Characterizing nonlinearity in invasive EEG recordings from temporal lobe epilepsy
type: Item
instance of: scholarly article
title: Characterizing nonlinearity in invasive EEG recordings from temporal lobe epilepsy
zbMATH Open document ID: 0886.92012
DOI: 10.1016/S0167-2789(96)00160-1
author: J. C. Sackellares
author: S. N. Roper
author: R. L. Gilmore
author: R. S. Savit
author: Martin Casdagli
author: Leonidas D. Iasemidis
published in: Physica D
publication date: 1997-02-03T00:00:00Z
review text: Invasive electroencephalographic (EEG) recordings from depth and subdural electrodes, performed in eight patients with temporal lobe epilepsy, are analyzed using a variety of nonlinear techniques. A surrogate data technique is used to find strong evidence for nonlinearities in epileptogenic regions of the brain. Most of these nonlinearities are characterized as ``spiking'' by a wavelet analysis. A small fraction of the nonlinearities are characterized as ``recurrent'' by a nonlinear prediction algorithm. Recurrent activity is found to occur in spatio-temporal patterns related to the location of the epileptogenic focus. Residual delay maps, used to characterize ``lag-one nonlinearity'', are remarkably stationary for a given electrode, and exhibit striking variations among electrodes. The clinical and theoretical implications of these results are discussed.
Mathematics Subject Classification ID: 92C50
Mathematics Subject Classification ID: 92C20
zbMATH DE Number: 968609
zbMATH Keywords: epileptogenic focus
zbMATH Keywords: invasive EEG
zbMATH Keywords: nonlinear prediction
zbMATH Keywords: surrogate data
zbMATH Keywords: wavelets
MaRDI profile type: Publication
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full work available at URL: s0167-2789(96)00160-1
OpenAlex ID: W2021546756
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