• DocumentCode
    973096
  • Title

    Frequency domain dipole localization: extensions of the method and applications to auditory and visual evoked potentials

  • Author

    Raz, Jonathan ; Biggins, Christie A. ; Turetsky, Bruce ; Fein, George

  • Author_Institution
    Dept. of Biostat., Michigan Univ., Ann Arbor, MI, USA
  • Volume
    40
  • Issue
    9
  • fYear
    1993
  • Firstpage
    909
  • Lastpage
    918
  • Abstract
    A statistical frequency domain approach to localizing equivalent dipole generators of human brain evoked potentials is described. The frequency domain representation allows considerable data reduction, constrains the magnitude function of the dipoles to be smooth, and accounts for the statistical properties of the background EEG. A general model in which dipole orientation can vary over time, and which includes multiple dipole generators is considered. The varying orientation model has the practical advantage of being more nearly linear and more flexible than a fixed orientation model, which facilitates convergence of the iterative fitting algorithm. A measure of goodness-of-fit that compares the likelihood of the dipole model with the likelihoods of saturated and null models is suggested. The results of fitting the model report recorded auditory and visual evoked potentials are reported. A single dipole with fixed orientation seems to be an adequate model of the auditory midlatency response, while two dipoles with varying orientation are needed to fit the later P200 component. Analysis of the visual P100 response to unilateral stimulation localized a generator in the contralateral occipital cortex, as expected from anatomical considerations.
  • Keywords
    bioelectric potentials; brain models; electroencephalography; frequency-domain analysis; hearing; maximum likelihood estimation; vision; P200 component; auditory evoked potentials; auditory midlatency response; background EEG; contralateral occipital cortex; equivalent dipole generators; human brain evoked potentials; iterative fitting algorithm; maximum likelihood estimates; multiple dipole generators; statistical frequency domain approach; statistical properties; unilateral stimulation; varying orientation model; visual P100 response; visual evoked potentials; Biomedical electrodes; Brain modeling; Convergence; Deafness; Electroencephalography; Frequency domain analysis; Humans; Iterative algorithms; Maximum likelihood estimation; Public healthcare; Scalp; Computer Simulation; Evoked Potentials, Auditory; Evoked Potentials, Visual; Fourier Analysis; Humans; Likelihood Functions; Models, Neurological; Models, Statistical; Reference Values; Signal Processing, Computer-Assisted;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/10.245612
  • Filename
    245612