Application of Semilinear Canonical Correlation to the Measurement of Opioid Drug Effect

To examine the relationship between the electroencephalograph (EEG) and plasma opioid concentration, one would like to collapse the high-dimensional EEG signal into a univariate quantity. Such a simplification of the EEG is desirable because a univariate quantity can be modeled using standard nonlinear regression techniques, and because most of the information in the EEG is redundant or unrelated to drug concentration. In previous studies of the EEG response to opioids, the manner in which a univariate component was extracted from the EEG was ad hoc. In this paper, this extraction was performed optimally using a new statistical technique, semilinear canonical correlation. Data from 15 patients who received an intravenous infusion of the semisynthetic opioid alfentanil were analyzed. The components of the EEG that were nearly maximally correlated with plasma drug concentration were found, based on a standard pharmacokinetic-pharmacodynamic model. Two new EEG components were produced from the powers in the frequency spectrum of the EEG: a weighted sum of the logarithms of the powers, and a weighted sum of the powers expressed as percentages of the total power. These components both had a median R2 of 0.84, compared to median R2s ranging from 0.37 to 0.83 for five commonly used ad hoc EEG components. The new components also had less variability in R2 between subjects.