Literature DB >> 9322268

Topographical characteristics and principal component structure of the hypnagogic EEG.

H Tanaka1, M Hayashi, T Hori.   

Abstract

The purpose of the present study was to identify the dominant topographic components of electroencephalographs (EEG) and their behavior during the waking-sleeping transition period. Somnography of nocturnal sleep was recorded on 10 male subjects. Each recording, from "lights-off" to 5 minutes after the appearance of the first sleep spindle, was analyzed. The typical EEG patterns during hypnagogic period were classified into nine EEG stages. Topographic maps demonstrated that the dominant areas of alpha-band activity moved from the posterior areas to anterior areas along the midline of the scalp. In delta-, theta-, and sigma-band activities, the differences of EEG amplitude between the focus areas (the dominant areas) and the surrounding areas increased as a function of EEG stage. To identify the dominant topographic components, a principal component analysis was carried out on a 12-channel EEG data set for each of six frequency bands. The dominant areas of alpha 2- (9.6-11.4 Hz) and alpha 3- (11.6-13.4 Hz) band activities moved from the posterior to anterior areas, respectively. The distribution of alpha 2-band activity on the scalp clearly changed just after EEG stage 3 (alpha intermittent, < 50%). On the other hand, alpha 3-band activity became dominant in anterior areas after the appearance of vertex sharp-wave bursts (EEG stage 7). For the sigma band, the amplitude of extensive areas from the frontal pole to the parietal showed a rapid rise after the onset of stage 7 (the appearance of vertex sharp-wave bursts). Based on the results, sleep onset process probably started before the onset of sleep stage 1 in standard criteria. On the other hand, the basic sleep process may start before the onset of sleep stage 2 or the manually scored spindles.

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Year:  1997        PMID: 9322268     DOI: 10.1093/sleep/20.7.523

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


  14 in total

1.  Topographical frequency dynamics within EEG and MEG sleep spindles.

Authors:  Nima Dehghani; Sydney S Cash; Eric Halgren
Journal:  Clin Neurophysiol       Date:  2010-07-15       Impact factor: 3.708

2.  Independent component analysis for source localization of EEG sleep spindle components.

Authors:  Erricos M Ventouras; Periklis Y Ktonas; Hara Tsekou; Thomas Paparrigopoulos; Ioannis Kalatzis; Constantin R Soldatos
Journal:  Comput Intell Neurosci       Date:  2010-03-29

3.  How deep is the rift between conscious states in sleep and wakefulness? Spontaneous experience over the sleep-wake cycle.

Authors:  Jennifer M Windt
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2020-12-14       Impact factor: 6.237

4.  Shifted coupling of EEG driving frequencies and fMRI resting state networks in schizophrenia spectrum disorders.

Authors:  Nadja Razavi; Kay Jann; Thomas Koenig; Mara Kottlow; Martinus Hauf; Werner Strik; Thomas Dierks
Journal:  PLoS One       Date:  2013-10-04       Impact factor: 3.240

5.  Tracking the sleep onset process: an empirical model of behavioral and physiological dynamics.

Authors:  Michael J Prerau; Katie E Hartnack; Gabriel Obregon-Henao; Aaron Sampson; Margaret Merlino; Karen Gannon; Matt T Bianchi; Jeffrey M Ellenbogen; Patrick L Purdon
Journal:  PLoS Comput Biol       Date:  2014-10-02       Impact factor: 4.475

6.  Transient Topographical Dynamics of the Electroencephalogram Predict Brain Connectivity and Behavioural Responsiveness During Drowsiness.

Authors:  Iulia M Comsa; Tristan A Bekinschtein; Srivas Chennu
Journal:  Brain Topogr       Date:  2018-11-29       Impact factor: 3.020

7.  Comparison of low resolution electromagnetic tomography imaging between subjects with mild and severe obstructive sleep apnea syndrome: a preliminary study.

Authors:  Hyun-Kwon Lee; Doo-Heum Park; Hyun-Sil Shin; Seok-Chan Hong
Journal:  Psychiatry Investig       Date:  2008-03-31       Impact factor: 2.505

8.  Objective evaluation of fatigue by EEG spectral analysis in steady-state visual evoked potential-based brain-computer interfaces.

Authors:  Teng Cao; Feng Wan; Chi Man Wong; Janir Nuno da Cruz; Yong Hu
Journal:  Biomed Eng Online       Date:  2014-03-12       Impact factor: 2.819

9.  Inducing task-relevant responses to speech in the sleeping brain.

Authors:  Sid Kouider; Thomas Andrillon; Leonardo S Barbosa; Louise Goupil; Tristan A Bekinschtein
Journal:  Curr Biol       Date:  2014-09-11       Impact factor: 10.834

10.  Asymmetrical Electroencephalographic Change of Human Brain During Sleep Onset Period.

Authors:  Doo-Heum Park; Chul-Jin Shin
Journal:  Psychiatry Investig       Date:  2017-11-07       Impact factor: 2.505

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