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Excessive daytime sleepiness (EDS) is characterized by difficulty staying awake during daytime, though additional features may be present. EDS is a significant problem for clinical and non-clinical populations, being associated with a range of negative outcomes that also represent a burden for society. Extreme EDS is associated with sleep disorders, most notably the central hypersomnias such as narcolepsy, Kleine-Levin syndrome, and idiopathic hypersomnia (IH). Although investigation of these conditions indicates that EDS results from diminished sleep quality, the underlying cause for this impairment remains uncertain. One possibility could be that previous research has been too narrow in scope with insufficient attention paid to non-sleep-related aspects. Here, we offer a broader perspective in which findings concerning the impact of EDS on cortical functioning are interpreted in relation to current understanding about the neural basis of consciousness. Alterations in the spatial distribution of cortical activity, in particular reduced connectivity of frontal cortex, suggest that EDS is associated with an altered state of consciousness.
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SLEEP BREATHING PHYSIOLOGY AND DISORDERS REVIEW
The neurophysiological basis of excessive daytime sleepiness:
suggestions of an altered state of consciousness
P. K. Hitchcott
1
&D. Menicucci
1
&S. Frumento
1
&A. Zaccaro
1
&A. Gemignani
1,2,3
Received: 8 March 2019 / Revised: 3 May 2019 / Accepted: 8 May 2019
#Springer Nature Switzerland AG 2019
Abstract
Excessive daytime sleepiness (EDS) is characterized by difficulty staying awake during daytime, though additional features may
be present. EDS is a significant problem for clinical and non-clinical populations, being associated with a range of negative
outcomes that also represent a burden for society. Extreme EDS is associated with sleep disorders, most notably the central
hypersomnias such as narcolepsy, Kleine-Levin syndrome, and idiopathic hypersomnia (IH). Although investigation of these
conditions indicates that EDS results from diminished sleep quality, the underlying cause for this impairment remains uncertain.
One possibility could be that previous research has been too narrow in scope with insufficient attention paid to non-sleep-related
aspects. Here, we offer a broader perspective in which findings concerning the impact of EDS on cortical functioning are
interpreted in relation to current understanding about the neural basis of consciousness. Alterations in the spatial distribution
of cortical activity, in particular reduced connectivity of frontal cortex, suggest that EDS is associated with an altered state of
consciousness.
Keywords Sleep .Hypersomnia .Excessive daytime sleepiness .Altered state of consciousness
Introduction
EDS in the general population
Excessive daytime sleepiness (EDS) is characterized by per-
sistent difficulty staying awake during the daytime and can be
associated with additional features (Bsleep drunkenness^)
though these are more common in clinical populations.
Severity typically varies over time, though a significant mi-
nority experience persistent, clinically significant EDS lasting
years [1,2]. EDS is a relatively common complaint which
negatively impacts both individuals and society in general.
Studies have shown that EDS is associated with a wide range
of negative effects related to all aspects of health (somatic,
neurological and psychological), including disability,
morbidity, and mortality. Beyond its health consequences,
EDS is implicated in poor academic and workplace perfor-
mance and is a major determinant of road traffic accidents
[38].
Reported prevalence rates for EDS vary widely, ranging
from < 1% to > 30% [see 9]. This variability relates to several
factors, including how EDS is defined and operationalized.
One significant issue is the need to reliably contrast between
EDS and fatigue. Though both states are associated with sub-
jective feelings of physical and/or mental tiredness, a core
distinction is that EDS is related to increased sleep propensity
whereas fatigue is not. Thus, fatigue resolves with rest, with-
out a need for sleep whereas EDS does not [10,11].
Epidemiological surveys assessing EDS based on less strin-
gent criteria (the use of 1 or 2 basic self-report items is not
uncommon) necessarily struggle to discriminate EDS from
fatigue. Moreover, although objective assessment of sleep
propensity is possible (the Multiple Sleep Latency Test)
[12], this methodology is impracticable for epidemiological
survey since it requires attendance at a sleep laboratory.
Consequently, standardized questionnaires, the Epworth
Sleepiness Scale (ESS) [13] being the most popular, represent
a suitable compromise. The ESS attempts to capture sleep
propensity by specifically assessing participantstendency to
*A. Gemignani
angelo.gemignani@unipi.it
1
Department of Surgical, Medical and Molecular Pathology and
Critical Care Medicine, University of Pisa, Pisa, Italy
2
National Research Council, Institute of Clinical Physiology,
Pisa, Italy
3
Azienda Ospedaliero-Universitaria Pisana, Pisa, Italy
Sleep and Breathing
https://doi.org/10.1007/s11325-019-01865-9
fall asleep inseveral commonsituations,and a cut-off score >
10 identifies clinically significant EDS [13]. Similar alterna-
tive instruments include the Stanford Sleepiness Scale [14]
and the Karolinska Sleepiness Scale [15].
Although most estimates of EDS prevalence fall within the
range of 515% [9], not all surveys have been performed in
samples representative of the general population. This is sig-
nificant since demographic variables, for example age [16], can
substantially affect prevalence estimates. Reports of sizeable
same-study differences in EDS rates from different countries
(e.g., 25% in the UK vs 3.5% in Spain) [17] and of a ~ 30%
increase in prevalence between 2002 and 2012 [18]further
complicate this picture. Studies with more rigorous methodol-
ogies conducted in larger, representative samples may be more
accurate, and these would seem to suggest that EDS prevalence
is higher than sometimes stated. For example, in a study of
almost 16,000 adults, aged 18102, Ohayon, Dauvilliers, and
Reynolds [2] estimated the overall prevalence of EDS at
27.8%. This value is close to that obtained by Jaussant et al.
[19] who reported an overall EDS prevalence of 33% in a study
of > 2000 individuals aged 1889 years using the ESS. While
not all similar previous research has yielded such high esti-
mates, rates of ~ 20% are not uncommon [20,21].
EDS has been reported to be significantly associated with a
diverse array of factors. These include sociodemographic
(e.g., age, gender, educational level), lifestyle (e.g., caffeine
and nicotine use, physical exercise), health (e.g., sleep disor-
ders, neurological and somatic diseases), and psychological
(e.g., anxiety and depression symptoms) variables [22]. One
significant gap in the literature relates to which of these causes,
or affect the progression of, EDS since little longitudinal re-
search has been conducted. However, one recent prospective
investigation [19] noted that while the severity of EDS fluctu-
ates in the majority of individuals, it exists in a more severe or
persistent form in some. Whereas fluctuations in EDS severity
were related to lifestyle and psychological influences, chronic
ill health was the main cause of persistent EDS. Replication
and extension of these findings would be especially valuable
for consolidating understanding about both the nature and
causes of EDS within the general population.
EDS and primary hypersomnias
Although there is an obvious relationship between EDS and
chronic sleep loss (or poor sleep quality), it occurs with
highest frequency (and is a defining feature) of several chronic
hypersomnias, including narcolepsy (with and without cata-
plexy), idiopathic hypersomnia (IH), and Kleine-Levin syn-
drome. While EDS is a shared symptom, a small number of
distinctive clinical features distinguish these disorders.
