Alexander Newman's E-Portfolio

Under the mentorship of Dr. Habibeh Khoshbouei, my research project investigates the differential effects of methamphetamine exposure on dopaminergic neuron function between males and females. Dopamine neurons play a crucial role in various functions, with one of their primary roles being the release of dopamine in response to rewarding or pleasurable stimuli. Methamphetamine, a highly potent drug, primarily targets these dopamine neurons, contributing to its strong addictive potential. While both males and females are susceptible to Methamphetamine Use Disorder, females exhibit greater sensitivity, heightened craving, and more frequent relapses. Therefore, we hypothesize that methamphetamine-treated females will display increased dopamine levels and more pronounced behavioral responses compared to their male counterparts. To test this hypothesis, we are employing the conditioned place preference (CPP) model, a widely used paradigm in drug addiction research. We utilize in vivo imaging techniques in freely behaving mice, allowing us to correlate behavioral responses with real-time dopamine activity. A significant aspect of this research involves the application of artificial intelligence (AI) for deep data analysis and developing predicting models. By leveraging AI software, I am able to process large datasets efficiently, enabling precise measurement of dopamine levels and their correlation with behavioral metrics such as speed, total distance traveled, and the CPP index—a key indicator of addiction. The utilization of AI algorithms facilitate the identification of subtle patterns and differences in behavior and dopamine activity that might be overlooked through traditional analysis methods. This research aims to provide valuable insights into the neurobiological and neurobehavioral sex differences in methamphetamine abuse, potentially informing more effective, sex-specific treatment strategies. The integration of AI not only enhances the accuracy and depth of our findings but also represents a step forward in the use of advanced technologies in neuroscience research.