Literature DB >> 11007440

EEG bands during wakefulness, slow-wave and paradoxical sleep as a result of principal component analysis in man.

M Corsi-Cabrera1, M A Guevara, Y Del Río-Portilla, C Arce, Y Villanueva-Hernández.   

Abstract

Human electroencephalogram (EEG) has been divided in bands established by visual inspection that frequently do not correspond with EEG generators nor with functional meaning of EEG rhythms. Power spectra from wakefulness, stage 2, stage 4 and paradoxical sleep of 8 young adults were submitted to Principal Component Analyses to investigate which frequencies covaried together. Two identical eigenvectors were identified for stage 2 and stage 4: 1 to 8 Hz and 5 to 15 Hz (87.95 and 84.62 % of the total variance respectively). Two eigenvectors were extracted for PS: 1 to 9 Hz and 10 to 15 Hz (81.62% of the total variance). Three eigenvectors were obtained for W: with frequencies between 1 to 7 Hz, 7 to 11 Hz, and 12 to 15 Hz (78.32% of the total variance). Power for all frequencies showed significant differences among vigilance states. These results indicate that slow wave activity can oscillate at higher frequencies, up to 8 Hz, and that spindle oscillations have a wider range down to 5 Hz. No theta band was independently identified, suggesting either that delta and theta oscillations are two rhythms under the same global influence, or that the traditional division of theta band in the human cortical EEG is artificial. Alpha as a band was identified only during wakefulness. Principal component analysis upon spectral densities extracted broad bands different for each vigilance state and from traditional bands, consistent with functional significance of EEG and with frequencies of generators of rhythmic activity obtained in cellular studies in animals.

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Year:  2000        PMID: 11007440

Source DB:  PubMed          Journal:  Sleep        ISSN: 0161-8105            Impact factor:   5.849


  13 in total

1.  Modification of EEG power spectra and EEG connectivity in autobiographical memory: a sLORETA study.

Authors:  Claudio Imperatori; Riccardo Brunetti; Benedetto Farina; Anna Maria Speranza; Anna Losurdo; Elisa Testani; Anna Contardi; Giacomo Della Marca
Journal:  Cogn Process       Date:  2014-03-09

2.  Electroencephalogram bands modulated by vigilance states in an anuran species: a factor analytic approach.

Authors:  Guangzhan Fang; Qin Chen; Jianguo Cui; Yezhong Tang
Journal:  J Comp Physiol A Neuroethol Sens Neural Behav Physiol       Date:  2011-11-02       Impact factor: 1.836

3.  Quantitative EEG amplitude across REM sleep periods in depression: preliminary report.

Authors:  Marcus P Liscombe; Robert F Hoffmann; Madhukar H Trivedi; Marc K Parker; A John Rush; Roseanne Armitage
Journal:  J Psychiatry Neurosci       Date:  2002-01       Impact factor: 6.186

4.  Sample entropy tracks changes in electroencephalogram power spectrum with sleep state and aging.

Authors:  Eugene N Bruce; Margaret C Bruce; Swetha Vennelaganti
Journal:  J Clin Neurophysiol       Date:  2009-08       Impact factor: 2.177

5.  Mutual information analysis of EEG signals indicates age-related changes in cortical interdependence during sleep in middle-aged versus elderly women.

Authors:  Pravitha Ramanand; Margaret C Bruce; Eugene N Bruce
Journal:  J Clin Neurophysiol       Date:  2010-08       Impact factor: 2.177

6.  Rhythmicity in heart rate and its surges usher a special period of sleep, a likely home for PGO waves.

Authors:  Andreas A Ioannides; Gregoris A Orphanides; Lichan Liu
Journal:  Curr Res Physiol       Date:  2022-02-15

7.  Application of independent component analysis for the data mining of simultaneous Eeg-fMRI: preliminary experience on sleep onset.

Authors:  Jong-Hwan Lee; Sungsuk Oh; Ferenc A Jolesz; Hyunwook Park; Seung-Schik Yoo
Journal:  Int J Neurosci       Date:  2009       Impact factor: 2.292

8.  EEG Bands of Wakeful Rest, Slow-Wave and Rapid-Eye-Movement Sleep at Different Brain Areas in Rats.

Authors:  Wei Jing; Yanran Wang; Guangzhan Fang; Mingming Chen; Miaomiao Xue; Daqing Guo; Dezhong Yao; Yang Xia
Journal:  Front Comput Neurosci       Date:  2016-08-03       Impact factor: 2.380

9.  Evoked potentials and behavioral performance during different states of brain arousal.

Authors:  Jue Huang; Tilman Hensch; Christine Ulke; Christian Sander; Janek Spada; Philippe Jawinski; Ulrich Hegerl
Journal:  BMC Neurosci       Date:  2017-01-25       Impact factor: 3.288

10.  Modifications of EEG power spectra in mesial temporal lobe during n-back tasks of increasing difficulty. A sLORETA study.

Authors:  Claudio Imperatori; Benedetto Farina; Riccardo Brunetti; Valentina Gnoni; Elisa Testani; Maria I Quintiliani; Claudia Del Gatto; Allegra Indraccolo; Anna Contardi; Anna M Speranza; Giacomo Della Marca
Journal:  Front Hum Neurosci       Date:  2013-04-02       Impact factor: 3.169

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