Partial seizures represent not only the most common seizure type in humans, but are frequently (~50%) intractable to medical therapy. The recognition that resective seizure surgery can benefit selected patients with intractable complex partials seizures has improved utilization of this resource. Presently the best candidates are those with mesial temporal sclerosis or lesional epilepsy. Neocortical epilepsy, particularly nonlesional extratemporal neocortical seizures continue to represent some of the greatest challenges for seizure localization and planned surgical treatment. The lack of an identified abnormality on imaging studies and the typical rapid seizure propagation and spread may make seizure localization difficult or imprecise. The studies proposed here will utilize computational methods to analyze and quantify the detailed dynamics of neocortical onset seizures recorded from intracranial electrode arrays in patients undergoing presurgical evaluations. It is known that seizure onset patterns are remarkably stereotyped from seizure to seizure in a given patient. Detailed time-frequency decompositions and measures of signal complexity allow continuous analyses of seizure dynamics that are not possible with traditional methods. These findings should facilitate seizure localization of neocortical onset seizures. 1 of the hypotheses being tested is the idea that different patterns of seizure onset and evolution will be seen in neocortical onset seizures in patients with known cortical lesions in contrast to those seizures in patients without imaging abnormalities.
The specific aims of this project are to quantify the intrinsic dynamics (e.g. frequency and complexity) of these seizures and to correlate these findings with seizure location, pathology, and clinical outcome after surgery. The analyses of the intrinsic dynamics will hopefully permit identification of subgroups of neocortical onset seizures, characterized by specific patterns of seizure dynamics, not readily apparent from visual inspection of the EEG that in fact would be excellent candidates for resective surgery.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
5R01NS048222-03
Application #
7266855
Study Section
Special Emphasis Panel (ZRG1-BDCN-A (03))
Program Officer
Stewart, Randall R
Project Start
2005-07-01
Project End
2009-06-30
Budget Start
2007-07-01
Budget End
2008-06-30
Support Year
3
Fiscal Year
2007
Total Cost
$359,598
Indirect Cost
Name
Johns Hopkins University
Department
Neurology
Type
Schools of Medicine
DUNS #
001910777
City
Baltimore
State
MD
Country
United States
Zip Code
21218
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Korzeniewska, A; Cervenka, M C; Jouny, C C et al. (2014) Ictal propagation of high frequency activity is recapitulated in interictal recordings: effective connectivity of epileptogenic networks recorded with intracranial EEG. Neuroimage 101:96-113
Jouny, Christophe C; Bergey, Gregory K (2012) Characterization of early partial seizure onset: frequency, complexity and entropy. Clin Neurophysiol 123:658-69
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Jouny, Christophe C; Bergey, Gregory K; Franaszczuk, Piotr J (2010) Partial seizures are associated with early increases in signal complexity. Clin Neurophysiol 121:7-13
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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