The effects of normal aging on sleep spindle and K-complex production

Crowley, Kate; Trinder, John; Kim, Young; Carrington, Melinda; Colrain, Ian M.

doi:10.1016/s1388-2457(02)00237-7

Cited by 213 publications

(183 citation statements)

References 56 publications

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“…They are greatly reduced in developmental abnormalities in children (Ellingson and Peters 1980;Selvitellia et al 2009;Godbout et al 2000;Limoges et al 2005), in adult schizophrenia (Ferrarelli et al 2007;Ferrarelli et al 2010;Manoach et al 2010;Manoach et al 2014) and in patients with Parkinson's disease with dementia (Latreille et al 2015). Spindle density, duration and amplitude decrease with age but the rate of decline is not the same in all subjects (Nicolas et al 2001;Crowley et al 2002;Guazzelli et al 1986;Wei et al 1999;Principe and Smith 1982). There is a correlation between age-related decline in spindle activity and decline in cognitive functioning (Peters et al 2008;Mander et al 2014).…”

Section: Assessment Of Sleep Spindles and K Complexesmentioning

confidence: 99%

The case for using digital EEG analysis in clinical sleep medicine

Younes

2017

Sleep Science Practice

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Evaluation of sleep in clinical polysomnograms continues to rely almost exclusively on visual scoring that implements rules proposed by Rechtschaffen and Kales nearly 50 years ago. Apart from its cost and timeconsuming nature, visual scoring has limitations including: A) Sleep depth, which is a continuous variable, is treated as if it changes in a stepwise fashion from light (stage 1), to intermediate (stage 2) to deep (stage 3). B) Even with this limited scale, there is considerable inter-scorer variability, particularly in scoring stages 1 and 3 of non-REM sleep, thereby adding uncertainty to %time spent in these stages as a reliable metric for evaluating sleep depth. C) Limitation in scoring some of EEG features, including 1) arousal intensity, 2) extent of Alpha intrusion and 3) frequency, and characteristics of sleep spindles and K complexes. Digital analysis can solve these problems but producing a reliable system has been a challenge. In this review I begin with recent advances in digital scoring of sleep according to the Rechtschaffen and Kales rules and conclude that this technology has progressed enough to make it possible to obtain reliable, reproducible scoring, comparable in accuracy to scoring by highly experienced technologists, with minimal editing. This is followed by description of several new metrics that can be obtained if digital scoring systems were to be used routinely in clinical studies. The scientific evidence supporting the potential of these metrics to positively impact sleep medicine practice and the wide range of such metrics in patients studied in the sleep laboratory are highlighted.

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Section: Assessment Of Sleep Spindles and K Complexesmentioning

confidence: 99%

The case for using digital EEG analysis in clinical sleep medicine

Younes

2017

Sleep Science Practice

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“…Late-life insomnia is associated with changes in the architecture of sleep. Compared with younger adults, older adults spend less time in SWS and in REM sleep [2][3][4], with reductions in delta wave amplitude [3], activity and density of REM sleep and sleep spindles [2], [4][5][6][7]. As a result, older adults' sleep is more fragmented, with frequent and longer awakenings [3], [8], [9].…”

Section: Insomnia In Older Adultsmentioning

confidence: 99%

Cognitive training improves sleep quality and cognitive function among older adults with insomnia

Haimov

Shatil

2013

Sleep Medicine

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Study Objectives: To investigate the effect of an eight-week, home-based, personalized, computerized cognitive training program on sleep quality and cognitive performance among older adults with insomnia.Design: Participants (n = 51) were randomly allocated to a cognitive training group (n = 34) or to an active control group (n = 17). The participants in the cognitive training group completed an eight-week, home-based, personalized, computerized cognitive training program, while the participants in the active control group completed an eight-week, home-based program involving computerized tasks that do not engage high-level cognitive functioning. Before and after training, all participants' sleep was monitored for one week by an actigraph and their cognitive performance was evaluated.Setting: Community setting: residential sleep/performance testing facility.Participants: Fifty-one older adults with insomnia (aged 65-85).Interventions: Eight weeks of computerized cognitive training for older adults with insomnia.Results: Mixed models for repeated measures analysis showed between-group improvements for the cognitive training group on both sleep quality (sleep onset latency and sleep efficiency) and cognitive performance (avoiding distractions, working memory, visual memory, general memory and naming). Hierarchical linear regressions analysis in the cognitive training group indicated that improved visual scanning is associated with earlier advent of sleep, while improved naming is associated with the reduction in wake after sleep onset and with the reduction in number of awakenings. Likewise the results indicate that improved ''avoiding distractions'' is associated with an increase in the duration of sleep. Moreover, the results indicate that in the active control group cognitive decline observed in working memory is associated with an increase in the time required to fall asleep.Conclusions: New learning is instrumental in promoting initiation and maintenance of sleep in older adults with insomnia. Lasting and personalized cognitive training is particularly indicated to generate the type of learning necessary for combined cognitive and sleep enhancements in this population.

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“…K-Complexes can thus be used to test the ability of the brain to produce large amplitude synchronized waveforms. Aging has been shown to impact delta generation during sleep with a decrease in the incidence of spontaneous K-complexes (Crowley et al 2002b;Kubicki et al 1989) as well as the incidence and amplitude of the evoked K-complex (Colrain et al 2010;Crowley et al 2004;Crowley et al 2002a). A linear regression analysis ( Fig.…”

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confidence: 99%

Sleep and Sleep Disorders in Older Adults

2011

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A common but significant change associated with aging is a profound disruption to the daily sleep-wake cycle. It has been estimated that as many as 50% of older adults complain about difficulty initiating or maintaining sleep. Poor sleep results in increased risk of significant morbidity and mortality. Moreover, in younger adults, compromised sleep has been shown to have a consistent effect on cognitive function, which may suggest that sleep problems contribute to the cognitive changes that accompany older age. The multifactorial nature of variables affecting sleep in old age cannot be overstated. Changes in sleep have been thought to reflect normal developmental processes, which can be further compromised by sleep disturbances secondary to medical or psychiatric diseases (e.g., chronic pain, dementia, depression), a primary sleep disorder that can itself be age-related (e.g., Sleep Disordered Breathing and Periodic Limb Movements During Sleep), or some combination of any of these factors. Given that changes in sleep quality and quantity in later life have implications for quality of life and level of functioning, it is imperative to distinguish the normal age-related sleep changes from those originating from pathological processes.

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The effects of normal aging on sleep spindle and K-complex production

Cited by 213 publications

References 56 publications

The case for using digital EEG analysis in clinical sleep medicine

The case for using digital EEG analysis in clinical sleep medicine

Cognitive training improves sleep quality and cognitive function among older adults with insomnia

Sleep and Sleep Disorders in Older Adults

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