Epileptic seizures from abnormal networks: Why some seizures defy predictability

Anderson, William S.; Azhar, Feraz; Kudela, Pawel; Bergey, Gregory K.; Franaszczuk, Piotr J.

doi:10.1016/j.eplepsyres.2011.11.006

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Volume 99, Issue 3 , Pages 202-213, May 2012

Epileptic seizures from abnormal networks: Why some seizures defy predictability

William S. Anderson
- The Johns Hopkins University School of Medicine, Department of Neurosurgery, Meyer 5-109E, 600 North Wolfe Street, Baltimore, MD 21287, USA
- Corresponding author. Tel.: +1 443 287 4561; fax: +1 443 287 6423.
Feraz Azhar
- The Johns Hopkins University School of Medicine, Department of Neurosurgery, Meyer 5-157, 600 North Wolfe Street, Baltimore, MD 21287, USA
- Tel.: +1 443 287 4561; fax: +1 443 287 6423.
Pawel Kudela
- The Johns Hopkins University School of Medicine, Department of Neurology, Meyer 2-147, 600 North Wolfe Street, Baltimore, MD 21287, USA
- Tel.: +1 443 287 8295; fax: +1 410 955 0751.
Gregory K. Bergey
- The Johns Hopkins University School of Medicine, Department of Neurology, Meyer 2-147, 600 North Wolfe Street, Baltimore, MD 21287, USA
- Tel.: +1 410 955 7338; fax: +1 410 502 2507.
Piotr J. Franaszczuk
- The Johns Hopkins University School of Medicine, Department of Neurology, USA
- U.S. Army Research Laboratory, Human Research and Engineering Directorate, Aberdeen Proving Ground, 2800 Powder Mill Road, Adelphi, MD 20783, USA
- Tel.: +1 410 278 8003; fax: +1 410 278 8828.

Received 15 June 2011; received in revised form 19 October 2011; accepted 18 November 2011. published online 14 December 2011.

Summary

Seizure prediction has proven to be difficult in clinically realistic environments. Is it possible that fluctuations in cortical firing could influence the onset of seizures in an ictal zone? To test this, we have now used neural network simulations in a computational model of cortex having a total of 65,536 neurons with intercellular wiring patterned after histological data. A spatially distributed Poisson driven background input representing the activity of neighboring cortex affected 1% of the neurons. Gamma distributions were fit to the interbursting phase intervals, a non-parametric test for randomness was applied, and a dynamical systems analysis was performed to search for period-1 orbits in the intervals. The non-parametric analysis suggests that intervals are being drawn at random from their underlying joint distribution and the dynamical systems analysis is consistent with a nondeterministic dynamical interpretation of the generation of bursting phases. These results imply that in a region of cortex with abnormal connectivity analogous to a seizure focus, it is possible to initiate seizure activity with fluctuations of input from the surrounding cortical regions. These findings suggest one possibility for ictal generation from abnormal focal epileptic networks. This mechanism additionally could help explain the difficulty in predicting partial seizures in some patients.

Keywords: Computational simulation, Neural network model, Seizure prediction, Seizure generation