Spread of Epileptic Seizure Activity in Experimental and Clinical Epilepsy: The Use of Mutual Information Analysis
The mechanism of spread of epileptic seizures re-mains an important unsolved question in the process of epileptogenesis. This question is not only of fundamental importance for understanding how focal epileptic activity propagates to neighboring and/or distant brain areas but also of practical interest. This last aspect is particularly relevant where the primary site of an epileptogenic focus must be determined, namely in those patients in whom the surgical removal of the focus is being considered. The propagation of focal epileptic activity is not easy to assess by way of visual examination of a large number of EEG records even if recorded from subdural or intracerebral electrodes. It is generally assumed that the EEG signal recorded from the focal area will present a time lead over signals recorded from distant areas. However, a main difficulty is that it is not possible to assess visually small time differences in the order of a few milliseconds which may exist between such EEG signals. Therefore, computer- based analysis methods have been devised to obtain estimates of time delays between such EEG signals. Brazier (1972,1973) carried out the first type of such an analysis. Based on the phase angle (φ0 in degrees) at a particular frequency (f0 in Hz) for which coherence was maximal, a time delay (Δt) was calculated according to: φ0/360f0. This method, however, may give ambiguous results since the phase angle at one particular frequency can be transformed into a time delay only if the phase as function of frequency fits a straight line which intersects the axes at the origin. However, this does not always occur in practice. Sometimes phase functions are encountered between EEG signals which at zero frequency intersect the phase axis at ±180°.
KeywordsMutual Information Epileptic Seizure Estimate Time Delay Epileptogenic Focus Clinical Epilepsy
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- Brazier MAB (1973) Electrical seizure discharges within the human brain: the problem of spread. In: Brazier MAB (ed) Epilepsy: its phenomena in man. Academic, New York, pp 153–170Google Scholar
- Carter GC (1976) Time delay estimation. Naval Underwater Systems Center, New London, CO Report TR-5335Google Scholar
- Gel’fand JM, Yaglom AM (1959) Calculation of the amount of information about a random function contained in another such function. American Mathematical Society Translations 12: 199–246Google Scholar
- Gersch W (1972) Causality or driving in electrophysiological signal analysis method (with G. V. Gddard). Science 150: 701–702Google Scholar
- Mars NJI, Lopes da Silva FH, Van Hulten K, Lommen JG (1977) Computer assisted analysis of EEGs during seizures; localisation of an epileptogenic area. Electroencephalogr Clin Neurophysiol 43: 575Google Scholar
- Moddemeijer R (1985) Estimation of entropy and mutual information of continuous distribution. In: Vinck AJ (ed) Proceeding 6th symposium on information theory in the Benelux. EnschedeGoogle Scholar
- Shannon CE, Weaver W (1949) The mathematical theory of communication. University of Illinois Press, UrbanaGoogle Scholar
- Taylor C, Krnjevic K, Ropert N (1983) Field interactions in CA3 hippocampal pyramidal layer in rats in vivo. Can J Pharmacol 61: A32–A33Google Scholar