seizures and death. The development of targeted pharmacotherapies for treating AWS has been slow, due in part to the lack of available animal models that capture the key features of human AWS. Using a unique optogenetic method of probing network excitability, we examined electrophysiologic correlates of hyperexcitability sensitive to early changes in CNS excitability. This method is sensitive to pharmacologic treatments that reduce excitability and may represent a platform for AWS drug development. METHODS: We applied a newly developed method, the optogenetic population discharge threshold (oPDT), which uses light intensity response curves to measure network excitability in chronically implanted mice. Excitability was tracked using the oPDT before, during, and after the chronic intermittent exposure (CIE) model of alcohol withdrawal (WD). RESULTS: Alcohol withdrawal produced a dose-dependent leftward shift in the oPDT curve (denoting increased excitability), which was detectable in as few as three exposure cycles. This shift in excitability mirrored an increase in the number of spontaneous interictal spikes during withdrawal. In addition, Withdrawal lowered seizure thresholds and increased seizure severity in optogenetically kindled mice. CONCLUSION: We demonstrate that the oPDT provides a sensitive measure of alcohol withdrawal-induced hyperexcitability. The ability to actively probe the progression of excitability without eliciting potentially confounding seizures promises to be a useful tool in the preclinical development of next-generation pharmacotherapies for AWS.