• DocumentCode
    1240161
  • Title

    Nonlinear changes in brain´s response in the event of injury as detected by adaptive coherence estimation of evoked potentials

  • Author

    Thakor, Nitish V. ; Kong, Xuan ; Hanley, Daniel F.

  • Author_Institution
    Dept. of Biomed. Eng., Johns Hopkins Univ., Baltimore, MD, USA
  • Volume
    42
  • Issue
    1
  • fYear
    1995
  • Firstpage
    42
  • Lastpage
    51
  • Abstract
    Injury-related changes in evoked potentials are studied with the aid of the coherence function, which effectively measures the degree of linear association between a pair of signals recorded during normal and abnormal states of the brain. The performance of an adaptive algorithm for estimating coherence function is studied, and the effects of additive noise on the estimated coherence function is discussed. Further, a linearity index is formulated and, through analysis and simulations, the index is shown to respond in a predictable manner to increasing nonlinearity while maintaining the robustness to the observation noise. Somatosensory evoked potentials are shown to be sensitive to injury resulting from acute cerebral hypoxia. The authors analyze the somatosensory evoked potentials recorded from anesthetized cats during inhalation of 8-9% oxygen gas mixtures and during recovery with 100% oxygen. Analyses of the experimental data show a very sharp drop in the magnitude coherence estimates during hypoxic injury and a corresponding rapid decline in the linearity index at the very early stages of the hypoxic injury. Thus, injury may lead to nonlinearities in the electrical response of the brain, and such measurements analyzed by the adaptive coherence estimation method may be used for diagnostic purposes.
  • Keywords
    bioelectric potentials; brain; somatosensory phenomena; abnormal brain states; adaptive coherence estimation; anesthetized cats; brain´s response; hypoxic injury; injury-related changes; nonlinear changes; normal brain states; somatosensory evoked potentials; Adaptive algorithm; Additive noise; Analytical models; Brain modeling; Cats; Event detection; Injuries; Linearity; Noise robustness; Predictive models; Algorithms; Animals; Cats; Computer Simulation; Evoked Potentials, Somatosensory; Hypoxia, Brain; Models, Biological; Monitoring, Physiologic; Nonlinear Dynamics;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/10.362920
  • Filename
    362920