Narcolepsy with cataplexy is characterized by rapid entries
into rapid-eye-movement sleep (SOREMPs), the presence of
cataplexy (episodes of muscle atony triggered by emotional
stimulation), and a deficit of hypocretin-1 in the cerebrospinal
fluid. Kleine-Levin syndrome is extremely rare (~200 cases
have been reported) and characterized by recurrent
hypersomnia accompanied by hyperphagia and hypersexuali-
ty [1,23,24]. The exact prevalence of IH is unclear because of
changeable diagnostic criteria but affects ~ 5% of patients
with clinically significant EDS. A rough estimate of 50/10
6
has been suggested based on the 510 times lower frequency
of IH relative to narcolepsy [1], although some studies have
suggested much higher rates [2527]. There is, moreover, un-
certainty about whether IH is a unitary condition. Until quite
recently, two forms of IH were distinguished according to
whether individuals display prolonged (> 10 h) or normal (>
6 h and < 10 h) nocturnal sleep [28,29].
While EDS is a shared feature of all hypersomnias, IH is
the quintessential EDS disorder. This is evident from the most
recent diagnostic classification criteria [23] and from detailed
characterizations of IH [e.g., 30]. The latter indicate that rela-
tive to healthy controls, individuals with IH are more likely to
report unrefreshing sleep despite normal or unusually long (>
10 h) sleep and problematic transition from sleep to wakeful-
ness. Difficulties waking without return to sleep are common
and in ~ 3040% of individual symptoms of sleep drunken-
ness, such as motor discoordination, confusion, and automatic
behavior may be present. Patients also report reduced alertness
and ability to focus/concentrate throughout the day with an
increased need to lay down/nap, though as with nocturnal
sleep, this tends not to be refreshing. Few non-EDS features
are evident though psychological (anxiety and depression)
and somatic (e.g., temperature dysregulation, digestion prob-
lems) symptoms are more common. In addition, the diagnosis
of IH requires not only that there should be almost daily EDS
lasting 3 months but also the exclusion of any other of the
known causes of EDS [23]. This includes hypersomnia due to
mental disorder. Although differential diagnosis may be prob-
lematic, based on differential changes in polysomnographic
parameters, it has been suggested that whereas psychiatric
hypersomnia is a disorder of hyperarousal, primary
hypersomnia is a disorder of hypoarousal [31]. Overall, as
IH is near-exclusively a disorder of EDS, it may be an ideal
population in which to probe the neurophysiological basis of
EDS. Previous authors have drawn the same conclusion [32].
To date, no biological mechanism selective for EDS has
been identified. Despite considerable excitement about human
and animal evidence indicating hypocretin deficiency as a key
substrate for narcolepsy with cataplexy [33,34], CSF
hypocretin levels are normal in several other sleep disorders
including IH [3537]. Moreover, the exact role of hypocretin
dysfunction in the pathophysiology of narcolepsy is unclear
[see 38] with some indications that it is related to non-EDS
features of the disorder [37,39]. Although isolated reports
[40] have identified alternative potential causes of EDS, de-
finitive evidence remains absent. Given the highly complex
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chemical neuroanatomy of sleep/wake control mechanisms
[41], a pragmatic starting point for investigating the neuro-
physiological basis of EDS is more likely to be in terms of
macro brain activity related to the known functions of sleep.
The function(s) of sleep
Sleep is defined as a rapidly reversible state characterized by
reductions in responsiveness to sensory stimuli, motor activi-
ty, and metabolism. The conservation of sleep across species
[42] and the profound consequences of prolonged deprivation
[43,44] are widely interpreted to indicate that it subserves one
or more vital functions. Although no single unifying explana-
tion is available, several theories have emerged that provide
partially overlapping explanations related to subsets of the
available evidence. This fragmentation reflects, in part, the
fact that two distinctive sleep states exist in humans: rapid
eye movement (REM) and non-REM (NREM). These states
are differentiated based on electroencephalographic (EEG)
and electromyographic (EMG) parameters and, in addition,
possess distinct underlying neurophysiological control mech-
anisms. In NREM, most bodily functions slow and there is
diminished responsivity to sensory stimuli and reduced mus-
cle tone though thermoregulation remains. Breathing is slow
and regular, accompanied by reduced heart rate and heat pro-
duction with slight temperature reduction. The NREM EEGis
characterized by high voltage, low frequency (delta and theta)
activity, and the presence of spindles and k-complexes (isolat-
ed high voltage waves occurring spontaneously or after sen-
sory stimulation). One hallmark of slow wave sleep (SWS) is
the presence of slow (< 1 Hz) oscillations [45,46]thatreflects
widespread, synchronicity of neuronal up (depolarized) and
down (hyperpolarized) states thought to derive in vivo from
thalamo-cortical interplay [47]. During REM sleep, there is
deep muscular relaxation and sensory thresholds are in-
creased; sudden eye movements, muscular twitches, and
dreaming occur. Homeostatic regulation declines as indicated
by increased heart rate variability, irregular respiration, and
poikilothermy. The REM EEG appears similar to that during
waking with low-voltage mixed frequencies [41,48]. The
marked differences between REM and NREM sleep suggest
that they may promote separate functions [49].
Most, but not all, theories of sleep function assume that it
has adaptivephysiological significance. An alternative view is
that sleep is primarily an adaptive behavioral state that pro-
motes dormancy (reducing energy expenditure) when waking
activity is not beneficial [50]. The more common concept, that
sleep performs an essential physiological function, centers on
two main themes: nervous system recuperation and synaptic
plasticity. NREM sleep is most closely associated with theo-
ries of physiological recuperation as brain energy metabolism
reaches a minimum during its deepest stages, i.e., during
SWS. In contrast, brain metabolism during REM sleep is
similar to that during wakefulness [51,52]. It has been sug-
gested both that sleep restores key macromolecules in prepa-
ration for wakefulness [53] and that it aids the removal of toxic
by-products of increased waking activity [54,55]. The former
idea is supported by evidence that rates of protein synthesis
are highest during SWS [56]. Findings consistent with the
latter theme include reports that sleep deprivation causes neu-
ronal degradation and thatthis is moremarked in brain regions
with high metabolic activity [57,58]. One crucial develop-
ment in this area is the demonstration of a ~ 60% increase in
cortical interstitial space during sleep that facilitates clearance
of potentially harmful degradation products accumulated dur-
ing wakefulness. This effect is believed to be mediated by
noradrenergic effects on astroglial cell morphology [55,59].
Such findings add to growing evidence implicating neuronal-
glial interactions as an important source of sleep/wake control
[60,61].
A second mainstream theory is that sleep is related to mem-
ory consolidation. During consolidation, memory engrams
that are initially labile traces susceptible to interference are
progressively stabilized (Bsynaptic consolidation^) and inte-
grated into existing information networks (Bsystems
consolidation^) by serial neurobiological processes operating
over widely varying time spans [62,63]. The fundamental
basis of synaptic consolidation is the alteration of synaptic
strengths within the neural networks within which the memo-
ry trace is held. The main ways in which learning changes
synaptic strengths are via long-term potentiation (LTP) and
long-term depression (LTD). Key cellular processes include
the activation of glutamatergic synapses and, via their activa-
tion, the triggering of various signal transduction cascades,
protein synthesis, and pre- and post-synaptic morphological
changes [64]. Whereas synaptic consolidation occurs within a
timeframe of seconds-hours, systems consolidation requires
days-months and its underlying substrates are less well under-
stood. However, sleep is believed to play a key role [65].
It has long been recognized that when sleep follows a learn-
ing event, subsequent recall is improved [66]. Explanations
for this effect have evolved. It was at first suggested that sleep
protected recently encoded memories from retroactive inter-
ference; that during sleep, new learning was prevented and
thereby ongoing consolidation would continue undisrupted.
