EVALUATION OF A NOVEL EEG ANALYSIS METHOD WITH POTENTIAL DIAGNOSTIC APPLICATIONS

Background: Cerebral cortex oscillations as recorded on electroencephalograms involve multiple frequency bands. Phase locking of oscillations of these different frequencies may provide a mechanism by which regions of the brain communicate efficiently. Differences in the character of such phase locking may potentially be a diagnostic tool to differentiate seizure types, as traditional analysis of clinical EEG recordings has seldom considered phase-clocking as a diagnostic indicator. Recently, Canolty et al^1 used a novel metric to quantify cross-frequency phase-amplitude coupling during both spontaneous and induced EEG activity. The technique holds advantages over traditional measures, including easy comparison across trials, robustness to amplitude variation, and simple quantification of preferred phase. Traditional analysis of clinical EEG recordings has seldom considered phase-clocking as a diagnostic indicator. Methods: We adapted the metric of Canolty^1 to perform better with highly rhythmic oscillations, such as those in seizures, by adding multi-segment reshuffling of phase traces. To validate our modified technique, we used artificial sinusoid traces with a known degree of coupling to test the response of our modified analysis method, and to derive empirically, appropriate values for important numerical parameters. Frequency and phase information was acquired with both the Hilbert and wavelet transforms, with similar qualitative results achieved with either. Results: As an initial exploration of diagnostic potential, we applied our metric to field potential data obtained from an anaesthetized rat preparation. We compared the phase-amplitude coupling profiles of sleep oscillations with those of simulated absence seizures and showed consistent differences in the phase amplitude coupling profiles. The data suggest that such differences may be useful in evaluating human seizure data. Conclusions: We conclude that our modified method of data analysis provides an effective approach for measuring normalized phase-amplitude coupling in field potential recordings. Future work will aim to evaluate the possible diagnostic uses of phase-amplitude coupling analysis with data from human seizure patients. Reference: Canolty et al. Science 2006;313:1626. Supported by CIHR, NSERC, and the Health Research Foundation.