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Sleep and Synaptic Homeostasis

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Abstract

This paper discusses the synaptic homeostasis hypothesis of sleep. The main claim of the hypothesis is that plastic processes occurring during wakefulness result in a net increase in synaptic strength in many brain circuits, and that role of sleep is to downscale synaptic strength to a baseline level that is energetically sustainable, makes efficient use of gray matter space, and is beneficial for learning and memory. Thus, sleep is the price we have to pay for plasticity, and its goal is the homeostatic regulation of the total synaptic weight impinging on neurons. In this chapter we review evidence pro and contra the hypothesis, discuss similarities and differences with other hypotheses that focus on the role of sleep in neural plasticity, and mention ongoing and future experiments to test it directly.

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... sleepiness (high sleep pressure) and sleep ciclicity. It also acts on micro-levels, represented by sleep microstructure including the dynamics of sleep slow waves (SWs) within the framework of the cyclic alternating pattern (CAP) [5][6][7] -NREM sleep-oscillations range from high-frequency Hz) hippocampal and cortical ripples (high frequency oscillations; HFO) through thalamo-cortical sleep spindles (12)(13)(14)(15) and cortical (< 1Hz) SWs. SWs are constituted by active "up" states associating with spindles and ripples and disfacilitated "down" states [8]. ...
... According to the synaptic homeostatic hypothesis, SW power increases during the day reaching its peak at the beginning of the "descending"-i.e. deepening-slope of the first sleep-cycle of the night [6,7]. SWA parallels use-dependent sleep homeostasis [23]. ...
... Also this function is marked by slow wave activity. The synaptic homeostasis hypothesis [6,7] suggests an upgrading of synaptic strength (also termed upscaling) during the day and its downgrading (or downscaling) with deep nREM sleep. An opposite terminology (but apparently the same tendency) is proposed by Timofeev et al. [27], supposing the downgrading (also termed downscaling; weakening) of synapses during the day, and the restoration of synaptic strength (upgrading) during NREM sleep. ...
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Purpose To review the mutual links of sleep and epilepsy. Recent Findings It is supported in several ways that epilepsy is ‘born’ in sleep and evolves as its ‘wilding’. At least twelve to thirty percent of seizures occur during non-rapid eyemovement (NREM) sleep and interictal epileptiform activity accumulates during NREM sleep, paralleling homeostatic power and sleep pressure. The imbalance of sleep-related synaptic plasticity carries the risk of over-excitation and epileptic derailment. This is seen in major epilepsies, where normal NREM sleep patterns are shown to transform to epileptic discharges. Epilepsies then ‘strike back’ to sleep impairing its structure and functions. The harm of seizures is obvious; and interictal discharges even in seizure free patients may bring insidious and permanent loss of cognitive functions. Conclusion Sleep reveals the real face of epilepsy. Understanding the fine mechanisms of NREM sleep may lead to more effective epilepsy therapies and help reducing the harm of interictal activity as well.
... The first description of REM sleep in 1953, which revealed the presence of brain waves very similar to those of an awake brain in sleeping mammals (Aserinsky and Kleitman, 1953), justified the need to study the neurophysiological aspect of sleep. Therefore, the variations in the brain waves, the neural circuits and the hormonal secretions specific to sleep have been described (Helfrich-Förster, 2018;Hendricks et al., 2000;Kaiser and Steiner-Kaiser, 1983;Siegel, 2008;Tobler and Stalder, 1988;Tononi and Cirelli, 2003). The following studies in phylogeny and genetics have shed light on the evolution of sleep across the animal kingdom and the expression of genes which are linked to this state. ...
... The following studies in phylogeny and genetics have shed light on the evolution of sleep across the animal kingdom and the expression of genes which are linked to this state. They also revealed many homologous genes in very distant taxa (Anafi et al., 2019;Aulsebrook et al., 2016;Helfrich-Förster, 2018;Keene and Duboue, 2018;Lesku et al., 2009;Siegel, 2009;Tononi and Cirelli, 2003). Finally, an all too often forgotten aspect of sleep is its ecological aspect, which yet raises many questions: why this state which impedes the exploration of the environment and decreases vigilance (which should have a strong negative impact on fitness, especially by increasing the risk of predation) is still present in so many different species? ...
