Dynamical Systems Seminar: Francois Meyer

Decoding Epileptogenesis in a Reduced State Space

Francois Meyer

Department of Electrical, Computer, and Energy Engineering; University of Colorado Boulder

Date and time: 

Thursday, October 8, 2015 - 2:00pm

Location: 

ECCR 257

Abstract: 

In many areas of science the only method to study a complex system entails making indirect time-resolved measurements of the state of the system. In the absence of a detailed mathematical model that can be used to explain the measurements, we have to resort to machine learning methods to learn the association between the state of the system and the measurements. An example of such a problem involves the definition of a biomarker to monitor epileptogenesis following a traumatic brain injury.

In this talk I will describe the recent results of a multidisciplinary effort to actively and continuously decode the progressive changes in neural network organization leading to epilepsy. Using an animal model of acquired epilepsy, we chronically recorded hippocampal auditory evoked potentials during epileptogenesis.  Our approach combines in a unique manner applied harmonic analysis, spectral graph theory, and state-space models to infer the hidden distinct stages of epileptogenesis. Using our decoding algorithm, we were able to show that archetypal changes in the waveform morphology have universal predictive value for the development of spontaneous recurrent seizures.

This work was done in collaboration with Daniel Barth, Alexander M. Benison,  Zachariah Smith, and Lukas Ruediger Nels Goetz-Weiss