Home Department: undeclared
Mentor: John Huguenard (Neurology & Neurological Sciences and Neurosurgery)

“Machine Learning Classification of Oscillations to Investigate Thalamocortical Network Dysfunction in Autism Spectrum Disorder"

Thalamocortical network dysfunction is increasingly linked to Autism Spectrum Disorder (ASD), a condition affecting ~2.8% of US children. However, with ASD tied to hundreds of genetic variants, underlying mechanisms remain largely unclear. Fuga will record thalamocortical oscillations and analyze existing lab data in Shank3-KO/HCN2-KO mice to extract electrophysiological-oscillatory features, then develop machine learning models to classify the oscillations, theorizing similar network dysfunction and feature significance between the mice. By deducing the features and molecular changes that beget thalamic hyperexcitability, Fuga hypothesizes a novel method—tested by treating the mice with lvabradine—to uncover new mechanisms and treatment options.