Summary
This paper discusses the analysis of human EEGs, recorded during epileptic seizures, to determine the area in the brain -the so-called epileptogenic focus- responsible for the synchrony seen during seizures.
Because the pathways of propagation of epileptic activity in the brain are highly non-linear, conventional methods of measuring the time delays between derivations (like crosscorrelation) can not be used. Instead, a new analysis method -based on information theory- has been developed, the AAMI-function (Average Amount of Mutual Information).
Like the crosscorrelation, the AAMI-function provides a measure of the predictability of one signal, given another. By computing the AAMI for a range of lag-values -in analogy to the crosscorrelation function- time delays between signals can be determined.
To estimate AAMI, an algorithm has been developed which comprises an iterative probability density function estimation procedure. Simulations have been performed to determine the quality of our estimator. The technique has been applied to EEGs of artificially provoked seizures in dogs and of spontaneous human seizures.
The method appears also suitable for investigation of other non-linear phenomena in the brain.
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© 1982 Springer-Verlag Berlin Heidelberg
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Mars, N.J.I. (1982). Information-theoretic analysis of human epileptic seizure EEGs. In: O’Moore, R.R., Barber, B., Reichertz, P.L., Roger, F. (eds) Medical Informatics Europe 82. Lecture Notes in Medical Informatics, vol 16. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-93201-4_37
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DOI: https://doi.org/10.1007/978-3-642-93201-4_37
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