Thus, memory facilitation was seen as a corollary of sleep
unrelated to any direct impact on memory consolidation pro-
cesses per se. This view has been superseded in light of evi-
dence suggesting that sleep actively promotes consolidation.
One significant line of research supporting this hypothesis has
demonstrated that high-speed, distributed replay of waking
experiences takes place during SWS [67]. This and related
evidence have led to proposals that sleep facilitates various
facets of system consolidation including the integration of
new and existing knowledge [68] and insight [69]. Although
the neurophysiological bases of such effects are not yet fully
Sleep Breath
clear, one key finding is that boosting slow oscillations during
sleep by means of transcranial electrical stimulation potenti-
ates memory [70]. Additional evidence suggests that sleep
may also play an active role in synaptic consolidation [71].
In this case, REM sleep and specific associated features (e.g.,
theta activity), rather than NREM sleep, is implicated.
The neurophysiological basis of EDS
While there may be no consensus about the function of sleep,
the primary contemporary hypotheses described above never-
theless suggest useful starting points from which to explore
the neurophysiological basis of EDS. Most obviously, EDS
can be considered as a dysregulation of normal sleep regula-
tory processes and these can be explored in relation to main
functions of sleep. The following section will commence in
this manner. However, in an attempt to diversify thinking on
this topic, we will explore the possibility that EDS might also
be a state of altered consciousness. The foundation for this
hypothesis relates to tantalizing hints that neurophysiological
dysfunction in EDS occurs within similar neuronal circuitry
demonstrated to be involved in consciousness. Our aim is to
conduct an open inquiry of this possibility and various gaps in
the literature will be over-looked in favor of describing some
intriguing, albeit speculative, connections.
Several studies have investigated the possibility that EDS is
caused by dysfunction of normal regulatory sleep processes.
Three basic processes have been hypothesized to underlie
sleep regulation, one of which (process S) is a homeostatic
mechanism that increases in strength as a function of time
awake and dissipates during sleep. Sforza et al. [72]tested
two hypotheses linking EDS to either over- or under-activity
of process S. The former idea relates EDS to an excessive
build-up of process S during the daytime and/or insufficient
dissipation during sleep. The latter postulate considers EDS a
product of deficient recuperative sleep caused by
hypofunctioning process S. These contrary hypotheses were
tested by assessing slow wave activity (SWA; 0.754.5 Hz)
during the first two sleep cycles as an index of the level of
process S activity. The results showed reduced SWA in IH
patients compared to healthy controls implying EDS results
from a deficit in recuperative sleep. This conclusion is rein-
forced by the observation of altered sleep microstructure, in-
cluding increased sleep fragmentation and decreased delta
power in IH [29,32]. Thus, increased sleep duration and
EDS can be seen as the consequences of impaired sleep qual-
ity. Findings about changes in sleep structure are less clear.
Most studies have not found polysomnographic differences in
either REM or NREM sleep percentages [28,32,72]. In con-
trast, one previous report [29] observed decreased stage 34
sleep percentage and increased REM sleep percentage in IH.
Despite this discordance, these studies are consistent in indi-
cating that there are no changes in NREM (or SWS), for
example increased NREM duration, which might compensate
for impaired sleep quality.
A reasonable conjecture is that the deficit in NREM sleep
quality in IH is associated with the high frequency of cognitive
complaints in this population. However, it is well established
that subjective cognitive complaints are an unreliable index of
objective cognitive impairment [73,74]. One pertinent issue is
that subjective complaints are amplified by depressive symp-
tomatology, which is increased in IH [28]. Too few studies
profiling cognitive impairments using objective measures
have been conducted to identify which specific cognitive pro-
cesses are actually impaired. Occasional reports of attentional
deficits exist [75,76], and these are consistent both with the
problems self-reported by IH patients [30] and broader evi-
dence concerning objective deficits in narcoleptic patients
[77]. However, too little data about objective cognitive impair-
ment in hypersomnic patients is available to draw any firm
conclusions. Overall, the limited available data suggest im-
pairments in frontal cortical substrates of executive function
might be present but whether the profile of cognitive impair-
ment in IH mirrors the selective deficit pattern observed in
narcoleptic patients [77] or following sleep deprivation in
healthy subjects [78] is unknown. Despite this uncertainty,
the existence of working memory/executive impairment
would be consistent with additional evidence concerning
structural and functional alterations of frontal cortex in IH.
Several studies have examined structural and functional
brain alterations in hypersomnic patients and healthy sleep-
deprived subjects. Crucially, alterations extraneous to the hy-
pothalamus, both in cortical and subcortical areas, potentially
indicative of abnormalities within the default-mode network,
have been documented [79]. Whether similar changes are
present in the brains of IH patients is less clear as compara-
tively few studies have been performed. However, growing
evidence points to a role of the frontal cortexin EDS. Reduced
gray matter volume within the ventromedial prefrontal
(vmPFC) and orbital (OFC) regions of frontal cortex is both
common to a number of sleep disorders and associated with
increased daytime sleepiness (higher ESS scores) in healthy
individuals [80]. Measurements of regional glucose metabo-
lism and blood flow are also consistent with a relationship
between the prefrontal cortex and EDS. Relevant observations
include reports of reduced activity within the vmPFC follow-
ing overnight sleep deprivation [81] and of a negative corre-
lation between ESS scores and cerebral blood flow in the
medial prefrontal cortex [82]. Of particular interest are indica-
tions that the pattern of daytime regional cerebral blood flow
(rCBF) in IH patients closely resembles that seen in sleeping
healthy subjects [83]. As others [82]havenoted,thissuggests
that during wakefulness, IH patients experience an NREM-
like metabolism pattern. It seems reasonable to associate this
observation with the evidence (described above) on reduced
sleep quality (decreased delta power) and the normal or
Sleep Breath
decreased percentage of NREM sleep in IH. Moreover, these
data, along with the specific correlation between delta power
and rCBF within the vmPFC [83], reinforces the view that
vmPFC disturbances are a central feature of EDS. These re-
flect a key feature of broader deficits affecting default-mode
network structures are related to EDS, a common feature of
central hypersomnias.
Can EDS be considered an altered state
of consciousness?
It has been argued that consciousness has two main compo-
nents: wakefulness and awareness, the levels of which are
positively correlated in most circumstances [84]. Altered
states of consciousness are, therefore, normally reflected in
continuous variation along the regression between these com-
ponents. Though normallycorrelated, wakefulness and aware-
ness can be dissociated at multiple levels, including
neuroanatomically. Wakefulness is controlled principally by
subcortical arousal systems including monoamine and cholin-
ergic nuclei located in the region of the upper brainstem [85]
and chemically diverse mechanisms originating in the hypo-
thalamus [86]. In contrast, brain areas involved in awareness
include several cortical regions including the insula, medial
prefrontal, and cingulate cortices, though several non-cortical
regions are also critically involved [87]. This broader anatom-
ical distribution is most likely related to the existence of mul-
tiple networks that subserve distinct aspects of awareness.