... The electrodes must then be replaced by probes measuring local electric potentials (Kaiser and Steiner-Kaiser, 1983;Keene and Duboue, 2018), which reduces the accuracy of the results. Nevertheless, it was possible to detect a common point in the brain activity of many studied species, which is the production of low-frequency high-voltage waves during sleep periods (Anafi et al., 2019;Keene and Duboue, 2018;Lesku et al., 2009;Siegel, 2008;Siegel, 2009;Tononi and Cirelli, 2003). In mammals and birds, this activity is associated with deep sleep (Siegel, 2008). ...
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Although sleep is essential for the survival of all animals, this behaviour is far from being studied in all species, especially in invertebrates. In this dissertation, we attempted to bring together current knowledge about sleep with a focus on arthropods, which have been much less studied in this regard than vertebrates. While some species appear to exhibit rest periods that combine all the characteristics of sleep, the existence of this state in most arthropods remains ambiguous, if not unknown. Even among insects, the arthropods most commonly seen in papers about sleep, the number of species studied is extremely low, compared to the sheer number of species that belong to the phylum of arthropods. This results in a very strong bias towards vertebrates, and especially mammals, whose sleep has been thoroughly studied in many different species, while this class includes very few species of the animal kingdom, in proportion. This taxonomic bias is explained by historical lack of interest in the sleep of arthropods, which however tends to be reduced, given that the current context of global changes encourages biologists to study the impact of anthropogenically-driven sleep disturbances in insects on the balance of ecosystems.
... It has been proposed that sleep renormalizes excitability and eliminates synapses [termed "down-scaling" or "pruning" (5,(7)(8)(9)]. Thus, sleep may restore the optimal neurobiological milieu for learning and strengthen memory representations (2,10). That such mechanisms take place in the human brain remains largely speculative. ...
... To date, the majority of the evidence for sleep-dependent cellular and network homeostasis suggests that slow oscillations (SOs; <1.25 Hz) during NREM (nonrapid eye movement) sleep may mediate the regulation of neural excitability (2,10). Considerably less evidence exists regarding a similar role for REM sleep, with limited data in rodents suggesting that theta activity (4 to 10 Hz) may offer similar functional benefits (8,13). ...
... At the population level, the cardinal oscillations of NREM sleep actively coordinate the hippocampal-neocortical dialogue to enable information reactivation, transfer, and consolidation (1,43). NREM sleep oscillations, including sharp-wave ripples, which are typically nested in SOs or spindles (44)(45)(46), have been suggested to mediate neuroplasticity through repetitive replay of firing sequences (43,47) and the memory-specific up-regulation of synapse formation (48); thus, reflecting a potential state of increased net excitation, in addition to co-occurring benefits of synaptic downscaling (2,10). ...
Article
The proposed mechanisms of sleep-dependent memory consolidation involve the overnight regulation of neural activity at both synaptic and whole-network levels. Now, there is a lack of in vivo data in humans elucidating if, and how, sleep and its varied stages balance neural activity, and if such recalibration benefits memory. We combined electrophysiology with in vivo two-photon calcium imaging in rodents as well as intracranial and scalp electroencephalography (EEG) in humans to reveal a key role for non-oscillatory brain activity during rapid eye movement (REM) sleep to mediate sleep-dependent recalibration of neural population dynamics. The extent of this REM sleep recalibration predicted the success of overnight memory consolidation, expressly the modulation of hippocampal-neocortical activity, favoring remembering rather than forgetting. The findings describe a non-oscillatory mechanism how human REM sleep modulates neural population activity to enhance long-term memory.
... The validity of the mathematical formulation of the model was extensively studied and independently confirmed by a large body of data, and a variety of markers were introduced to quantify both processes [36,[39][40][41][42]. Amongst these, low frequency electroencephalographic (EEG) oscillations, known as slow wave activity (SWA), emerged as the most powerful indices of sleep pressure. Indeed, SWA (contributing to Slow Wave Sleep, SWS) dominates in the first part of the night and decays through consecutive sleep cycles, and its magnitude increases after extended wakefulness [43], sleep deprivation [40], and demanding presleep activity such as physically demanding activities, learning or novel experience [44][45][46]. SWA in the beginning of the night reflects the restorative properties of sleep that provide a period for the organism to recover from the "burden of wakefulness" preceding sleep, that is, it allows to repair and to replenish the body's biological resources that were depleted during wakefulness [47]. ...
