Applying a Machine Learning Method to Detect Changing Neuronal Activity in Seizure Disorders

This study aims to use machine learning to find miniature excitatory postsynaptic currents (EPSCs) in neurons of a Drosophila to find behavior markers of a seizure. Using MATLAB, we are training a machine learning model on electrophysiological data to recognize patterns of post-synaptic events that show potential seizure activity. We have faced challenges applying this method and we are planning to present these in our poster. The results of this research may help develop a further understanding of seizure mechanisms in Drosophila that could translate into a more in-depth understanding for neurological disorders in humans.