Computational and Mathematical Methods in Medicine
Volume 8 (2007), Issue 4, Pages 225-234
doi:10.1080/17486700701528970
Original Article

Analysis of Seizure EEG in Kindled Epileptic Rats

A. K. Sen,1 M. J. Kubek,2 and H. E. Shannon3

1Department of Mathematical Sciences, Indiana University, Indianapolis, IN 46202, USA
2Department of Anatomy and Cell Biology, Indiana University School of Medicine, Indianapolis, IN 46202, USA
3Division of CNS Research, Eli Lilly and Company, Lilly Corporate Center, Indianapolis, IN 46285, USA

Received 11 August 2006; Revised 16 May 2007; Accepted 20 June 2007

Copyright © 2007 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Using wavelet analysis we have detected the presence of chirps in seizure EEG signals recorded from kindled epileptic rats. Seizures were induced by electrical stimulation of the amygdala and the EEG signals recorded from the amygdala were analyzed using a continuous wavelet transform. A time–frequency representation of the wavelet power spectrum revealed that during seizure the EEG signal is characterized by a chirp-like waveform whose frequency changes with time from the onset of seizure to its completion. Similar chirp-like time–frequency profiles have been observed in newborn and adult patients undergoing epileptic seizures. The global wavelet spectrum depicting the variation of power with frequency showed two dominant frequencies with the largest amounts of power during seizure. Our results indicate that a kindling paradigm in rats can be used as an animal model of human temporal lobe epilepsy to detect seizures by identifying chirp-like time–frequency variations in the EEG signal.