Abstracts

NONLINEAR ANALYSIS OF HIGH-RESOLUTION MICROWIRE ELECTRODE DATA FROM A CHRONIC LIMBIC EPILEPSY MODEL OVER THE LATENT PERIOD

Abstract number : 2.098
Submission category :
Year : 2005
Submission ID : 5402
Source : www.aesnet.org
Presentation date : 12/3/2005 12:00:00 AM
Published date : Dec 2, 2005, 06:00 AM

Authors :
1Jennifer D. Simonotto, 2Justin Sanchez, 2Wendy L. Norman, 1Michael D. Furman, 2Paul R. Carney, and 1William L. Ditto

Epilepsy affects 3-5% of the population worldwide, affecting persons indiscriminately of age, sex or race. In the vast majority of cases, seizures arise from medial temporal structures that have been damaged months to years before onset of seizures. By characterizing the latent development of epilepsy from traumatic insult to onset in the chronic limbic epilepsy rat model (a realistic animal model for human temporal lobe epilepsy and epileptogenesis), essential relationships between onset pathology and remodeling of the neural tissue can be determined. An array of 32 microwires were implanted into the hippocampus of animals which were then stimulated in the manner prescribed for the Chronic Limbic Epilepsy model. After the initial seizure brought on by the stimulation, the animals were recorded at high sampling rate (12-25 kHz). The animals typically had a latent period of 4-8 weeks, during which no seizures were evident, but over time the electrical activity of different regions typically became more similar. We analyzed the data using synchronization, entropy, spectal, and coherence measures across channels to characterize this change. Initially, channels from similar regions displayed characteristics which were the most similar, but gradually over time the magnitude of differences changed. Phase differences between channels were seen to reverse immediately before a seizure, implying a change in the order of information flow in the hippocampus. Coherence was highest during spiking bursts across all channels, even when the behavior was not classified as a seizure, while the entropy was lowest at such times. Spectrograms revealed energy at high frequencies ([gt] 2000 Hz) during such spiking periods and high frequency oscillation events. This work, in conjunction with collaborators[apos] work on histology, high resolution MRI and studies of single unit firing, is a unique undertaking which we hope will lead to greater understanding of the latent period and the remodelling underlying epilepsy. (Supported by CRCNS Evolution into Epilepsy Grant
1R01EB004752-01 William L. Ditto University of Florida.)