During sleep, there is a substantial decrease in connectivity
across cortical regions with frequent breakdowns of temporal
integration linked to the occurrence of spontaneous slow os-
cillations. This phenomenon is thought to explain why sleep is
associated with a loss of consciousness despite continued,
though decreased, neuronal activity [88,89]. Crucially, vari-
ous studies indicate that sleep deprivation also disturbs func-
tional connectivity. Moreover, this occurs within areas or net-
works implicated in consciousness. Findings derive from in-
vestigations employing various techniques including func-
tional magnetic resonance imaging (fMRI) [90,91]and
high-density EEG [92]. Collectively, the results of such stud-
ies consistently indicate that sleep deprivation results in de-
creased connectivity within different brain networks including
the default-mode network (DMN). In addition, the study by
Verweij et al. [92] detected alterations in both alpha and theta
EEG bands indicating reduced local and globalefficacy within
the frontal aspects of the DMN. This observation is significant
given the critical role of frontal cortex in various functions
including cognition [93], emotion [94], and as a site associated
with the neural representation of self [95]. Thus, sleep
deprivation-related changes in cortical connectivity are un-
likely to reflect altered wakefulness solely. Moreover, such
functions are considered central for self-conscious awareness
which is lost or at least greatly diminished by deactivation of
the prefrontal cortex during sleep [96]. Indeed, substantial
sleep-related changes in blood flow occur within the prefron-
tal cortex although selective reactivations within posterior and
ventromedial prefrontal areas are present during REM sleep.
The continued deactivation of dorsolateral PFC has been sug-
gested to underlie illogical (non-executive) thinking during
dreaming [97] whereas prefrontal reactivation during REM
sleep is linked with consolidation of emotional memories [98].
Overall, the prefrontal cortex appears to be highly sensitive
to sleep deprivation and subjective sleepiness, in healthy con-
trols, is associated with altered EEG patterns involving the
PFC. In particular, sleepiness correlates both with increased
theta and decreased alpha activity and the former correlates
with cognitive task performance [99,100]. Increased theta
activity following sleep deprivation has attracted much atten-
tion because of evidence that it could be a marker for Blocal
sleep,^i.e., transient neuronal off periods [101]. These events
have been linked with performance errors in humans, the na-
ture of which depend on the location of the off period within
the cortex [102]. Although such data identifies increased fron-
tal theta activity as a correlate of EDS in healthy individuals,
similar studies do not appear to have been conducted in IH
subjects. Investigations of resting-state cerebral metabolism
are unhelpful since this is reported both to be increased
[103] and decreased [82] in IH though dissociated alterations
in distinct cortical networks (e.g., salience vs default-mode
networks) might explain this disparity. Nonetheless, it is worth
noting that when cortical theta activity is modified in healthy
non-sleep-deprived subjects, either by mechanical stimulation
of the olfactory epithelium [104] or slow nasal breathing
[105], shifts in consciousness, more specifically, shifts in
awareness have been observed.
Summary and conclusions
Although there are many unresolved issues, a reasonable as-
sumption is that EDS, similar to drowsiness, is not only a state
of reduced wakefulness but also of reduced awareness. This
tentative conclusion derives from diverse and incomplete lines
of evidence, and future research may yet contradict this idea.
However, studies conducted both in healthy sleep-deprived
and hypersomnic subjects are concordant with respect to an
impact of sleepiness on frontal cortical activity. As this region
is implicated in various aspects of consciousness, one possi-
bility is that alterations in consciousness may accompany
pathological or non-pathological sleepiness. While no defini-
tive answer is available, evidence consistent with this view is
emerging. Future research is needed on several fronts, some of
which have been highlighted in this article. Novel approaches,
for example, exploring altered consciousness following natu-
ral (slow-breathing) or artificial (mechanical stimulation of the
olfactory epithelium) manipulations of cortical activity and
connectivity can supplement traditional paradigms. These
Sleep Breath
may have important advantages including avoidance of the
confounding impact of stress that is inevitably associated with
sleep deprivation and sleep disorders. Methodological diver-
sification may also aid conceptual development in this field.
There is growing appreciation that core psychological pro-
cesses are modulated by changes in somatic physiology.
Cortical processing and integration of these interoceptive sig-
nals is believed to be fundamental to higher level aspects of
consciousness including self-awareness [106]. Respiratory
feedback is of particular interest given that, unlike many other
vital somatic functions (e.g., digestion), it can be brought un-
der conscious control. Recent evidence shows that respiration
can alter the balance between long-range vs local connectivity
by modulating theta and delta oscillations, respectively [107].
Such effects not only invite comparison with the well-
described changes in brain connectivity associated with al-
tered states of wakefulness but lend further support to the
hypothesis that EDS represents an intermediate state of con-
sciousness (see Fig. 1).
Compliance with ethical standards
Conflict of interest The authors declare that they have no conflict of
interest.
Ethical approval This article does not contain any studies with human
participants performed by any of the authors.
References
1. Dauvilliers Y, Bassetti CL (2017) Idiopathic hypersomnia. In:
Kryger MH, Roth T, Dement WC (eds) Principles and practice
of pediatric sleep medicine, 6th edn. Elsevier, Philadelphia, pp
883891
2. Ohayon MM, Dauvilliers Y, Reynolds CF (2012) Operationaldef-
initions and algorithms for excessive sleepiness in the general
population: implications for DSM-5 nosology. Arch Gen
Psychiatry 69:7179. https://doi.org/10.1001/archgenpsychiatry.
2011.1240
3. Blachier M, Dauvilliers Y, Jaussent I, Helmer C, Ritchie K,
Jouven X, Tzourio C, Amouyel P, Besset A, Ducimetiere P,
Empana JP (2012) Excessive daytime sleepiness and vascular
events: the three city study. Ann Neurol 71:661667. https://doi.
org/10.1002/ana.22656
4. Jaussent I, Bouyer J, Ancelin ML, Berr C, Foubert-Samier A,
Ritchie K, Ohayon MM, Besset A, Dauvilliers Y (2012)
Excessive sleepiness is predictive of cognitive decline in the el-
derly. Sleep 35:12011207. https://doi.org/10.5665/sleep.2070
5. Jaussent I, EmpanaJP, Ancelin ML, Besset A, Helmer C, Tzourio
C, Ritchie K, Bouyer J, Davilliers Y (2013) Insomnia, daytime
sleepiness and cardio-cerebrovascular diseases in the elderly: a 6-
year prospective study. PLoS One 8:e56048. https://doi.org/10.