... In addition, SWS plays an important role in the consolidation of previously encoded information (i.e., memory consolidation; see [56] for an extensive review). The two most influential models of sleep-related memory consolidation are the synaptic downscaling or synaptic homeostasis hypothesis (SHY) [44] and the memory reactivation theory [56,57]. The SHY postulates that sleep facilitates learning by locally renormalizing synaptic weights saturated by prolonged wakefulness experience inducing synaptic plasticity. ...
... The SHY postulates that sleep facilitates learning by locally renormalizing synaptic weights saturated by prolonged wakefulness experience inducing synaptic plasticity. Elimination of weak synaptic links and strengthening of stronger and functionally relevant (learning-related) synaptic connections increases the signal to noise ratio and optimizes information processing [44]. ...
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Dreams are often viewed as fascinating but relatively irrelevant mental epihenomena of the sleeping mind with questionable or no functional relevance. Despite long hours of oneiric activity, and high individual differences in dream recall, dream amnesia is one of the most robust and universal features of dreaming. In this review, we conceptualize dreaming and dream amnesia as inherent aspects of the homeostatic functions of sleep and wakefulness. In this framework the temporal progression of sleep throughout the night is shaped by reactive and predictive homeostatic functions. Mental activity during sleep conforms to the dynamic interplay of restorative processes and future anticipation, and particularly during the second half of the night, unfolds as a special form of non-constrained, self-referent, and future-oriented cognitive process. Awakening facilitates constrained, goal-directed prospection that competes for shared neural resources with dream production and dream recall, and hence, contributes to dream amnesia. We present the neurophysiological aspects of reactive and predictive homeostasis during sleep, highlighting the putative role of nocturnal cortisol as well as the cortisol awakening response in predictive homeostasis and dream amnesia, respectively. The theoretical and methodological aspect of our proposal is discussed in relation to the study of dream recall, sleep-related cognitive processes and altered dreaming in sleep disorders.
... The morphology of slow waves provides information about nocturnal regeneration and cortical maturation [14,23,24] and slow wave sleep is suggested to be involved in nocturnal memory consolidation [13]. Decreased strength of cortical synapses during sleep due to pruning processes is represented by the declining slope of slow waves, and linked to neuronal recovery and learning capacity [25]. ...
... Studies have shown an alteration of slow wave activity and CAP in association with epilepsy, and a corresponding impairment of sleep quality [13,24,25,29]. ...
... As a disorder of cortical network organisation [68] epilepsy affects brain structures involved in sleep plastic functions, such as the cortico-thalamic and hippocampal systems [69]. Seizures or high intensity of epileptiform discharges occurring early in life do so during a critical period of activity-dependent synaptogenesis (blooming) and its regulation by elimination of extra synapses (pruning), a sign of plasticity [25,70]. Early alterations of sleep could have a lasting impact on the maturation of neural networks, resulting in functional disorders [3,71]. ...
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Aim Epilepsy occurs in approximately 80 per 100,000 infants in the first year of life, ranging in severity from self-limited and likely to spontaneously resolve, to severe developmental and epileptic encephalopathies. Sleep plays a key role in early brain development and the reciprocal relationship between sleep and seizures is not yet fully understood, particularly in young children. We conducted a Scoping Review to synthesise current knowledge of sleep architecture in neonates and infants with epilepsy. Method Peer-reviewed publications from 2005 to 2022 describing sleep architecture in infants up to six months of age with unprovoked seizures were included. The analysis set was derived from EMBASE, Web of Science and PubMED using key terms “sleep, epilepsy and infant” and related descriptors. Inclusion criteria were prospectively described in a Scoping Review protocol. Sleep architecture was assessed as macro- and micro-structural elements. Results 21 publications were included in the qualitative analysis. In self-limited familial and genetic epilepsy, sleep macrostructure was generally preserved. In DEEs and in epileptic encephalopathies of genetic or structural aetiology, sleep architecture was significantly disrupted. Interpretation Early identification of infants with epilepsy is important to ensure early and effective treatment. In the DEE spectrum, sleep architecture is significantly impacted, and abnormal sleep architecture may be associated with compromised developmental outcome. Further research is needed to identify the sequence of events in abnormal brain development, epilepsy and sleep disruption and potentially help to predict the course of epilepsy towards a self-limited epilepsy versus a DEE.
