The impact of chronic daily nicotine exposure and its overnight withdrawal on the structure of anxiety-related behaviors in rats: Role of the lateral habenula.

Tobacco smoking is a serious health problem worldwide and a leading cause of mortality. Nicotine, the addictive component of tobacco, affects a range of emotional responses, including anxiety-related behaviors. Although perceived by smokers to be anxiolytic, evidence suggests that smoking increases anxiety and that mood fluctuates with nicotine intake. Thus, nicotine addiction may depend on easing the psychobiological distress caused by its abuse. The lateral habenula (LHb) has been implicated as a neural substrate for acute nicotine-induced anxiety, but its role in anxiety-like behaviors associated with chronic nicotine exposure has not been explored. Here, we assessed the effect of chronic nicotine exposure and its subsequent overnight withdrawal on anxiety-like behavior using both quantitative and multivariate T-pattern analysis in rats tested using the hole-board apparatus. Additionally, we explored the role of the LHb by comparing the behavioral effects of short-term nicotine withdrawal in chronically treated LHb-lesioned rats. Quantitative analysis revealed increased anxiety-like behavior in chronically treated overnight nicotine-deprived rats, as manifested in reduced general and focused exploratory behaviors, which was eased in animals that received nicotine. Quantitative analysis failed to reveal a role of the LHb in overnight nicotine deprivation-induced anxiety. Conversely, T-pattern analysis of behavioral outcomes revealed that chronic nicotine-treated rats still show anxiety-like behavior following nicotine challenge. Moreover, it demonstrated that the LHb lesion induced a stronger anxiolytic-like response to the acute challenge of nicotine in chronically nicotine-exposed animals, implicating the LHb in the anxiogenic effect of chronic nicotine exposure. These data further highlight the LHb as a promising target for smoking cessation therapies and support the importance of T-pattern analysis for behavioral analysis.