1371/journal.pone.0056048
6. Ohayon MM (2008) From wakefulness to excessive sleepiness:
what we know and still need to know. Sleep Med Rev 12:129
141. https://doi.org/10.1016/j.smrv.2008.01.001
7. Ohayon MM (2012) Determining the level of sleepiness in the
American population and its correlates. J Psychiatr Res 46:422
427. https://doi.org/10.1016/j.jpsychires.2011.06.008
8. Strohl KP, Brown DB, Collop N, George C, Grunstein R, Han F,
Kline L, Malhotra A, Pack A, Phillips B, Rodenstein D, Schwab
R, Weaver T, Wilson K (2013) ATS ad hoc committee on sleep
apnea, sleepiness, and driving risk in noncommercial drivers. An
official American Thoracic Society clinical practice guideline:
sleep apnea, sleepiness, and driving risk in noncommercial
drivers. An update of a 1994 statement. Am J Respir Crit Care
Med 187:12591266. https://doi.org/10.1164/rccm.201304-
0726ST
9. Partinen M (2011) Epidemiology of sleep disorders. In: Montagna
P, Chokroverty S (eds) Handbook of clinical neurology, 98 (3rd
series) Sleep Disorders, Part, vol 1. Elsevier, Philadelphia, pp
275314
10. Shen J, Barbera J, Shapiro CM (2006) Distinguishing sleepiness
and fatigue: focus on definition and measurement. Sleep Med Rev
10(1):6376. https://doi.org/10.1016/j.smrv.2005.05.004
11. Vgontzas AN, Chrousos GP (2002) Sleep, the hypothalamic-
pituitary-adrenal axis, and cytokines: multiple interactions and
disturbances in sleep disorders. Endocrinol Metab Clin N Am
31:1536
12. Carskadon MA, Dement WC, Mitler MM, Roth T, Westbrook PR,
Keenan S (1986) Guidelines for the multiple sleep latency test
(MSLT): a standard measure of sleepiness. Sleep 9:519524
13. Johns MW (1991) A new method for measuring daytime sleepi-
ness: the Epworth sleepiness scale. Sleep 14:540545
14. Hoddes E, Zarcone V, Smythe H, Phillips R, Dement WC (1973)
Quantification of sleepiness: a new approach. Psychophysiology
10:431436
15. Åkerstedt T, Gillberg M (1990) Subjective and objective sleepi-
ness in the active individual. Int J Neurosci 52:2937
16. Bixler EO, Vgontzas AN, Lin HM, Calhoun SL, Vela-Bueno A,
Kales A (2005) Excessive daytime sleepiness in a general popu-
lation sample: the role of sleep apnea, age, obesity, diabetes, and
depression. J Clin Endocrin Metab 90:45104515. https://doi.org/
10.1210/jc.2005-0035
17. Ohayon MM, Priest RG, Zulley J, Smirne S, Paiva T (2002)
Prevalence of narcolepsy symptomatology and diagnosis in the
European general population. Neurology 58:18261833
18. Ford ES, Cunningham TJ, Giles WH, Croft JB (2015) Trends in
insomnia andexcessive daytime sleepiness among US adults from
2002 to 2012. Sleep Med 16:372378. https://doi.org/10.1016/j.
sleep.2014.12.008
19. Jaussent I, Morin CM, Ivers H, Dauvilliers Y (2017) Incidence,
worsening and risk factors of daytime sleepiness in a population-
based 5-year longitudinal study. Sci Rep 7:1372. https://doi.org/
10.1038/s41598-017-01547-0
20. Pallesen S, Nordhus IH, Omvik S, Sivertsen B, Tell GS, Bjorvatn
B (2007) Prevalence and risk factors of subjective sleepiness in the
general adult population. Sleep 30:619624
Fig. 1 Schematic representation of the hypothetical functional
connectivity in EDS (b), compared to wakefulness (a) and NREM sleep
(c): in this model, the EDS pattern shares features of both wakefulness
and sleep but displays augmented segregation. Such a model suggests an
intermediate state of consciousness is present in EDS
Sleep Breath
21. Wu S, Wang R, Ma X, Zhao Y, Yan X, He J (2012) Excessive
daytime sleepiness assessed by the Epworth sleepiness scale and
its association with health related quality of life: a population-
based study in China. BMC Public Health 12:849. https://doi.
org/10.1186/1471-2458-12-849
22. Fernandez-Mendoza J, Calhoun SL (2015) Excessive daytime
sleepiness: age, sleep, mood, and metabolic modulation. In
Watson RR (Ed.) Modulation of sleep by obesity, diabetes, age,
and diet. Academic Press pp 193-202
23. American Academy of Sleep Medicine (2014) International clas-
sification of sleep disordersthird edition (ICSD-3). American
Academy of Sleep Medicine, Darien, IL
24. Miglis MG, Guilleminault C (2014) Kleine-Levin syndrome: a
review. Nat Sci Sleep 6:1926. https://doi.org/10.2147/NSS.
S44750
25. Mignot E, Lin L, Finn L, Lopes C, Pluff K, Sundstrom ML, Young
T (2006) Correlates of sleep-onset REM periods during the mul-
tiple sleeplatency test in community adults. Brain 129:16091623
26. Ohayon MM, Reynolds CF III, Dauvilliers Y (2013) Excessive
sleep duration and quality of life. Ann Neurol 73:785794. https://
doi.org/10.1002/ana.23818
27. Singh M, Drake CL, Roth T (2006) The prevalence of multiple
sleep-onset REM periods in a population-based sample. Sleep 29:
890895
28. Roth B (1981) Idiopathic hypersomnia: a study of 187 personally
observed cases. Int J Neurol 15:108118
29. Vernet C, Arnulf I (2009) Idiopathic hypersomnia with and with-
out long sleep time: a controlled series of 75 patients. Sleep 32:
753759
30. Vernet C, Leu-Semenescu S, Buzare MA, Arnulf I (2010)
Subjective symptoms in idiopathic hypersomnia: beyond exces-
sive sleepiness. J Sleep Res 19:525534. https://doi.org/10.1111/j.
1365-2869.2010.00824.x
31. Vgontzas AN, Bixler EO, Kales A, Criley C, Vela-Bueno A
(2000) Differences in nocturnal and daytime sleep between pri-
mary and psychiatric hypersomnia: diagnostic and treatment im-
plications. Psychosom Med 62:220226
32. Pizza F, Ferri R, Poli F, Vandi S, Cosentino FI, Plazzi G (2013)
Polysomnographic study of nocturnal sleep in idiopathic
hypersomnia without long sleep time. J Sleep Res 22:185196.
https://doi.org/10.1111/j.1365-2869.2012.01061.x
33. Hara J, Beuckmann CT, Nambu T, Willie JT, Chemelli RM,
Sinton CM, Sugiyama F, Yagami K, Goto K, Yanagisawa M,
Sakurai T (2001) Genetic ablation of orexin neurons in mice re-
sults in narcolepsy, hypophagia, and obesity. Neuron 30:345354
34. Liblau RS, Vassalli A, Seifinejad A, Tafti M (2015) Hypocretin
(orexin) biology and the pathophysiology of narcolepsy with cat-
aplexy. Lancet Neurol 14:318328. https://doi.org/10.1016/
S1474-4422(14)70218-2
35. Dauvilliers Y, Baumann CR, Carlander B, Bischof M, Blatter T,
Lecendreux M, Maly F, Besset A, Touchon J, Billiard M, Tafti M,
Bassetti CL (2003) CSF hypocretin-1 levels in narcolepsy, Kleine-
Levin syndrome, and other hypersomnias and neurological condi-
tions. J Neurol Neurosurg Psychiatry 74:16671673
36. Kanbayashi T, Inoue Y, Chiba S, Aizawa R, Saito Y, Tsukamoto
H, Fujii Y, Nishino S, Shimizu T (2002) CSF hypocretin-1
(orexin-A) concentrations in narcolepsy with and without cata-
plexy and idiopathic hypersomnia. J Sleep Res 11:9193
37. Mignot E, Lammers GJ, Ripley B, Okun M, Nevsimalova S,
Overeem S, Vankova J, Black J, Harsh J, Bassetti C, Schrader
H, Nishino S (2002) The role of cerebrospinal fluid hypocretin
measurement in the diagnosis of narcolepsy and other
hypersomnias. Arch Neurol 59:15531562
38. Baumann CR, Bassetti CL (2005) Hypocretins (orexins) and
sleepwake disorders. Lancet Neurol 4:673682. https://doi.org/
10.1016/S1474-4422(05)70196-4
39. Kok SW, Overeem S, Visscher TL, Lammers GJ, Seidell JC, Pijl
H, Meinders AE (2003) Hypocretin deficiency in narcoleptic
humans is associated with abdominal obesity. Obes Res 11:
11471154
40. Nishino S, Sakurai E, Nevsimalova S, Yoshida Y, Watanabe T,
Yanai K, Mignot E (2009) Decreased CSF histamine in narcolepsy
with and without low CSF hypocretin-1 in comparison to healthy
controls. Sleep 32:175180
41. Brown RE, Basheer R, McKenna JT, Strecker RE, McCarley RW
(2012) Control of sleep and wakefulness. Physiol Rev 92:1087
1187. https://doi.org/10.1152/physrev.00032.2011
42. Cirelli C, Tononi G (2008) Is sleep essential? PLoS Biol 6:e216.
https://doi.org/10.1371/journal.pbio.0060216
43. Montagna P, Gambetti P, Cortelli P, Lugaresi E (2003) Familial
and sporadic fatal insomnia. Lancet Neurol 2:167176
44. Rechtschaffen A, GillilandMA, Bergmann BM, Winter JB (1983)
Physiological correlates of prolonged sleep deprivation in rats.
Science 221:182184
45. Steriade M (2006) Grouping of brain rhythms in corticothalamic
systems. Neuroscience 137:10871106
46. Menicucci D, Piarulli A, Allegrini P, Laurino M, Mastorci F,
Sebastiani L, Bedini R, Gemignani A (2013) Fragments of
wake-like activity frame down-states of sleep slow oscillations
in humans: new vistas for studying homeostatic processes during
sleep. Int J Psychophysiol 89:151157. https://doi.org/10.1016/j.
ijpsycho.2013.01.014
47. Crunelli V, Hughes SW (2010) The slow (< 1 Hz) rhythm of non-
REM sleep: a dialogue between three cardinal oscillators. Nat
Neurosci 13:917. https://doi.org/10.1038/nn.2445
48. Siegel J (2004) Brain mechanisms that control sleep and waking.
Naturwissenschaften 91:355365
49. Siegel JM (2005) Clues to the functions of mammalian sleep.
Nature 437:12641271
50. Siegel JM (2009) Sleep viewed as a state of adaptive inactivity.
Nat Rev Neurosci 10:747753. https://doi.org/10.1038/nrn2697
51. Maquet P (1995) Sleep function(s) and cerebral metabolism.
Behav Brain Res 69:7583
52. Maquet P (2000) Functional neuroimaging ofnormal human sleep
by positron emission tomography. J Sleep Res 9:207232
53. Mackiewicz M, Shockley KR, Romer MA, Galante RJ,
Zimmerman JE, Naidoo N, Baldwin DA, Jensen ST, Churchill
GA, Pack AI (2008) Macromolecule biosynthesis - a key function
of sleep. Physiol Genomics 31:441457
54. Reimund E (1994) The free radical flux theory of sleep. Med
Hypotheses 43:231233
55. Xie L, Kang H, Xu Q, Chen MJ, Liao Y, Thiyagarajan M,
ODonnell J, Christensen DJ, Nicholson C, Illiff JJ, Takano T,
Deane R, Nedergaard M (2013) Sleep drives metabolite clearance
from the adult brain. Science 342:373377. https://doi.org/10.
1126/science.1241224
56. Ramm P, Smith CT (1990) Rates of cerebral protein synthesis are
linked to slow wave sleep in the rat. Physiol Behav 48:749753
57. Eiland MM, Ramanathan L, Gulyani S, Gilliland M, Bergmann
BM, Rechtschaffen A, Siegel JM (2002) Increases in amino-
cupric-silver staining of the supraoptic nucleus after sleep depri-
vation. Brain Res 945:18
58. Ramanathan L, Gulyani S, Nienhuis R, Siegel JM (2002) Sleep
deprivation decreases superoxide dismutase activity in rat hippo-
campus and brainstem. Neuroreport 13:13871390
59. Shain W, Forman DS, Madelian V, Turner JN (1987) Morphology
of astroglial cells is controlled by beta-adrenergic receptors. J Cell
Biol 105:23072314
60. Blutstein T, Haydon PG (2013) The importance of astrocyte-
derived purines in the modulation of sleep. Glia 61:129139
Sleep Breath
61. ODonnell J, Ding F, Nedergaard M (2015) Distinct functional
states of astrocytes during sleep and wakefulness: is norepineph-
rine the master regulator? Curr Sleep Med Rep 1:18
62. Dudai Y (2004) The neurobiology of consolidations, or, how sta-
ble is the engram? Ann Rev Psychol 55:5186
63. McGaugh JL (2000) Memorya century of consolidation. Science
287:248251
64. Bosch M, Castro J, Saneyoshi T, Matsuno H, Sur M, Hayashi Y
(2014) Structural and molecular remodeling of dendritic spine
substructures during long-term potentiation. Neuron 82:444459
65. Dudai Y, Karni A, Born J (2015) The consolidation and transfor-
mation of memory. Neuron 88:2032
66. Rasch B, Born J (2013) About sleeps role in memory. Physiolol
Rev 93:681766
67. ONeill J, Pleydell-Bouverie B, Dupret D, Csicsvari J (2010) Play
it again: reactivation of waking experience and memory. Trends
Neurosci 33:220229
68. Tamminen J, Payne JD, Stickgold R, Wamsley EJ, Gaskell MG
(2010) Sleep spindle activity is associated with the integration of
new memories and existing knowledge. J Neurosci 30:14356
14360
69. Wagner U, Gais S, Haider H, Verleger R, Born J (2004) Sleep
inspires insight. Nature 427:352355
70. Marshall L, Helgadóttir H, Mölle M, Born J (2006) Boosting slow
oscillations during sleeppotentiates memory. Nature 444:610613
71. Diekelmann S, Born J (2010) The memory function of sleep. Nat
Rev Neurosci 11:114126
72. Sforza E, Gaudreau H, Petit D, Montplaisir J (2000) Homeostatic
sleep regulation in patients with idiopathic hypersomnia. Clin
Neurophysiol 111:277282
73. Reid LM, MacLullich AM (2006) Subjective memory complaints
and cognitive impairment in older people. Dement Geriatr Cogn
Disord 22:471485
74. Wearden AJ, Appleby L (1996) Research on cognitive complaints
and cognitive functioning in patients with chronic fatigue syn-
drome (CFS): what conclusions can we draw? J Psychosom Res
41:197211
75. Thomann J, Baumann CR, Landolt HP, Werth E (2014)
Psychomotor vigilance task demonstrates impaired vigilance in
disorders with excessive daytime sleepiness. J Clin Sleep Med
10:10191024
76. Van Schie MK, Thijs RD, Fronczek R, Middelkoop HA, Lammers
GJ, Van Dijk JG (2012) Sustained attention to response task
(SART) shows impaired vigilance in a spectrum of disorders of
excessive daytime sleepiness. J Sleep Res 21:390395
77. Naumann A, Bellebaum C, Daum I (2006) Cognitive deficits in
narcolepsy. J Sleep Res 15:329338
78. Killgore WD (2010) Effects of sleep deprivation on cognition. In
Progress in brain research (Vol. 185). Elsevier, pp. 105-129
79. Killgore WD, Schwab ZJ, Weiner MR (2012) Self-reported noc-
turnal sleep duration is associated with next-day resting state func-
tional connectivity. Neuroreport 23:741745
80. Killgore WD, Schwab ZJ, Kipman M, DelDonno SR, Weber M
(2012) Voxel-based morphometric gray matter correlates of day-
time sleepiness. Neurosci Lett 518:1013
81. Goel N, Rao H, Durmer JS, Dinges DF (2009) Neurocognitive
consequences of sleep deprivation. In seminars in neurology (Vol.