... Furthermore, the detrimental effects of sleep deprivation on memory encoding could be related to synaptic saturation produced during long periods of wakefulness (16). The synaptic homeostasis hypothesis (SHY) (17,18) posits that Non-rapid eye movement (NREM) sleep, specifically slow wave activity (0.5-4 Hz, SWA), favors a global downscaling of synapses that were potentiated during preceding wakefulness, thus facilitating the encoding of information after a period of sleep. In line with the SHY hypothesis, Antonenko et al. (2013) (19) demonstrated that applying transcranial slow oscillation stimulation (tSOS) oscillating at 0.75 Hz, to induce SWA in healthy humans during an 80-min afternoon nap, enhanced SWA and improved memory encoding of declarative materials compared to sham. ...
... It is important to highlight that despite the beneficial effects of sleep on memory encoding being largely attributed to NREM sleep (17,18) related to the enhancement of memory encoding, the potential benefits of naps shorter than 80 minutes in improving learning remain largely unexplored due to the attribution of learning improvement after napping to the effects of NREM sleep. Specifically regarding the role of lighter sleep stages, several studies suggest that light sleep, including both S1 and S2, is related to memory processing (25,26,27,28). ...
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The application of neuroscience findings in educational settings offers promising opportunities to enhance academic performance. Adolescents, particularly affected by delayed sleep patterns due to early school start times, often experience sleep deprivation, impacting memory processes crucial for learning. The synaptic homeostasis hypothesis (SHY) posits that non-rapid eye movement (NREM) sleep, particularly slow wave activity (0.5-4 Hz), downscales synapses potentiated during wakefulness, thereby facilitating post-sleep encoding. In this study, we evaluate the impact of a short nap on memory encoding of a biology lesson in a classroom setting. High school students were randomly assigned to either a Nap group allowed a short nap or a Control group engaging in calm activities. Following the nap or calm activities, all students received a biology lesson, followed by an immediate test. We found that students in the Nap group showed better memory encoding performance than those in the Control group. However, contrary to our hypothesis, this improvement was not explained by NREM sleep. In fact, longer periods of NREM sleep were negatively correlated with performance, potentially attributed to sleep inertia effects. Thus, while short naps proved useful for boosting academic performance, careful attention should be paid to the time interval between sleep and learning to avoid sleep inertia, particularly when applied in natural settings.
... Memory downscaling is widely used in ANNs, and can be roughly divided into weight 502 decay [57,58] and pruning [59,60]. Although we consider them to be plausible 503 implementations subscribing to the Synaptic Homeostasis hypothesis [61,62] as 504 in [63,64], they are largely simplified from the biological reality, and other 505 implementations also exist [65]. Notably it is often unnecessary for ANNs to undergo 506 sleep periods, and downscaling such as weight decay is typically integrated into their 507 training protocols [66], which is believed to bring in the same benefits as if performing 508 downscaling in a dedicated sleep period [63]. ...
... We dismissed spontaneous replay for the RBM, as it yielded ill-behaved replay samples 668 according to our early-stage experiments. reducing metabolic costs and signal saturation [61][62][63]65]. It also improves 673 generalisation of ANNs [72], including RBMs [66], by moderating overfitting, and has 674 become widely used with various implementations in machine learning [57,58]. ...
