Corrigendum to “Internight reliability and benchmark values for computer analyses of non-rapid eye movement (NREM) and REM EEG in normal young adult and elderly subjects” [Clin. Neurophysiol. 112 (2001) 1540–1552]

University of California, Davis, Davis, California, United States
Clinical Neurophysiology (Impact Factor: 3.1). 09/2001; 112(8):1540-52. DOI: 10.1016/s1388-2457(02)00425-x
Source: PubMed


To determine the reliability of computer measured non-rapid eye movement (NREM) and REM frequency bands in the 0.3-45 Hz range and to provide benchmark data for these measures in young normal (YN) and elderly normal (EN) subjects (Ss).
Sleep EEG was recorded in 19 YN and 19 EN Ss on 4 non-consecutive baseline nights and simultaneously quantified as fast Fourier transform (FFT) power and 3 zero-cross period-amplitude (PA) measures: integrated amplitude, time in band and average wave amplitude.
The shapes of both the FFT and PA spectra differed among Ss but were highly consistent within individuals. Inter-night reliability of the separate frequency bands was correspondingly high. Despite substantial age effects, the reliability of computer-measured sleep EEG in the elderly equaled that of the YN Ss. Within both the YN and EN groups, the shapes of the NREM and REM spectral curves differed significantly. The NREM and REM also differed significantly in the two age groups.
Computer-measured sleep EEG is highly reliable across non-consecutive nights in both young and elderly normal Ss. The trait-like stability of these measures suggests they are genetically determined. This possibility is supported by twin study data that show strong heritability for FFT-measured waking EEG. The different shapes of NREM and REM spectra add further evidence that these are fundamentally different states of brain organization. The age differences in spectral shape, along with PA data for wave incidence, demonstrate that age effects on sleep EEG are not caused by changes in skull impedance or other non-cerebral factors.

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Available from: Irwin Feinberg, Feb 11, 2015
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    • "Sleep and performance spectrum in sleep implies the existence of inter-individual traitlike differences in sleep EEG (Tan et al., 2001). Trait variability seems particularly strong for slow wave sleep and for quantitatively assessed delta power in non-REM sleep EEG (Tucker et al., 2007). "
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    ABSTRACT: While sleep restriction decreases performance, not all individuals are equal with regard to sensitivity to sleep loss. We tested the hypothesis that performance could be independent of sleep pressure as defined by EEG alpha-theta power. Twenty healthy subjects (10 vulnerable and 10 resistant) underwent sleep deprivation for 25 h. Subjects had to rate their sleepiness (Karolinska Sleepiness Scale) and to perform a 10-min psychomotor vigilance task (PVT) every 2 h (20:00-08:00 hours). Sleep pressure was measured by EEG power spectral analysis (alpha-theta band 6.0-9.0 Hz). Initial performance, EEG spectral power and KSS score were equal in both groups (ANOVA, NS). The performance of vulnerable subjects significantly increased during the night (rANOVA, P < 0.01), whereas resistant subjects globally sustained their performance. Homeostatic pressure and subjective sleepiness significantly increased during the night (rANOVA, P < 0.01) identically in both categories (rANOVA, NS). Resistant subjects sustained their reaction time independently of the increase in homeostatic pressure. The phenotypic determinants of vulnerability to extended wakefulness remain unknown.
    Journal of Sleep Research 03/2008; 17(1):11-5. DOI:10.1111/j.1365-2869.2008.00629.x · 3.35 Impact Factor
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    • "In a further report (Palagini et al., 2000), it was also found that the stability within individuals for power in the delta and sigma bands was robust to administration of GABAergic agents. Although the statistical approach (based on correlation matrices) did not allow for quantitative conclusions, Feinberg and colleagues pointed out that these findings imply the existence of trait-like interindividual differences in the sleep EEG (Tan et al., 2001). Achermann and colleagues compared the EEG of baseline sleep to that of recovery sleep after 40 h of total sleep deprivation (Finelli et al., 2001; Tinguely et al., 2006). "
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    ABSTRACT: Despite decades of sleep research by means of polysomnography (PSG), systematic interindividual differences in PSG-assessed sleep parameters have been scarcely investigated. The present study is the first to quantify interindividual variability in standard PSG-assessed variables of sleep structure in terms of stability and robustness as well as magnitude. Twenty-one carefully screened healthy young adults were studied continuously in a strictly controlled laboratory environment, where their PSGs were recorded for eight nights interspersed with three separate 36 h sleep deprivation periods. All PSG records were scored blind to subject and condition, using conventional criteria, and delta power in the non-REM sleep EEG was computed for four electrode derivations. Interindividual differences in sleep variables were examined for stability and robustness, respectively, by comparing results across equivalent nights (e.g. baseline nights) and across experimentally differentiated nights (baseline nights versus recovery nights following sleep deprivation). Among 18 sleep variables analyzed, all except slow-wave sleep (SWS) latency were found to exhibit significantly stable and robust--i.e. trait-like--interindividual differences. This was quantified by means of intraclass correlation coefficients (ICCs), which ranged from 36% to 89% across physiologic variables, and were highest for SWS (73%) and delta power in the non-REM sleep EEG (78-89%). The magnitude of the trait interindividual differences was considerable, consistently exceeding the magnitude of the group-average effect on sleep structure of 36 h total sleep deprivation. Notably, for non-REM delta power--a putative marker of sleep homeostasis--the interindividual differences were from 9.9 to 12.8 times greater than the group-average increase following sleep deprivation relative to baseline. Physiologic sleep variables did not vary among subjects in a completely independent manner--61.1% of their combined variance clustered in three trait dimensions, which appeared to represent sleep duration, sleep intensity, and sleep discontinuity. Any independent functional significance of these sleep physiologic phenotypes remains to be determined.
    Journal of Sleep Research 07/2007; 16(2):170-80. DOI:10.1111/j.1365-2869.2007.00594.x · 3.35 Impact Factor
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    • "These data demonstrate that normal aging significantly affects the most prominent " phasic " component of rapid eye movement (REM) sleep. Tan et al. [24] had previously established that the " tonic " component of REM sleep (i.e. the power spectrum of its low-voltage EEG) is also altered by age. Power in the low EEG frequencies of stage REM in the elderly is below that of young adults but is above the young adult level in higher frequencies; the cross-over takes place at about 8 Hz. "
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