A neuronal group theory of sleep function

Krueger, James M.; Obál, F.

doi:10.1111/j.1365-2869.1993.tb00064.x

Cited by 272 publications

(173 citation statements)

References 29 publications

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“…These results lend support to the notion that sleep is not only a global phenomenon, and that its intensity can be regulated at a regional level. 49 Consistent with this, previous studies in humans found that intermittent vibration of one hand produces a transient and small increase in SWA in the contralateral somatosensory cortex, 50 while whisker stimulation in rodents produces an increase in SWA in the contralateral somatosensory cortex. 51,52 Increases in SWA also occur in circumscribed cortical areas after learning a rotational adaptation task, 7 after TMS-induced stimulation of motor cortex, 9 or following paired associative stimulation within sensorimotor cortex, 11 while arm immobilization decreases SWA.…”

Section: Arc Stainingsupporting

confidence: 72%

Effects of Skilled Training on Sleep Slow Wave Activity and Cortical Gene Expression in the Rat

Hanlon

Faraguna

Vyazovskiy

et al. 2009

Sleep

142

131

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SO FAR. IN MAMMALS, THE BEST CHARACTERIZED marker of sleep homeostasis is slow wave activity (SWA), the power density in the electroencephalogram (EEG) between 0.5 and 4 Hz during NREM sleep. SWA is high at sleep onset and declines during sleep, suggesting that it may reflect the accumulation of sleep pressure as a function of duration and/or intensity of prior waking. 1,2 Why and how SWA should reflect sleep homeostasis, however, is still unclear.We hypothesized that SWA is high at sleep onset because it reflects the occurrence, during waking, of widespread synaptic potentiation in cortical and subcortical areas. 3,4 This increase would be detrimental in the long term, because stronger synapses need more energy, space, and cellular supplies, and may lead to saturation of the ability to learn. Sleep would thus be crucial to renormalize synaptic strength to an energetically sustainable level. Molecular and electrophysiological markers of synaptic potentiation increase after waking in rat cortex and hippocampus, while markers of synaptic depression do so after sleep. 5,6 Moreover, in rats and humans, procedures presumably leading to synaptic potentiation or depression result in SWA increases and decreases, respectively. 7-12 More specifically, a study in humans using highdensity EEG found that performing a visuomotor learning task produced a local increase in SWA during subsequent sleep. 7 The increase was restricted to the right parietal cortical areas presumably modified by learning. 13 Moreover, it was specific for NREM sleep, reversible within the first 90 minutes of sleep, and correlated with the improvement in performance after sleep. 7 However, there is no direct evidence that the motor adaptation task used in that study activates neurons in parietal cortex, nor that it causes synaptic potentiation specifically in that region.Previous studies have suggested that activity-dependent genes activated during a specific waking experience may be reactivated during sleep, perhaps to potentiate the same synapses previously engaged during waking. 14 Ribeiro and colleagues found that the exposure to a new environment for 3 hours 15 results in the immediate cortical and hippocampal induction, during waking, of plasticity-related gene zif-268, 16 followed by its downregulation during NREM sleep, and then again by its increased expression during REM sleep (relative to NREM sleep). Intriguingly ~ 3 min of NREM sleep were enough to downregulate waking-induced zif-268 expression, and ~ 2 min of REM sleep were sufficient to detect its selective reinduction, even if both NREM and REM rats were awake during the last 30 min before sacrifice. Another study 17 recently found, using fluorescent in situ hybridization, that the number of hippocampal CA1 neurons showing induction of Arc and/or Homer1a was similar during "rest" periods before and after the exploration of a new environment. However, more cells were active during both exploration and post-task rest than during exploration and pre-task rest. Based on these findings, it h...

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Section: Arc Stainingsupporting

confidence: 72%

Effects of Skilled Training on Sleep Slow Wave Activity and Cortical Gene Expression in the Rat

Hanlon

Faraguna

Vyazovskiy

et al. 2009

Sleep

142

131

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“…It may be associated with the reduction of regional cerebral blood flow which is known to occur during slow wave sleep (Finelli et al 2000b; for a review see Maquet 2000) as well as in the course of prolonged waking (Thomas et al 1998(Thomas et al , 2000. These findings support the hypothesis that sleep has a local, use-dependent, facet and that cerebral structures that had been particularly active during waking may exhibit more intensive signs of sleep (Horne 1993;Krueger and Obál 1993;Kattler et al 1994;Benington and Heller 1995;Borbély and Achermann 2000).Studies on regional differences in the sleep EEG are typically based on the statistical analysis of the records from several subjects. This approach emphasizes the changes common to all subjects, and tends to disregard individual differences.…”

