Colloquium: Graduate Portfolio in Scientific Computation

The Spring Research Colloquium for Graduate Portfolio in Scientific Computation is scheduled for Thursday, May 4, 11-11:30 AM in GDC 7.402.






Nitish Mittal Thursday, May 4 11:00–11:30 AM GDC 7.402 "Use of Ultrasonic Vocalization Data to Predict Future Alcohol Consumption in Rats"

Nitish Mittal 

(PhD, Pharmacuetical Sciences, College of Pharmacy, supervised by Dr. Greg Hixon)

Title: "Use of Ultrasonic Vocalization Data to Predict Future Alcohol Consumption in Rats"

Abstract: Excessive alcohol consumption has a vast, negative impact on society. Rodent models have been successful in furthering our understanding of the biological underpinnings that drive alcohol consumption. Rodents emit ultrasonic vocalizations (USVs) that are each composed of several acoustic characteristics (e.g., frequency, duration, power and bandwidth).  USVs reflect neurotransmitter activity in dopaminergic and cholinergic neurotransmitter systems and thus serve as non-invasive, real-time biomarkers of dopaminergic and cholinergic neurotransmission. In the present study, we recorded spontaneously emitted USVs from alcohol-naïve Long-Evans (LE) rats and then measured their alcohol intake. We combined the USV acoustic characteristics and alcohol consumption data from LE rats with previously published data from selectively bred high- (P and HAD-1) and low-alcohol (NP and LAD-1) drinking strains from studies with the same experimental method. Predictive analytic techniques were applied simultaneously to this combined data set and revealed that: (a) alcohol-naïve USVs accurately discriminated among high-alcohol consuming, LE, and low-alcohol consuming rat lines, and (b) future alcohol consumption in these same rat lines was reliably predicted from the alcohol-naïve USV profiles. Because USV acoustic characteristics are sensitive to underlying neural activity, these findings suggest that rodent alcohol consumption can be predicted from differences in baseline cholinergic and dopaminergic tone.