Literature DB >> 18068922

Spectral characteristics of EEG gamma rhythms associated with epileptic spasms.

Takushi Inoue1, Katsuhiro Kobayashi, Makio Oka, Harumi Yoshinaga, Yoko Ohtsuka.   

Abstract

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+/-16.8Hz, 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.

Entities:  

Mesh:

Year:  2008        PMID: 18068922     DOI: 10.1016/j.braindev.2007.10.003

Source DB:  PubMed          Journal:  Brain Dev        ISSN: 0387-7604            Impact factor:   1.961


  15 in total

1.  Automatic detection of fast oscillations (40-200 Hz) in scalp EEG recordings.

Authors:  Nicolás von Ellenrieder; Luciana P Andrade-Valença; François Dubeau; Jean Gotman
Journal:  Clin Neurophysiol       Date:  2011-09-21       Impact factor: 3.708

2.  Interictal scalp fast oscillations as a marker of the seizure onset zone.

Authors:  L P Andrade-Valenca; F Dubeau; F Mari; R Zelmann; J Gotman
Journal:  Neurology       Date:  2011-07-13       Impact factor: 9.910

Review 3.  High-frequency oscillations: The state of clinical research.

Authors:  Birgit Frauscher; Fabrice Bartolomei; Katsuhiro Kobayashi; Jan Cimbalnik; Maryse A van 't Klooster; Stefan Rampp; Hiroshi Otsubo; Yvonne Höller; Joyce Y Wu; Eishi Asano; Jerome Engel; Philippe Kahane; Julia Jacobs; Jean Gotman
Journal:  Epilepsia       Date:  2017-06-30       Impact factor: 5.864

4.  High frequency EEG activity associated with ictal events in an animal model of infantile spasms.

Authors:  James D Frost; Chong L Lee; Richard A Hrachovy; John W Swann
Journal:  Epilepsia       Date:  2011-01-04       Impact factor: 5.864

5.  Interictal high frequency oscillations in an animal model of infantile spasms.

Authors:  James D Frost; Chong L Lee; John T Le; Richard A Hrachovy; John W Swann
Journal:  Neurobiol Dis       Date:  2012-02-09       Impact factor: 5.996

6.  A semi-automated method for rapid detection of ripple events on interictal voltage discharges in the scalp electroencephalogram.

Authors:  Catherine J Chu; Arthur Chan; Dan Song; Kevin J Staley; Steven M Stufflebeam; Mark A Kramer
Journal:  J Neurosci Methods       Date:  2016-12-14       Impact factor: 2.390

7.  High-frequency neuronal network modulations encoded in scalp EEG precede the onset of focal seizures.

Authors:  Catherine Stamoulis; Lawrence J Gruber; Donald L Schomer; Bernard S Chang
Journal:  Epilepsy Behav       Date:  2012-03-10       Impact factor: 2.937

Review 8.  High-frequency oscillations (HFOs) in clinical epilepsy.

Authors:  J Jacobs; R Staba; E Asano; H Otsubo; J Y Wu; M Zijlmans; I Mohamed; P Kahane; F Dubeau; V Navarro; J Gotman
Journal:  Prog Neurobiol       Date:  2012-04-03       Impact factor: 11.685

9.  Scalp recorded spike ripples predict seizure risk in childhood epilepsy better than spikes.

Authors:  Mark A Kramer; Lauren M Ostrowski; Daniel Y Song; Emily L Thorn; Sally M Stoyell; McKenna Parnes; Dhinakaran Chinappen; Grace Xiao; Uri T Eden; Kevin J Staley; Steven M Stufflebeam; Catherine J Chu
Journal:  Brain       Date:  2019-05-01       Impact factor: 13.501

10.  Information theoretic measures of network coordination in high-frequency scalp EEG reveal dynamic patterns associated with seizure termination.

Authors:  Catherine Stamoulis; Donald L Schomer; Bernard S Chang
Journal:  Epilepsy Res       Date:  2013-04-19       Impact factor: 3.045

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.