18 research outputs found
Negative Affect-Associated USV Acoustic Characteristics Predict Future Excessive Alcohol Drinking and Alcohol Avoidance in Male P and NP Rats
BACKGROUND:
Negative emotional status and adverse emotional events increase vulnerability to alcohol abuse. Ultrasonic vocalizations (USVs) emitted by rats are a well-established model of emotional status that can reflect positive or negative affective responses in real time. Most USV studies assess counts, yet each USV is a multidimensional data point characterized by several acoustic characteristics that may provide insight into the neurocircuitry underlying emotional response.
METHODS:
USVs emitted from selectively bred alcohol-naïve and alcohol-experienced alcohol-preferring and nonpreferring rats (P and NP rats) were recorded during 4-hour sessions on alternating days over 4 weeks. Linear mixed modeling (LMM) and linear discriminant analysis (LDA) were applied to USV acoustic characteristics (e.g., frequency, duration, power, and bandwidth) of negative affect (22 to 28 kilohertz [kHz])- and positive (50 to 55 kHz) affect-related USVs.
RESULTS:
Hundred percent separation between alcohol-naïve P and NP rats was achieved through a linear combination (produced by LDA) of USV acoustic characteristics of 22- to 28-kHz USVs, whereas poor separation (36.5%) was observed for 50- to 55-kHz USVs. 22- to 28-kHz LDA separation was high (87%) between alcohol-experienced P and NP rats, but was poor for 50- to 55-kHz USVs (57.3%). USV mean frequency and duration were the highest weighted characteristics in both the naïve and experienced 22- to 28-kHz LDA representations suggesting that alcohol experience does not alter the representations. LMM analyses of 22- to 28-kHz USV acoustic characteristics matched the LDA results. Poor LDA separation was observed between alcohol-naïve and alcohol-experienced P rats for both 22- to 28-kHz and 50- to 55-kHz USVs.
CONCLUSIONS:
Advanced statistical analysis of negative affect-associated USV data predicts future behaviors of excessive alcohol drinking and alcohol avoidance in selectively bred rats. USV characteristics across rat lines reveal affect-related motivation to consume alcohol and may predict neural pathways mediating emotional response. Further characterization of these differences could delineate particular neurocircuitry and methods to ameliorate dysregulated emotional states often observed in human alcohol abusers
Sex differences in cognitive performance and alcohol consumption in High Alcohol-Drinking (HAD-1) rats
Excessive alcohol (ethanol) consumption negatively impacts social, emotional, as well as cognitive function and well-being. Thus, identifying behavioral and/or biological predictors of excessive ethanol consumption is important for developing prevention and treatment strategies against alcohol use disorders (AUDs). Sex differences in alcohol consumption patterns are observed in humans, primates, and rodents. Selectively bred high alcohol-drinking rat lines, such as the “HAD-1” lines are recognized animal models of alcoholism. The present work examined sex differences in alcohol consumption, object recognition, and exploratory behavior in male and female HAD-1 rats. Naïve male and female HAD-1 rats were tested in an object recognition test (ORT) prior to a chronic 24 h intermittent ethanol access procedure for five weeks. Object recognition parameters measured included exploratory behavior, object investigation, and time spent near objects. During the initial training trial, rearing, active object investigation and amount of time spent in the object-containing section was significantly greater in female HAD-1 rats compared to their male counterparts. During the subsequent testing trial, time spent in the object-containing section was greater in female, compared to male, rats; but active object investigation and rearing did not statistically differ between females and males. In addition, female HAD-1 rats consumed significantly more ethanol than their male counterparts, replicating previous findings. Moreover, across all animals there was a significant positive correlation between exploratory behavior in ORT and ethanol consumption level. These results indicate there are significant sex differences in cognitive performance and alcohol consumption in HAD-1 rats, which suggests neurobiological differences as well
Recommended from our members
Suboptimal Criterion Learning in Static and Dynamic Environments
Humans often make decisions based on uncertain sensory information. Signal detection theory (SDT) describes detection and discrimination decisions as a comparison of stimulus "strength" to a fixed decision criterion. However, recent research suggests that current responses depend on the recent history of stimuli and previous responses, suggesting that the decision criterion is updated trial-by-trial. The mechanisms underpinning criterion setting remain unknown. Here, we examine how observers learn to set a decision criterion in an orientation-discrimination task under both static and dynamic conditions. To investigate mechanisms underlying trial-by-trial criterion placement, we introduce a novel task in which participants explicitly set the criterion, and compare it to a more traditional discrimination task, allowing us to model this explicit indication of criterion dynamics. In each task, stimuli were ellipses with principal orientations drawn from two categories: Gaussian distributions with different means and equal variance. In the covert-criterion task, observers categorized a displayed ellipse. In the overt-criterion task, observers adjusted the orientation of a line that served as the discrimination criterion for a subsequently presented ellipse. We compared performance to the ideal Bayesian learner and several suboptimal models that varied in both computational and memory demands. Under static and dynamic conditions, we found that, in both tasks, observers used suboptimal learning rules. In most conditions, a model in which the recent history of past samples determines a belief about category means fit the data best for most observers and on average. Our results reveal dynamic adjustment of discrimination criterion, even after prolonged training, and indicate how decision criteria are updated over time