The proposed research is based upon three key discoveries made during the initial funding period of this project. These discoveries resulted from the application of nonlinear analytic techniques to the study of intracranial electroencephalographic (EEG) recordings performed in patients with medically intractable seizures of anterior mesial temporal (AMT) origin. First, in the interictal state, signals generated by the epileptogenic AMT focus exhibit dynamical characteristics that distinguish them from those recorded from other areas of the hippocampus and cerebral cortex. This discovery offers the possibility of improved methods for localizing the epileptogenic focus, obviating the need to record multiple seizures, and identifying patients that are most likely to experience seizure control following surgery. Second, AMT seizures are preceded by a characteristic spatiotemporal transition process that begins up to l hour prior to the initial ictal discharge. This transition involves dynamical entrainment of multiple areas of both cerebral hemispheres and can be demonstrated with measures of spatiotemporal order or chaos (e.g., maximum Lyapunov exponent). The presence of a preictal transition process offers the potential for predicting seizure occurrence in time to prevent an impending seizure through novel therapeutic interventions. Third, preictal entrainment similar to that observed in AMT foci has been observed in a few cases with orbitofrontal foci.
The first aim of the present proposal is to examine recordings from patients with a single unilateral AMT epileptogenic focus to determine whether the epileptogenic focus can be identified consistently and accurately with dynamical measures of the interictal EEG. In contrast, we postulate that recordings from patients with two or more independent epileptogenic foci will not demonstrate a single dynamically distinct focus in the interictal state.
The second aim i s to determine whether temporal lobe seizures can be predicted using algorithms designed to detect preictal transition to the seizure. Finally, we wish to test the hypothesis that seizures originating in the frontal or temporal neocortex are consistently preceded by a spatiotemporal dynamical transition similar to that observed in seizures of AMT origin.

National Institute of Health (NIH)
National Institute of Neurological Disorders and Stroke (NINDS)
Research Project (R01)
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Neurology A Study Section (NEUA)
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Jacobs, Margaret
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University of Florida
Schools of Medicine
United States
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Chaovalitwongse, W; Iasemidis, L D; Pardalos, P M et al. (2005) Performance of a seizure warning algorithm based on the dynamics of intracranial EEG. Epilepsy Res 64:93-113
Manuca, R; Casdagli, M C; Savit, R S (1998) Nonstationarity in epileptic EEG and implications for neural dynamics. Math Biosci 147:1-22
Casdagli, M C; Iasemidis, L D; Savit, R S et al. (1997) Non-linearity in invasive EEG recordings from patients with temporal lobe epilepsy. Electroencephalogr Clin Neurophysiol 102:98-105