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Physiological Ripples Associated with Sleep Spindles Differ in Waveform Morphology from Epileptic Ripples.

Authors :
Bruder JC
Dümpelmann M
Piza DL
Mader M
Schulze-Bonhage A
Jacobs-Le Van J
Source :
International journal of neural systems [Int J Neural Syst] 2017 Nov; Vol. 27 (7), pp. 1750011. Date of Electronic Publication: 2016 Nov 02.
Publication Year :
2017

Abstract

High frequency oscillations (HFOs, 80-500[Formula: see text]Hz) serve as novel electroencephalography (EEG) markers of epileptic tissue. The differentiation of physiological and epileptic HFO is an important challenge and is complicated by the fact that both types are generated in mesiotemporal structures. This study aimed to identify oscillation features that serve to distinguish physiological ripples associated with sleep spindles and epileptic ripples. We studied 19 patients with chronic intracranial EEG(iEEG) with mesiotemporal implantation and simultaneous scalp EEG. Sleep spindles, ripples and spikes were visually marked during nonrapid eye movement sleep stage 2. Ripples co-occurring with spikes and in seizure onset zone (SOZ) channels but outside of spindles were considered epileptic. The SOZ is defined by the origin of clinical seizures in iEEG. Ripples co-occurring with spindles were considered as models for physiological ripples. A correlation analysis showed a significant ripple amplitude peak - spindle trough - coupling, thus proving their physiological linkage. Epileptic ripples showed significantly higher values in all amplitude features than spindle ripples. All amplitude features and peaks per sample length showed a predictive value for the classification between model physiological ripples and epileptic ripples but indicate that the specificity is not sufficient for a reliable discrimination of single ripple events. The presented results suggest that a secure identification of epileptic ripples may be available to help identify the epileptic focus in the future.

Details

Language :
English
ISSN :
1793-6462
Volume :
27
Issue :
7
Database :
MEDLINE
Journal :
International journal of neural systems
Publication Type :
Academic Journal
Accession number :
28043201
Full Text :
https://doi.org/10.1142/S0129065717500113