• DocumentCode
    2413742
  • Title

    A comparison of linear and chaotic measures for rat hippocampal eeg during different vigilance states

  • Author

    Ning, Taikang ; Grare, Adam ; Ning, James

  • Author_Institution
    Trinity Coll., Hartford, CT, USA
  • fYear
    2009
  • fDate
    3-6 Sept. 2009
  • Firstpage
    3437
  • Lastpage
    3440
  • Abstract
    The correlation dimension was used in this paper as a quantifier to describe the chaotic behavior of sleep EEG recorded from the hippocampus of adult rats during vigilance states of quiet-waking, slow-wave sleep, and REM sleep. A modified Grassberger-Procaccia method was implemented to compute the correlation integral using a Euclidean distance normalized by the embedding dimension. The performance of the correlation dimension as a measure to characterize the sleep EEG was compared to the quantitative measures derived from linear autoregressive models. Even though linear and chaotic measures are based on completely different theories and concepts, our experimental results have indicated them both effective in capturing the characteristic differences of sleep EEG during various states. The preliminary results have also shown the correlation dimension being particularly effective in emphasizing the differences in regard to the chaotic behavior between the EEG activity in SWS and QW and REM sleep.
  • Keywords
    autoregressive processes; electroencephalography; sleep; Euclidean distance; adult rat; chaotic measurement; linear autoregressive models; linear measure; modified Grassberger-Procaccia method; quiet walking; rat hippocampal EEG; sleep EEG; slow wave sleep; Algorithms; Animals; Electroencephalography; Hippocampus; Humans; Linear Models; Models, Statistical; Nonlinear Dynamics; Rats; Regression Analysis; Sleep; Sleep Stages; Sleep, REM;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE
  • Conference_Location
    Minneapolis, MN
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-3296-7
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2009.5334635
  • Filename
    5334635