29, No. 04). Thieme Medical Publishers, pp. 320-339
82. Boucetta S, Montplaisir J, Zadra A, Lachapelle F, Soucy JP,
Gravel P, Dang-Vu TT (2017) Altered regional cerebral blood
flow in idiopathic hypersomnia. Sleep 40(10):zsx140
83. Dang-Vu TT, Desseilles M, Laureys S, Degueldre C, Perrin F,
Phillips C, Maquet P, Peigneux P (2005) Cerebral correlates of
delta waves during non-REM sleep revisited. Neuroimage 28:
1421
84. Laureys S (2005) The neural correlate of (un) awareness: lessons
from the vegetative state. Trends Cogn Sci 9:556559
85. Fuller P, Sherman D, Pedersen NP, Saper CB, Lu J (2011)
Reassessment of the structural basis of the ascending arousal sys-
tem. J Comp Neurol 519:933956
86. Saper CB, Lowell BB (2014) The hypothalamus. Curr Biol 24:
R1111R1116
87. Panksepp J, Northoff G (2009) The trans-species core SELF: the
emergence of active cultural and neuro-ecological agents through
self-related processing within subcortical-cortical midline net-
works. Conscious Cogn 18:193215
88. Gemignani A, Menicucci D, Laurino M, Piarulli A, Mastorci F,
Sebastiani L, Allegrini P (2015) Linking sleep slow oscillations
with consciousness theories: new vistas on slow wave sleep un-
consciousness. Arch Ital Biol 153:135143
89. Massimini M, Ferrarelli F, Huber R, Esser SK, Singh H, Tononi G
(2005) Breakdown of cortical effective connectivity during sleep.
Science 309:22282232
90. Gujar N, Yoo SS, Hu P, Walker MP (2010) The unrested resting
brain: sleep deprivation alters activity within the default-mode
network. J Cogn Neurosci 22:16371648
91. Sämann PG, Tully C, Spoormaker VI, Wetter TC, Holsboer F,
Wehrle R, Czisch M (2010) Increased sleep pressure reduces rest-
ing state functional connectivity. MAGMA 23:375389
92. Verweij IM, Romeijn N, Smit DJ, Piantoni G, Van Someren EJ,
van der Werf YD (2014) Sleep deprivation leads to a loss of
functional connectivity in frontal brain regions. BMC Neurosci
15:88
93. Euston DR, Gruber AJ, McNaughton BL (2012) The role of me-
dial prefrontal cortex inmemory and decision making. Neuron76:
10571070
94. Etkin A, Egner T, Kalisch R (2011) Emotional processing in an-
terior cingulate and medial prefrontal cortex. Trends Cogn Sci 15:
8593
95. Gusnard DA, Akbudak E, Shulman GL, Raichle ME (2001)
Medial prefrontal cortex and self-referential mental activity: rela-
tion to a default mode of brain function. Proc Natl Acad Sci 98:
42594264
96. Muzur A, Pace-Schott EF, Hobson JA (2002) The prefrontal cor-
tex in sleep. Trends Cogn Sci 6:475481
97. Hobson JA (2009) REM sleep and dreaming: towards a theory of
protoconsciousness. Nat Rev Neurosci 10:803813
98. Nishida M, Pearsall J, Buckner RL, Walker MP (2008) REM
sleep, prefrontal theta, and the consolidation of human emotional
memory. Cereb Cortex 19:11581166
99. Fattinger S, Kurth S, Ringli M, Jenni OG, Huber R (2017) Theta
waves in childrens waking electroencephalogram resemble local
aspects of sleep during wakefulness. Sci Rep 7:11187
100. Strijkstra AM, Beersma DG, Drayer B, Halbesma N, Daan S
(2003) Subjective sleepiness correlates negatively with global al-
pha (812 Hz) and positively with central frontal theta (48Hz)
frequencies in the human resting awake electroencephalogram.
Neurosci Lett 340:1720
101. Vyazovskiy VV, Olcese U, Hanlon EC, Nir Y, Cirelli C, Tononi G
(2011) Local sleep in awake rats. Nature 472:443447
102. Bernardi G, Siclari F, Yu X, Zennig C, Bellesi M, Ricciardi E. ... &
Tononi, G (2015) Neural and behavioral correlates of extended
training during sleep deprivation in humans: evidence for local,
task-specific effects. J Neurosci 35: 44874500
103. Dauvilliers Y, Evangelista E, De Verbizier D, Barateau L,
Peigneux P (2017) [18F] fludeoxyglucose-positron emission to-
mography evidence for cerebral hypermetabolism in the awake
state in narcolepsy and idiopathic hypersomnia. Frontiers Neurol
8:350
104. Piarulli A, Zaccaro A, Laurino M, Menicucci D, De Vito A,
Bruschini L, Berrettini S, Bergamasco M, Laureys S, Gemignani
Sleep Breath
A (2018) Ultra-slow mechanical stimulation of olfactory epitheli-
um modulates consciousness by slowing cerebral rhythms in
humans. Sci Rep 8:6581
105. Zaccaro A, Piarulli A, Laurino M, Garbella E, Menicucci D, Neri
B, Gemignani A (2018) How breath-control can change your life:
a systematic review on psycho-physiological correlates of slow
breathing. Front Hum Neurosci 12
106. Blanke O (2012) Multisensory brain mechanisms of bodily self-
consciousness. Nat Rev Neurosci 13(8):556571
107. Tort AB, Brankačk J, Draguhn A (2018) Respiration-entrained
brain rhythms are global but often overlooked. Trends Neurosci
41(4):186197
Comments
Excellent synthesis of the network neuroscience that is relevant to this
challenging and poorly characterized disease. The authors do a nice job
citing what evidence is available while constructing a hypothesis
framework for discussion about underlying etiology.
Kent Werner
MD, USA
PublishersnoteSpringer Nature remains neutral with regard to
jurisdictional claims in published maps and institutional affiliations.
Sleep Breath
... The aversive effects of excessive sleepiness on various aspects of health include disability, morbidity, and mortality. Beyond its health consequences, excessive sleepiness is a major determinant of road traffic accidents and implicated in poor academic and workplace performance [1]. Therefore, the ability to evaluate sleepiness has obvious implications for medicine and safety-critical occupations and procedures [2]. ...
... Since objective assessment of sleepiness, such as measurements of sleep propensity with the multiple sleep latency test (MSLT), requires attendance at a sleep laboratory, this methodology is impracticable in this respect. Consequently, standardized questionnaires represent a suitable compromise, with the 8-item Epworth sleepiness scale (ESS) [3] being the most popular [1]. ...
... Application of a computerized analysis to recordings of the human electroencephalographic (EEG) signal provides a possibility to associate certain quantitative changes in spectral composition of the EEG with changes in the underlying processes of sleep regulation [11,12]. The classic example is the conceptualization of the brain activity in delta range of the EEG spectrum (1)(2)(3)(4) as an objective marker of the homeostatic process of sleep regulation. It was suggested that the power density in this frequency range of the EEG spectrum can serve as a marker of the strength of the drive for sleep [13]. ...
