Abstracts

Epilepsy research for the design of seizure detection/prediction neuroprosthetics has been faced with the search for electrophysiologic control parameters that can be used to infer the epileptic state of the animal and be leveraged at a later time to deliver neurotherapeutic feedback. The analysis presented here uses multi-microelectrode array technology to provide a fundamental neurophysiologic quantification of an ensemble of hippocampal neurons during epileptogenesis. Multichannel neuronal potentials were collected synchronously over the course of two months from a rat developing epilepsy after being subjected to an hour of electrically-induced status epilepticus. Arrays of tungsten microwire electrodes were stereotaxically implanted in the dentate and CA1-2 of the hippocampus. Neuronal ensemble activity was recorded at 24414.1Hz and spike sorting was implemented to discriminate and track single unit activity over the study duration. Electrode placement and CA1-2/Dentate targeting were verified post-mortem using a high-field (17.6 Tesla) MRI instrument. At the microscopic level, single unit spike train statistical analysis revealed an increase in the coefficient of variation (CV) of the interspike intervals of the dentate and CA1-2 neurons. Temporal increases in CV indicated a modulation of irregular bursting activity. At the mesoscopic level, linear predictive modeling (LPC) applied to local segments of raw ensemble recordings confirmed an increase in the number of temporal bursts that vary in amplitude and duration. Long term single unit activity analysis suggests that hippocampal neurons in both CA1-2 and dentate regions increase the frequency and duration of their bursting activity after injury to the contra-lateral hippocampus and during the latent period of epileptogenesis. The trends inferred from both scales of analysis suggest that the evolution into epilepsy is not abrupt but evolves gradually from the time of injury. (Supported by National Institutes of Health, National Science Foundation, Children[apos]s Miracle Network.)