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Clin Neurophysiol. 2005 Mar;116(3):545-51. Epub 2005 Jan 5.

Multivariate linear discrimination of seizures.

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1
Krasnow Institute for Advanced Study, George Mason University, Fairfax, VA 22030, USA.

Abstract

OBJECTIVE:

To discriminate seizures from interictal dynamics based on multivariate synchrony measures, and to identify dynamics of a pre-seizure state.

METHODS:

A linear discriminator was constructed from two different measures of synchronization: cross-correlation and phase synchronization. We applied this discriminator to a sequence of seizures recorded from the intracranial EEG of a patient monitored over 6 days.

RESULTS:

Surprisingly, we found that this bivariate measure of synchronization was not a reliable seizure discriminator for 7 of 9 seizures. Furthermore, the method did not appear to reliably detect a pre-seizure state. An association between anti-convulsant dosage, frequency of clinical seizures, and discriminator performance was noted.

CONCLUSIONS:

Using a bivariate measure of synchronization failed to reliably differentiate seizures from non-seizure periods in these data, nor did such methods show reliable detection of a synchronous pre-seizure state. The non-stationary variables of decreasing antiepileptic medication (without available serum concentration measurements), and concomitant increasing seizure frequency contributed to the difficulties in validating a seizure prediction tool on such data.

SIGNIFICANCE:

The finding that these seizures were not a simple reflection of increasing synchronization in the EEG has important implications. The non-stationary characteristics of human post-implantation intracranial EEG is an inherent limitation of pre-resection data sets.

PMID:
15721068
DOI:
10.1016/j.clinph.2004.08.023
[Indexed for MEDLINE]
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