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PurposeSince disagreement has been found between an objective sleep propensity measured by sleep onset latency (SOL) and subjective sleepiness assessment measured by the Epworth sleepiness scale (ESS) score, distinct underlying causes and consequences were suggested for these two sleepiness measures. We addressed the issue of validation of the ESS against objective sleepiness and sleep indexes by examining the hypothesis that these two sleepiness measures are disconnected due to their differential relationship with the antagonistic drives for sleep and wake.Methods The polysomnographic records of 50-min napping attempts were collected from 27 university students on three occasions. Scores on the first and second principal components of the electroencephalographic (EEG) spectrum were calculated to measure the sleep and wake drives, respectively. Self-assessments of subjective sleepiness and sleep were additionally collected in online survey of 633 students at the same university.ResultsAn ESS score was disconnected with the polysomnographic and self-assessed SOL in the nap study and online survey, respectively. An ESS score but not SOL was significantly linked to the spectral EEG measure of the sleep drive, while SOL but not ESS showed a significant association with the spectral EEG measure of the opposing wake drive.Conclusions Each of two sleepiness measures was validated against objective indicators of the opposing sleep-wake regulating processes, but different underlying causes were identified for two distinct aspects of sleepiness. A stronger sleep drive and a weaker opposing drive for wake seem to contribute to a higher ESS score and to a shorter SOL, respectively.
... Unlike in numerous other conceptions, we do not consider sleep as a state of consciousness (Hitchcott et al., 2019;Hobson and Pace-Schott, 2002;Maquet, 2001;Strickgold, 1998). ...
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The neurophysiological basis of consciousness is still unknown and one of the most challenging questions in the field of neuroscience and related disciplines. We propose that consciousness is essentially characterized by the maintenance of mental representations of internal and external stimuli beyond their perception for the execution of cognitive operations. Thus, consciousness cannot exist without working memory and it is likely that consciousness and working memory share the same neural substrates. Here, we present a novel psychological and neurophysiological framework that explains the role of consciousness for cognition, adaptive behavior, and everyday life. In this model, a novel architecture of consciousness is presented that is organized as a system of operation and storage units called “platforms” that are controlled by a consciousness center, termed central executive/online platform. Platforms maintain mental representations or contents, are entrusted with different executive functions, and operate at different levels of consciousness. We further differentiate between the “high-end” conscious central executive/online- and mental time travel platforms, the semiconscious steady-state- and the pre-conscious stand-by platforms. All mental representations or contents are represented by neural circuits and their support cells (astrocytes, oligodendrocytes etc.). Mental representations and contents become conscious when neural circuits reverberate, that is fire sequentially and continuously with relative synchronicity. Reverberatory activity in neural circuits is initiated and maintained by pacemaker cells/neural circuit pulsars, enhanced electrotonic coupling via gap junctions and unapposed hemichannel opening. The central executive/online platform controls which mental representations or contents should become conscious by recruiting pacemaker cells/neural network pulsars, the opening of hemichannels and promoting enhanced neural circuit coupling via gap junctions. With respect to cognitive evolution it is likely that the inter-individual and cross-species level of consciousness depends on the capacity of the central executive to preset pacemaker cells/neural network pulsars, and to control gap junction coupling and uncoupling of neural circuits and their support cells.
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Sleep deficiency is associated with disabling daytime symptoms, including excessive daytime sleepiness (EDS) and fatigue. The purpose of this article is to discuss the contributions of sleep deficiency and sleep disorders to fatigue and EDS among people with chronic conditions. We use exemplars from the literature on chronic heart failure, inflammatory bowel disease, and breast cancer to (1) describe the prevalence of fatigue and EDS and their consequences; (2) examine the evidence for the contributions of sleep deficiency and sleep disorders to these symptoms; and (3) recommend implications for future research and practice.
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The neurophysiological basis of consciousness is still unknown and one of the most challenging questions in the field of neuroscience and related disciplines. We propose that consciousness is characterized by the maintenance of mental representations of internal and external stimuli for the execution of cognitive operations. Consciousness cannot exist without working memory, and it is likely that consciousness and working memory share the same neural substrates. Here, we present a novel psychological and neurophysiological framework that explains the role of consciousness for cognition, adaptive behavior, and everyday life. A hypothetical architecture of consciousness is presented that is organized as a system of operation and storage units named platforms that are controlled by a consciousness center (central executive/online platform). Platforms maintain mental representations or contents, are entrusted with different executive functions, and operate at different levels of consciousness. The model includes conscious-mode central executive/online and mental time travel platforms and semiconscious steady-state and preconscious standby platforms. Mental representations or contents are represented by neural circuits and their support cells (astrocytes, oligodendrocytes, etc.) and become conscious when neural circuits reverberate, that is, fire sequentially and continuously with relative synchronicity. Reverberatory activity in neural circuits may be initiated and maintained by pacemaker cells/neural circuit pulsars, enhanced electronic coupling via gap junctions, and unapposed hemichannel opening. The central executive/online platform controls which mental representations or contents should become conscious by recruiting pacemaker cells/neural network pulsars, the opening of hemichannels, and promoting enhanced neural circuit coupling via gap junctions.
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Background: The psycho-physiological changes in brain-body interaction observed in most of meditative and relaxing practices rely on voluntary slowing down of breath frequency. However, the identification of mechanisms linking breath control to its psychophysiological effects is still under debate. This systematic review is aimed at unveiling psychophysiological mechanisms underlying slow breathing techniques (<10 breaths/minute) and their effects on healthy subjects. Methods: A systematic search of MEDLINE and SCOPUS databases, using keywords related to both breathing techniques and to their psychophysiological outcomes, focusing on cardio-respiratory and central nervous system, has been conducted. From a pool of 2,461 abstracts only 15 articles met eligibility criteria and were included in the review. The present systematic review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Results: The main effects of slow breathing techniques cover autonomic and central nervous systems activities as well as the psychological status. Slow breathing techniques promote autonomic changes increasing Heart Rate Variability and Respiratory Sinus Arrhythmia paralleled by Central Nervous System (CNS) activity modifications. EEG studies show an increase in alpha and a decrease in theta power. Anatomically, the only available fMRI study highlights increased activity in cortical (e.g., prefrontal, motor, and parietal cortices) and subcortical (e.g., pons, thalamus, sub-parabrachial nucleus, periaqueductal gray, and hypothalamus) structures. Psychological/behavioral outputs related to the abovementioned changes are increased comfort, relaxation, pleasantness, vigor and alertness, and reduced symptoms of arousal, anxiety, depression, anger, and confusion. Conclusions: Slow breathing techniques act enhancing autonomic, cerebral and psychological flexibility in a scenario of mutual interactions: we found evidence of links between parasympathetic activity (increased HRV and LF power), CNS activities (increased EEG alpha power and decreased EEG theta power) related to emotional control and psychological well-being in healthy subjects. Our hypothesis considers two different mechanisms for explaining psychophysiological changes induced by voluntary control of slow breathing: one is related to a voluntary regulation of internal bodily states (enteroception), the other is associated to the role of mechanoceptors within the nasal vault in translating slow breathing in a modulation of olfactory bulb activity, which in turn tunes the activity of the entire cortical mantle.
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