Nonlinear autoregressive analysis of the 3/s ictal electroencephalogram: implications for underlying dynamics Academic Article Article uri icon

Overview

MeSH Major

  • Epididymis
  • Microsurgery
  • Robotics
  • Vasovasostomy

abstract

  • In a previous study, nonlinear autoregressive (NLAR) models applied to ictal electroencephalogram (EEG) recordings in six patients revealed nonlinear signal interactions that correlated with seizure type and clinical diagnosis. Here we interpret these models from a theoretical viewpoint. Extended models with multiple nonlinear terms are employed to demonstrate the independence of nonlinear dynamical interactions identified in the 'NLAR fingerprint' of patients with 3/s seizure discharges. Analysis of the role of periodicity in the EEG signal reveals that the fingerprints reflect the dynamics not only of the periodic discharge itself, but also of the fluctuations of each cycle about an average waveform. A stability analysis is used to make qualitative inferences concerning the network properties of the ictal generators. Finally, the NLAR fingerprint is analyzed in the context of Volterra-Weiner theory.

publication date

  • May 1995

Research

keywords

  • Academic Article

Identity

Digital Object Identifier (DOI)

  • 10.1007/BF00199895

PubMed ID

  • 7612724

Additional Document Info

start page

  • 527

end page

  • 32

volume

  • 72

number

  • 6