Accurate seizure characterization and localization can be important for appropriate treatment of patients with epilepsy including those with intractable partial epilepsy being considered for seizure surgery. While in some patients the regions of seizure onset may be apparent from scalp EEG recordings, not infrequently scap recordings are not sufficient and intra-cranial ictal EEG recordings must be obtained using depth electrode arrays or subdural grids and strips. Some seizures, particularly those originating from frontal lobe regions or other neocortical regions (e.g., temporal lobe) may be particularly difficult to localize even with extensive incracranial recording arrays because of broad regional onset or rapid seizure propagation. New computer assisted methods for EEG analysis can provide significant insights not apparent from visual EEG inspection. The ability to measure patterns of seizure flow, using such methods as the directed transfer function method can determine sources of seizure activity that are not otherwise apparent. The recently described matching pursuit method allows detailed and continuous time-frequency decomposition of entire seizures, allowing exact characterization of the component frequencies.
The specific aims of this proposal are to apply these various analytic methods to characterize both mesial temporal onset seizures and seizures originating from lateral temporal and frontal neocortical regions, specifically addressing seizure dynamics and component frequencies. These and other techniques will be used to address the important issues regarding seizure occurrence. The occurrence of an epileptic seizure may not be a random event, particularly wen clusters of seizures occur. This proposal will apply various measures of synchronization and complexity to provide insights into evidence for deterministic behaviors that govern seizure occurrence, recurrence and seizure termination. Understanding the spatiotemporal relationships that produce seizure can provide important insights into epileptogenesis.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
7R01NS033732-05
Application #
6337911
Study Section
Special Emphasis Panel (ZRG1-BDCN-1 (01))
Program Officer
Jacobs, Margaret
Project Start
1995-08-01
Project End
2003-06-30
Budget Start
2000-07-01
Budget End
2001-06-30
Support Year
5
Fiscal Year
1999
Total Cost
Indirect Cost
Name
Johns Hopkins University
Department
Neurology
Type
Schools of Medicine
DUNS #
045911138
City
Baltimore
State
MD
Country
United States
Zip Code
21218
Jouny, Christophe C; Adamolekun, Bola; Franaszczuk, Piotr J et al. (2007) Intrinsic ictal dynamics at the seizure focus: effects of secondary generalization revealed by complexity measures. Epilepsia 48:297-304
Jouny, Christophe C; Franaszczuk, Piotr J; Bergey, Gregory K (2005) Signal complexity and synchrony of epileptic seizures: is there an identifiable preictal period? Clin Neurophysiol 116:552-8
Jouny, Christophe C; Franaszczuk, Piotr J; Bergey, Gregory K (2003) Characterization of epileptic seizure dynamics using Gabor atom density. Clin Neurophysiol 114:426-37
Ray, Supratim; Jouny, Christophe C; Crone, Nathan E et al. (2003) Human ECoG analysis during speech perception using matching pursuit: a comparison between stochastic and dyadic dictionaries. IEEE Trans Biomed Eng 50:1371-3
Bergey, G K; Franaszczuk, P J (2001) Epileptic seizures are characterized by changing signal complexity. Clin Neurophysiol 112:241-9
Franaszczuk, P J; Bergey, G K; Durka, P J et al. (1998) Time-frequency analysis using the matching pursuit algorithm applied to seizures originating from the mesial temporal lobe. Electroencephalogr Clin Neurophysiol 106:513-21
Franaszczuk, P J; Bergey, G K (1998) Application of the directed transfer function method to mesial and lateral onset temporal lobe seizures. Brain Topogr 11:13-21
Kudela, P; Franaszczuk, P J; Bergey, G K (1997) A simple computer model of excitable synaptically connected neurons. Biol Cybern 77:71-7