• DocumentCode
    1184618
  • Title

    A Nonlinear Model of the Neural Integrator Improves Detection of Deficits in the Human VOR

  • Author

    Chan, Wilbur W P ; Galiana, Henrietta L.

  • Author_Institution
    Dept. of Biomed. Eng., McGill Univ., Montreal, QC, Canada
  • Volume
    57
  • Issue
    5
  • fYear
    2010
  • fDate
    5/1/2010 12:00:00 AM
  • Firstpage
    1012
  • Lastpage
    1023
  • Abstract
    A nonlinear model has been proposed to describe the set-point-dependent characteristics of the neural integrator (NI) in the oculomotor system. It was shown to yield improved prediction of slow-phase eye position in the vestibulo-ocular reflex (VOR) of normal subjects, when compared to the classical linear model of the NI. In this paper, we compare the parameters of this nonlinear NI model fitted to VOR data from: 1) compensated subjects diagnosed with vestibular deficiencies such as vestibular neuronitis and Meniere´s disease and 2) normal (symptom-free) subjects. The identified models exhibit more severe nonlinearity in VOR patients than the normal controls. Several of the identified parameters in patients unmask asymmetries and more context dependence in the NI and in the VOR gain that are consistent with the lesioned side and could serve to support detection of lesions even after compensation.
  • Keywords
    biomedical measurement; neurophysiology; physiological models; vision; vision defects; Meniere´s disease; human VOR deficit detection; neural integrator nonlinear model; oculomotor system; set point dependent characteristics; slow phase eye position; vestibular deficiencies; vestibular neuronitis; vestibuloocular reflex; Lesion detection; modeling; neural integrator (NI); vestibulo-ocular reflex (VOR); Computer Simulation; Eye Movements; Humans; Models, Neurological; Nonlinear Dynamics; Reflex, Vestibulo-Ocular; Semicircular Canals; Vestibular Diseases; Vestibular Nuclei;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/TBME.2009.2016112
  • Filename
    4797863