BME MS Defense: Sneha Narayanan

The Dynamic Structure of Ictogenesis in an Experimental Model of Focal Epilepsy

Supervised by Prof. David Pinto

Abstract

The onset of an epileptic event, or ictogenesis, is deceptively simple to understand. A group of errant neurons become active and recruit activity in other neurons until a threshold is reached and the neuronal network explodes into an epileptic event. Describing the mathematics of this process rigorously, however, is more difficult. How can we use standard nonlinear analysis to frame the concept of network threshold? What experiments might we perform that can translate dynamic parameters into testable hypotheses? How can abstract concepts from dynamic systems lead to meaningful insights into clinical epilepsy? Our goal in this project is to answer these questions.

Understanding the dynamics of ictogenesis entails both mathematical and experimental methods. Mathematically, we use concepts from nonlinear analysis to derive a two-parameter model of a double-well potential that describes network threshold. We then use the model to design specific experimental methods to relate directly experimental data with model parameters. Finally, we carry out one of our proposed experiments to demonstrate how our model analysis can capture differences in the ictogenic properties between a region of the brain known for epileptic activity (piriform cortex) versus a region that is clinically stable (somatosensory cortex).

Taken together, our results suggest that our nonlinear model effectively describes the dynamics of experimental ictogenesis. These results represent a first step toward using nonlinear dynamics for devising targeted control strategies for preventing an epileptic event before it starts.