Article

Brain Topography

, Volume 2, Issue 4, pp 275-284

First online:

Spatial patterns underlying population differences in the background EEG

  • Zoltan J. KolesAffiliated withDepartment of Applied Sciences in Medicine, University of Alberta
  • , Michael S. LazarAffiliated withDepartment of Applied Sciences in Medicine, University of Alberta
  • , Steven Z. ZhouAffiliated withDepartment of Applied Sciences in Medicine, University of Alberta

Rent the article at a discount

Rent now

* Final gross prices may vary according to local VAT.

Get Access

Summary

A method is described which can be used to extract common spatial patterns underlying the EEGs from two human populations. These spatial patterns account, in the least-squares sense, maximally for the variance in the EEGs from one population and minimally for the variance in the other population and therefore would seem to be optimal for quantitatively discriminating between the individual EEGs in the two populations. By using this method, it is suggested that the problems associated with the more common approach to discriminating EEGs, significance probability mapping, can be avoided. The method is tested using EEGs from a population of normal subjects and using the EEGs from a population of patients with neurologic disorders. The results in most cases are excellent and the misclassification which occurs in some cases is attributed to the nonhomogeneity of the patient population particularly. The advantages of the method for feature selection, for automatically classifying the clinical EEG, and with respect to the reference-free nature of the selected features are discussed.

Key words

Electroencephalogram Eigenanalysis Spatial patterns Classification