Faculty Collaboration Database

Long-range prediction of epileptic seizures with nonlinear dynamics. Nonlinear Dynamics Psychol Life Sci 2011 Jul;15(3):377-88

Date

06/08/2011

Pubmed ID

21645436

Scopus ID

2-s2.0-80052390153 (requires institutional sign-in at Scopus site)   2 Citations

Abstract

Patients with uncontrolled epilepsy have some significant problems with planning life routines, and thus one goal of the present study was to explore the viability of predicting seizures in time intervals of one week. The second goal was to utilize the principle of dynamic diseases and to assess the viability of a cusp catastrophe model for seizure onset that was proposed by Cerf (2006). A seizure history of 124 weeks from one adult male patient fit both the cusp and fold catastrophe models (R2 = .92 and .88 respectively) reasonably well using the pdf method and more accurately than counterpart linear models. Prediction of future states was possible, but somewhat compromised because of the nonstationary nature of the data and uncertainties regarding the control variables in the catastrophe models. Analyses of lag functions, however, revealed some surprising elements, suggesting that the precursory conditions for a seizure could be building up over a period of several weeks and that a self-correcting effect within the nervous system could have been occurring.

Author List

Guastello SJ, Boeh H, Lynn M

Author

Stephen Guastello BA,MA,PhD Professor in the Psychology department at Marquette University

MESH terms used to index this publication - Major topics in bold

Algorithms
Bayes Theorem
Dominance, Cerebral
Epilepsy, Tonic-Clonic
Frontal Lobe
Humans
Male
Middle Aged
Neurons
Nonlinear Dynamics