• DocumentCode
    1092291
  • Title

    A random dipole model for spontaneous brain activity

  • Author

    De Munck, Jan C. ; Vijn, Peter C M ; Silva, Fernando H Lopes da

  • Author_Institution
    Low Temp. Dept., Tech. Univ. of Enschede, Netherlands
  • Volume
    39
  • Issue
    8
  • fYear
    1992
  • Firstpage
    791
  • Lastpage
    804
  • Abstract
    The statistical properties of the EEG and the MEG can be described mathematically as the result of randomly distributed dipoles representing the interactions of cortical neurons. If the dipoles are in a spherical volume conductor and have no preference for any direction, the variance of a differentially measured EEG signal is only a function of the electrode distance. The theoretically derived variance function is compared with EEG and MEG measurements. It is shown that a dipole with a fixed position and a randomly fluctuating amplitude is an adequate model for the alpha -rhythm. An expression for the covariance between the magnetic field and a differentially measured EEG signal is derived. This covariance is considered as a function of the magnetometer position. The theory can be used to obtain a (spatial) covariance matrix of the background noise, which occurs in evoked potential measurements. Such a covariance matrix can be used to obtain a maximum likelihood estimator (MLE) of the dipole parameters in evoked potential studies.
  • Keywords
    biomagnetism; brain models; electroencephalography; EEG; MEG; alpha rhythm model; cortical neurons interactions; covariance matrix; electrode distance; evoked potential measurements; magnetometer position; random dipole model; randomly distributed dipoles; randomly fluctuating amplitude; spherical volume conductor; spontaneous brain activity; statistical properties; Brain modeling; Conductors; Covariance matrix; Electrodes; Electroencephalography; Magnetic field measurement; Magnetometers; Maximum likelihood estimation; Neurons; Volume measurement; Artifacts; Brain; Computer Simulation; Electroencephalography; Humans; Likelihood Functions; Magnetoencephalography;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/10.148387
  • Filename
    148387