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Replay facilitates memory consolidation in both biological and artificial systems. Using the complementary learning systems (CLS) framework, we study replay in both humans and birds through computational modelling. We investigate impacts of replay triggered by targeted memory reactivation during sleep and experiments examining how sleep affects the development of birdsong in young songbirds. We show that qualitatively realistic sleep effects can be captured by highly abstracted, idealised CLS models. Our modelling sheds theoretical insights on the mechanisms underlying both strengthening and weakening effects of targeted memory reactivation, and supports the empirical hypothesis that replay drives overnight performance deterioration and correlates positively with the final performance in birdsong development. Author summary Taking a computational approach, we investigated the roles of memory replay in two complementary learning systems (CLS) models capturing realistic sleep effects observed in two real-life experiments on targeted memory reactivation (TMR) and birdsong development respectively. Our two CLS models are abstract and identical in architecture, and they are distinct in terms of where replay is generated. While the TMR model produces replay samples using its hippocampus, the birdsong model does so using the sensorimotor cortex. We found that certain TMR effects could characterise different TMR models, which might account for individual differences in human subjects. The results of the birdsong model support the idea that the dramatic overnight oscillations in performance accuracy which are observed during birdsong development are mainly driven by memory replay, and that long-term performance gain can be achieved despite short-term performance deterioration during the early nights of development. As we studied the two experiments using the unified CLS framework, we discuss how replay contributes to sleep-dependent performance changes from the perspective of systems consolidation.
... A ideia de que um relógio central circadiano controla as variações rítmicas em todo o corpo foi ampliada com a descoberta de múltiplos relógios atuando em diferentes níveis como componentes de uma rede circadiana. De acordo com a hipótese da homeostase sináptica, durante a vigília ocorre o fortalecimento das conexões sinápticas, enquanto durante o sono essas conexões são enfraquecidas, resultando na reorganização das conexões sinápticas no cérebro (TONONI;CIRELLI, 2003). As estruturas cerebrais e redes neuronais, como o hipotálamo, tronco cerebral e córtex cerebral, estão envolvidas na regulação do sono (CIRELLI, 2009;OHAYON, 2002). ...
... A ideia de que um relógio central circadiano controla as variações rítmicas em todo o corpo foi ampliada com a descoberta de múltiplos relógios atuando em diferentes níveis como componentes de uma rede circadiana. De acordo com a hipótese da homeostase sináptica, durante a vigília ocorre o fortalecimento das conexões sinápticas, enquanto durante o sono essas conexões são enfraquecidas, resultando na reorganização das conexões sinápticas no cérebro (TONONI;CIRELLI, 2003). As estruturas cerebrais e redes neuronais, como o hipotálamo, tronco cerebral e córtex cerebral, estão envolvidas na regulação do sono (CIRELLI, 2009;OHAYON, 2002). ...
... Electrophysiological measures, such as increased slope and amplitude of evoked cortical responses, and the frequency of miniature excitatory postsynaptic currents, have also been observed with wakefulness 4,13,40 . Collectively this evidence supports the first aspect of the synaptic homeostasis hypothesis of sleep (SHY) 16 , which proposes that during wakefulness, the intake and encoding of information leads to synaptic potentiation. Our findings suggest that the wakeassociated depolarizing shift in EGABAA forms part of a mechanism that facilitates the induction of synaptic potentiation with wakefulness. ...
... Our findings suggest that the wakeassociated depolarizing shift in EGABAA forms part of a mechanism that facilitates the induction of synaptic potentiation with wakefulness. The SHY also proposes that synaptic potentiation during wakefulness is linked to the homeostatic regulation of slow-wave activity (SWA) during non-rapid eye movement (NREM) sleep 16 . In our previous study, we demonstrated that wake-related depolarizing shifts in EGABAA occur locally within cortex, are activity-dependent, and regulate the level of local SWA 18 . ...
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Neural plasticity varies depending on the time of day and preceding sleep-wake history. It is unclear however, how diurnal changes in cellular physiology modulate a neuron's propensity to exhibit synaptic plasticity. Recently it has been shown that cortical pyramidal neurons exhibit diurnal changes in their transmembrane chloride gradients, which shift the equilibrium potential for GABAA receptors (EGABAA). Here we demonstrate that diurnal EGABAA affects membrane potential dynamics and glutamatergic long-term potentiation (LTP) elicited by high-frequency spiking activity in pyramidal neurons of mouse cortex. More depolarized EGABAA values associated with the active period facilitate LTP induction by promoting residual depolarization during synaptically-evoked spiking. Diurnal differences in LTP can be reversed by switching the EGABAA-dependent effects on membrane potential dynamics, either by direct current injection or pharmacologically altering EGABAA. These findings identify EGABAA as a metaplastic regulator of glutamatergic synaptic potentiation, which has implications for understanding synaptic plasticity during waking and sleep.
