Brain Topography

, Volume 14, Issue 4, pp 333–344

Complexity Measures of Event Related Potential Surface Laplacian Data Calculated Using the Wavelet Packet Transform

  • Kevin Jones
  • Henri Begleiter
  • Bernice Porjesz
  • Kongming Wang
  • David Chorlian
Article

DOI: 10.1023/A:1015708928892

Cite this article as:
Jones, K., Begleiter, H., Porjesz, B. et al. Brain Topogr (2002) 14: 333. doi:10.1023/A:1015708928892

Abstract

We describe a method to obtain estimates of EEG signal complexity using the well-established wavelet packet transform with best basis selection. In particular, we use the two-dimensional wavelet packet transform to obtain estimates of the complexity of two-dimensional images. This allows us to calculate complexity estimates of high-resolution brain potential maps generated from 61 scalp electrode Visual Oddball paradigm, grand-mean data. A significant reduction in the complexity of the surface Laplacian time-slices is observed during and after the Visual Potential 300 (P3) event for the target case, possibly as a result of increased spatial synchrony associated with visual-related tasks. We also present the results of a statistical analysis of the largest principal component of the time-varying complexity curves, for control, high-risk, and alcoholic groups of male subjects. Parametric and non-parametric analyses show differences in the complexity data which are significant between the control group and the alcoholic and high-risk groups.

ERP Brain's electrical fields Surface Laplacian Wavelet packet transform Complexity Entropy 

Copyright information

© Human Sciences Press, Inc. 2002

Authors and Affiliations

  • Kevin Jones
    • 1
  • Henri Begleiter
    • 1
  • Bernice Porjesz
    • 1
  • Kongming Wang
    • 1
  • David Chorlian
    • 1
  1. 1.Neurodynamics Laboratory, Department of Psychiatry,SUNY Health Science Center at Brooklyn,Brooklyn,USA

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