Statistical evaluation of clusters derived by nonlinear mapping of EEG spatial patterns

New methods were devised to improve the discrimination of EEG spatial amplitude patterns recorded from arrays of 64 electrodes placed on visual, auditory or somatic cortex. The 64 traces shared a spatially coherent, aperiodic carrier wave with a spatial pattern of amplitude modulation (AM). Previous observations on AM patterns from rabbits trained to discriminate conditioned stimuli with reinforcement (CS+) and without (CS-) had revealed epochs between the CS and the CR in which AM patterns on CS+ trials could be distinguished from AM patterns on CS- trials. The AM patterns were expressed by points in 64-space that formed clusters. Levels of CS-/CS+ pattern separation were quantified by a pair-wise Euclidean distance method with cross-validation. The present study documents use of the technique for nonlinear mapping (NLM) to project the 64-dimensional structure onto a plane while preserving the relative distances between all points. The goodness of classification by the Euclidean distance measure was the same or improved after projection. Whereas the Euclidean distance measure only gave pair-wise classifications, the planar displays showed the patterns for multiple clusters simultaneously. These NLM-based methods revealed previously unrecognized structures within distributions of AM patterns in sensory cortices in the time period between the CS and CR.