Abstract
Objective: It is investigated to which extent measures of nonlinearity derived from surrogate data analysis are capable to quantify the changes of epileptic activity related to varying vigilance levels.
Methods: Surface and intracranial EEG from foramen ovale (FO-)electrodes was recorded from a patient with temporal lobe epilepsy under presurgical evaluation over one night. Different measures of nonlinearity were estimated for non-overlapping 30-s segments for selected channels from surface and intracranial EEG. Additionally spectral measures were calculated. Sleep stages were scored according to Rechtschaffen/Kales and epileptic transients were counted and classified by visual inspection.
Results: In the intracranial recordings stronger nonlinearity was found ipsilateral to the epileptogenic focus, more pronounced in NREM sleep, weaker in REM sleep. The dynamics within the NREM episodes varied with the different nonlinearity measures. Some nonlinearity measures showed variations with the sleep cycle also in the intracranial recordings contralateral to the epileptic focus and in the surface EEG. It is shown that the nonlinearity is correlated with short-term fluctuations of the delta power. The higher frequency of occurrence of clinical relevant epileptic spikes in the first NREM episode was not clearly reflected in the nonlinearity measures.
Conclusions: It was confirmed that epileptic activity renders the EEG nonlinear. However, it was shown that the sleep dynamics itself also effects the nonlinearity measures. Therefore, at the present stage it is not possible to establish a unique connection between the studied nonlinearity measures and specific types of epileptic activity in sleep EEG recordings.
Original language | English |
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Place of Publication | Birmingham |
Publisher | Aston University |
Number of pages | 17 |
ISBN (Print) | 09-04 |
Publication status | Unpublished - 4 Nov 2009 |
Bibliographical note
Preprint submitted to Aston University Research Archive Monograph #5777Keywords
- epilepsy
- interictal spike
- surrogate data
- nonlinearity