MISC

2008年5月

Spectral characteristics of EEG gamma rhythms associated with epileptic spasms

BRAIN & DEVELOPMENT
  • Takushi Inoue
  • ,
  • Katsuhiro Kobayashi
  • ,
  • Makio Oka
  • ,
  • Harumi Yoshinaga
  • ,
  • Yoko Ohtsuka

30
5
開始ページ
321
終了ページ
328
記述言語
英語
掲載種別
DOI
10.1016/j.braindev.2007.10.003
出版者・発行元
ELSEVIER SCIENCE BV

To elucidate the pathophysiology of epileptic spasms, unaveraged time-frequency spectra of spasm-associated EEG gamma rhythms were investigated in 15 patients with West syndrome or related disorders. Using these unaveraged spectra, we were able to investigate in detail various aspects of the structure of ictal gamma rhythms that could not be examined using averaged spectra. The characteristics of the ictal gamma peaks (peak frequency, power, duration, and the number of peaks in each brain-region for each spasm) were statistically evaluated with respect to their differences among the brain regions and over the time-course of the clusters. Our findings were as follows: (1) Gamma peaks were clearly detected in most spectra and generally had a similar pattern in each spasm, which repeated in clusters. (2) The mean frequency of gamma peaks was 69.2 +/- 16.8 Hz, and the number of peaks in each brain region of each spasm was 1.83 +/- 1.16. (3) The occipitoparietal gamma peaks had significantly greater power and longer duration than the frontocentral peaks. (4) The frequency of the gamma peaks was higher in the mid phase of clusters than in the ending, and it tended to have a positive correlation with its latency from the preceding beta peak. An analysis of the ictal gamma rhythms might give some insight into the generative mechanism of spasms. (c) 2007 Elsevier B.V. All rights reserved.

リンク情報
DOI
https://doi.org/10.1016/j.braindev.2007.10.003
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000255526800003&DestApp=WOS_CPL
ID情報
  • DOI : 10.1016/j.braindev.2007.10.003
  • ISSN : 0387-7604
  • Web of Science ID : WOS:000255526800003

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