mentioning

confidence: 89%

Individual 'Fingerprints' in Human Sleep EEG Topography

Finelli

Achermann

Borbély

2001

Neuropsychopharmacology

172

129

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The sleep EEG of eight healthy young men was recorded from 27 derivations during a baseline night and a recovery night after 40 h of waking. Individual power maps of the nonREM sleep EEG were calculated for the delta, theta, alpha, sigma and beta range. The comparison of the normalized individual maps for baseline and recovery sleep revealed very similar individual patterns within each frequency band. This high correspondence was quantified and statistically confirmed by calculating the Manhattan distance between all pairs of maps within and between individuals. Although prolonged waking enhanced power inthe low-frequency range and reduced power in the high-frequency range Sleep is generally regarded as a global brain process. Recently, regional aspects of sleep have gained increasing attention. Early reports that the location of the recording electrodes affects the pattern of the sleep EEG (Findji et al. 1981;Buchsbaum et al. 1982;Hori 1985) were reexamined by using contemporary methods of quantitative EEG analysis. Power spectra along the antero-posterior axis were shown to exhibit frequencyspecific and state-dependent gradients (Werth et al. 1996(Werth et al. , 1997) with a frontal predominance in the 2-Hz band during the initial part of sleep. This hyperfrontality of low-frequency activity was accentuated by sleep deprivation (Cajochen et al. 1999). It may be associated with the reduction of regional cerebral blood flow which is known to occur during slow wave sleep (Finelli et al. 2000b; for a review see Maquet 2000) as well as in the course of prolonged waking (Thomas et al. 1998(Thomas et al. , 2000. These findings support the hypothesis that sleep has a local, use-dependent, facet and that cerebral structures that had been particularly active during waking may exhibit more intensive signs of sleep (Horne 1993;Krueger and Obál 1993;Kattler et al. 1994;Benington and Heller 1995;Borbély and Achermann 2000).Studies on regional differences in the sleep EEG are typically based on the statistical analysis of the records from several subjects. This approach emphasizes the changes common to all subjects, and tends to disregard individual differences. However, individual features may be important. This was recently demonstrated in a study where the relationship between the waking and sleep EEG was investigated (Finelli et al. 2000a). Examining the individual time course of theta power in the waking EEG in the course of a 40-h sleep deprivation period revealed a correlation with the change in delta power in the nonREM sleep EEG. The results suggested that a common regulatory process might control specific parts of the waking and sleep EEG. The aim of the present analysis was to investigate the individual topographic distribution of power in non-REM sleep before and after sleep deprivation, a manipulation known to cause massive changes in the sleep EEG. SUBJECTS AND METHODSEight right-handed healthy male subjects (mean age 23 y Ϯ 0.46 SEM, range 21-25 years) participated in the study. They were selected on the bas...

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“…82,83 It was also proposed that sleep is influenced by prior synaptic use, and functions to alter synaptic connections, in part through the local production of somnogenic compounds that include cytokines. 84,85 Another conjecture is that sleep acts to downscale the strengths of synaptic connections, so that increases in synaptic strength during wakefulness stay below mechanistically infeasible limits. 8,26,[86][87][88][89] This hypothesis is related to the earlier demonstration that the firing by neurons and the strengths of their synapses are homeostatically increased or decreased to maintain firing rates within certain boundaries.…”

Section: Introductionmentioning

confidence: 99%

Augmented generation of protein fragments during wakefulness as the molecular cause of sleep: a hypothesis

Varshavsky

2012

Protein Science

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Despite extensive understanding of sleep regulation, the molecular-level cause and function of sleep are unknown. I suggest that they originate in individual neurons and stem from increased production of protein fragments during wakefulness. These fragments are transient parts of protein complexes in which the fragments were generated. Neuronal Ca 21 fluxes are higher during wakefulness than during sleep. Subunits of transmembrane channels and other proteins are cleaved by Ca 21 -activated calpains and by other nonprocessive proteases, including caspases and secretases. In the proposed concept, termed the fragment generation (FG) hypothesis, sleep is a state during which the production of fragments is decreased (owing to lower Ca 21 transients) while fragment-destroying pathways are upregulated. These changes facilitate the elimination of fragments and the remodeling of protein complexes in which the fragments resided. The FG hypothesis posits that a proteolytic cleavage, which produces two fragments, can have both deleterious effects and fitness-increasing functions. This (previously not considered) dichotomy can explain both the conservation of cleavage sites in proteins and the evolutionary persistence of sleep, because sleep would counteract deleterious aspects of protein fragments. The FG hypothesis leads to new explanations of sleep phenomena, including a longer sleep after sleep deprivation. Studies in the 1970s showed that ethanol-induced sleep in mice can be strikingly prolonged by intracerebroventricular injections of either Ca 21 alone or Ca 21 and its ionophore (Erickson et al., Science 1978;199:1219-1221 Harris, Pharmacol Biochem Behav 1979;10:527-534; Erickson et al., Pharmacol Biochem Behav 1980;12:651-656). These results, which were never interpreted in connection to protein fragments or the function of sleep, may be accounted for by the FG hypothesis about molecular causation of sleep.

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A neuronal group theory of sleep function

Cited by 272 publications

References 29 publications

Effects of Skilled Training on Sleep Slow Wave Activity and Cortical Gene Expression in the Rat

Effects of Skilled Training on Sleep Slow Wave Activity and Cortical Gene Expression in the Rat

Individual 'Fingerprints' in Human Sleep EEG Topography

Augmented generation of protein fragments during wakefulness as the molecular cause of sleep: a hypothesis

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