... Le modèle de l'homéostasie synaptique (ou théorie du recalibrage synaptique ; figure 2B), proposé par Tononi et Cirelli [23], apporte une explication neurophysiologique globale à l'impact du sommeil lent sur la mémoire, et ce quel que soit le système de mémoire mis en jeu. Ainsi, les caractéristiques neurophysiologiques de l'éveil permettent le déclenchement de mécanismes de potentialisation à long terme (long-term potentiation [LTP]) permettant de fixer dans nos réseaux cérébraux de nouvelles informations. ...
... P : poids synaptique. Adapté de[30] et[23]. ...
... Two major hypotheses have emerged linking the memory functions of sleep to cortical excitability and plasticity. The synaptic homeostasis hypothesis (Tononi and Cirelli, 2003) states that sleep renormalizes the net increase in synaptic strength that accrues during wakefulness. In this framework, learning during waking experience leads to a cumulative potentiation of synapses. ...
... In this framework, learning during waking experience leads to a cumulative potentiation of synapses. To avoid excessive potentiation and maintain homeostatic equilibrium, sleep resets the excitability of neurons by facilitating a net downscaling of synapses (Tononi and Cirelli, 2003). The two-stage theory postulates that sleep consolidates memory through hippocampo-cortical transmission (Frankland and Bontempi, 2005). ...
... Sleep is a universal process of vital significance. Sleep ensures: -Regeneration of body, brain, and psyche -Brain growth and development, in particular in the first years of life -Synaptic strength, efficiency, and plasticity, meaning an elimination of unnecessary synapses through the process of pruning to ensure efficacious brain functioning and plasticity -Consolidation and integration of memory and learning -Emotion regulation weight, growth, risk-taking, pleasureseeking -Strengthening of the immune system -Cleaning of neurotoxins and cellular debris Therefore, sleep can be considered a particularly active process [18][19][20][21][22]. ...
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Epilepsy, as one of the most prevalent neurological diseases in childhood, has a strong reciprocal relationship with sleep. Sleep-associated epilepsy syndromes in childhood are mostly genetic and can be divided into (a) the group of self-limited focal epilepsies of childhood including self-limited epilepsy with autonomic seizures (SeLEAS) and self-limited epilepsy with centrotemporal spikes (SeLECTS) and (b) (non-self-limited) sleep-related hypermotor epilepsy (SHE). Sleep-accentuated (developmental and) epileptic encephalopathies (DEE/EE-SWAS, Landau–Kleffner syndrome [LKS]) are either genetic (possible transition from SeLEAS or SeLECTS) or structural, and they are characterized by continuous bilateral focal or generalized epileptic activity throughout the night with a clinical manifestation of stagnation or regression, in particular of cognition (verbal agnosia in LKS). Epilepsy syndromes with increased seizure frequency after sleep deprivation or with seizures in the transition to awakening include juvenile generalized epilepsy syndromes such as epilepsy with generalized tonic-clonic seizures alone (GTCA) or juvenile myoclonic epilepsy (JME), but also SeLECTS. Sleep is a very active process: Regeneration, reorganization, and consolidation of memory facilitate development and cognitive functioning. Epilepsy can alter sleep architecture and vice versa, which can appear as a vicious circle in epilepsies that are sleep related. Macrostructural elements of sleep such as sleep efficiency, sleep onset latency, wakefulness after sleep onset, REM and non-REM sleep fraction, as well as microstructural sleep elements such as slow-wave activity, slope of slow waves, cyclic alternating pattern (CAP), and physiological sleep figures, are important biomarkers with which to understand clinical symptoms such as cognitive stagnation and regression, to monitor treatment, but also to determine prognostic factors and will be an important tool for future studies.
