Computational Neuroscience for Understanding Epilepsy

Studying patterns in brain electrical activity can provide insights on when a seizure will occur.

During my tenure at Yale School of Medicine (2020-2021) as a computational neuroscience research associate in the Blumenfeld Lab, I developed signal processing pipelines to study and identify indicators of seizure onset. By separating the EEG signals of patients with epilepsy into their frequency subcomponents, I quantified the changes in brain signals before, during, and after a seizure to find patterns that indicate loss of consciousness. With these indicators, the lab is working towards suppressing the seizures with electrical stimulation before they even occur to prevent a loss of consciousness.

This exciting research is under review and will be available online soon!