I worked as a research assistant in a neuroscience lab for 2 years. During my time there I got to work directly with Principal Investigators across 5 different projects to better understand the role of specific brain features in regulating sleep and wakefulness, and ultimately find new clinical treatments for sleep disorders.

The projects I worked on focused on analyzing how neural structures in the basal forebrain regulate sleep/wake cycles, investigating the role of specific GABA receptors in controlling sleep depth, and identifying the neural correlates of sleep homeostasis. 

Thanks to my wonderful mentors, I learned a wide range of technical lab skills like stereotaxic surgery, opto/chemogenetic stimulation, perfusion, microtome sectioning, immunohistochemistry, brain imaging, and sleep-scoring.

I also worked on a sleep-scoring program that used machine learning to automatically classify mouse EEG/EMG data into "Wake," "NREM," "REM," or "Artifact" categories. The neural network model we trained reduced the time it takes to score a 24-hour sleep recording from about 6 hours to 10 minutes while performing at 90% accuracy on average. 

Here is a demo of the GUI I created for the program using the plotly python library: