Principal component analysis of pain-related cerebral potentials to mechanical and electrical stimulation in man

Abstract

Single trial event-related cerebral potentials (ERPs) in response to skin stimuli of various intensities and qualities in man were investigated in respect to their nociceptive information content. Electrical constant current stimuli (20 msec, 2–8 mA) and mechanical force controlled stimuli (20 msec, 0.8–3.2 N) were applied to the tip of the left middle finger. Four intensities of each stimulus quality were given, each intensity appearing 40 times in standardized randomized order. EEG segments (between 5 sec before and 500 msec after stimulus onset) were subjected to computer analysis. ERP wave form was shown to depend upon the amount of alpha waves in the prestimulus EEG. For analysis, only subjects with low power in the alpha band were selected. Principal component analysis was applied to all single trial ERPs measured using the variance-covariance matrix of association. Six principal components (PCs) were extracted accounting for about 90% of total variance. Five of the extracted PCs had well located loading maxima: PC1 (50–80 msec), PC2 (140–160 msec), PC3 (200–250 msec), PC4 (280–360 msec), PC5 (400–500 msec); PC6 appeared polyphasic. Analysis of variance of the mean PC scores revealed that one PC (PC1) discriminated between quality, and 4 PCs (PC1–PC4) between quantity of stimulation. Eliminating effects of stimulus intensity resulted in two PCs (PC2, PC4) which distinguished exclusively between non-pain and pain. PCA applied to disjunctive subsets of ERPs, corresponding to the different experimental conditions, yielded practically identical sets of PCs, such that no specific ERP component emerged when pain was reported.