• DocumentCode
    380552
  • Title

    A non-homogeneous binomial model for thalamic oscillations

  • Author

    Wang, T. ; Muthuswamy, J.

  • Author_Institution
    Dept. of Bioeng., Arizona State Univ., Tempe, AZ, USA
  • Volume
    1
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    793
  • Abstract
    The thalamic ventral posterior lateral neurons (VPL) respond to somatosensory stimulation with a burst of action potentials followed by a periodic oscillation at the spindle frequency. This study aims to build a statistical model to quantify the multi-unit behavior and explain putative underlying mechanisms. Multi-unit data, comprising 4 or 5 different neurons, were collected from anesthetized adult rats (n=2) by positioning a microelectrode in the ventral posterior lateral (VPL) nuclei of the thalamus. Using an observation window of 1 ms and assuming that neuronal firing is uncorrelated Within this window, the firing rate of the neurons can be successfully modeled by using a nonhomogeneous binomial model with N=1 (with 99.5% confidence). Using maximum likelihood estimator (MILE) of the parameter p, statistically consistent prediction of the parameters of non-homogeneous binomial model was made using a minimum of 50 stimulus-response pairs. The interstimulus interval histograms of the individual neuronal firing indicate a possible stochastic resonance behavior that will model the spindles in thalamus. Our model offers a statistically elegant description of oscillations in neuronal action potential data and can in general, be used to track changes in the neuronal dynamics with function or dysfunction.
  • Keywords
    binomial distribution; bioelectric potentials; brain models; feedback; maximum likelihood estimation; neurophysiology; somatosensory phenomena; stochastic processes; time series; action potentials; coherent feedback; dysfunction; maximum likelihood estimator; multi-unit behavior; neuronal dynamics; neuronal firing; nonhomogeneous binomial model; periodic oscillation; somatosensory stimulation; spindle frequency; statistical model; stimulus-response pairs; stochastic resonance; thalamic oscillations; thalamic ventral posterior lateral neurons; time-series analyses; underlying mechanisms; Biomedical engineering; Frequency; Histograms; Maximum likelihood estimation; Microelectrodes; Neurons; Probability; Rats; Stochastic resonance; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE
  • ISSN
    1094-687X
  • Print_ISBN
    0-7803-7211-5
  • Type

    conf

  • DOI
    10.1109/IEMBS.2001.1019060
  • Filename
    1019060