... Putatively, neurons exhaust some reserve during wake that must be replenished during sleep. Synapses seem to undergo systematic changes with time spent awake [32,38,39]. Regardless of the fundamental mechanisms of sleep homeostasis, seizures could theoretically result from build-up in sleep pressure, in which case they should mostly occur after prolonged wakefulness, possibly independently of a circadian phase or the momentary brain state. ...
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For centuries, epileptic seizures have been noticed to recur with temporal regularity, suggesting that an underlying biological rhythm may play a crucial role in their timing. In this review, we propose to adopt the framework of chronobiology to study the circadian timing of seizures. We first review observations made on seizure timing in patients with epilepsy and animal models of the disorder. We then present the existing chronobiology paradigm to disentangle intertwined circadian and sleep–wake timing mechanisms. In the light of this framework, we review the existing evidence for specific timing mechanisms in specific epilepsy syndromes and highlight that current knowledge is far from sufficient. We propose that individual seizure chronotypes may result from an interplay between independent timing mechanisms. We conclude with a research agenda to help solve the urgency of ticking seizures.
... The somatostatin expressing GABAergic neurons in basal forebrain were found to inhibit basal forebrain cholinergic, parvalbumine, and glutamatergic neurons via GABAergic synapses (Xu et al., 2015). In addition, many of these cells were sleep-active and sleep promoting, and might suppress all wake-promoting BF cell types during non-REM sleep.SWA was found to facilitate synaptic consolidation or produce synaptic downscaling, thereby increasing signal-to-noise ratios in relevant neural circuits (Tononi et al., 2006). There is stronger DRN than MRN input to prefrontal and entorhinal cortex, so there need to be a way to disentagle their opposite effects on cortical activity in wakefulness and SWS. ...
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Opiates are fast pain relievers that can cause respiratory arrest. I show new mechanisms how mu-opioids and high prenatal nicotine cause respiratory slowdown linked to slow wave sleep. Mu-opioids activate the medial habenula which activates the interpeduncular nucleus. The MHb-IPN system decreases respiration and alarm/arousal response to hypercapnia by projections to PAG, DRN, MRN and MRN→LPO→RMTg→vPAG. The same MHb-IPN circuit that causes respiratory slowdown, likely causes ventilatory deficits in mammalian neonates, known as sudden infant death syndrome (SIDS), linked to high fetal nicotine intake. Natural slowdown of respiration and heart rate is caused by slow wave sleep, when body is not moving. The MHb and rostromedial tegmental nucleus are known for high amount of mu-opioid receptors. Both were claimed to be activated by the MHb→IPN→MRN circuit that activates serotonin release, promotes slow SWS, rest, immune defense, recovery, sharp wave ripples, cortical spindles, replay of temporally, spatially and relationally bound memories, synaptogenesis, BDNF linked growth and DG neurogenesis, but inhibits theta states, arousal, alert wakefulness, awareness and REM sleep linked circuits (Vadovičová, 2015).This updated circuit model explains role of the MHb→IPN→MRN→hippocampus + claustrum→cortical slow wave activity (SWA) in anesthesia, memory replay, loss of awareness, SWS and in theta states suppression. I proposed new mechanisms for anesthetic ketamine effect: activation of the IPN→MRN→claustrum→cortical SWA circuit by the 5-HT2a IPN and claustrum receptors. I show why are ketamine and hallucinogens anxiolytic and antidepressant, andhow activation of 5-HT2a receptors in vACC/infralimbic cortex increases the safety, well-being signal, and cognitive flexibility.
... These substances induced both specific and shared neural activity features across the brain regions involved (Johnson et al., 2003;Kiat et al., 2018). hdEEG has also been used to investigate the generators of the spindles that characterize brain activity during non-rapid eye movement sleep, to characterize different sleep stages (Furrer et al., 2019) and to reveal the role of slow-wave activity increases in mediating awareness of the external environment (Castelnovo et al., 2018(Castelnovo et al., , 2022 and in supporting neuroplastic changes (Tononi & Cirelli, 2003). ...
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Electroencephalography (EEG) is a technique for non‐invasively measuring neuronal activity in the human brain using electrodes placed on the participant's scalp. With the advancement of digital technologies, EEG analysis has evolved over time from the qualitative analysis of amplitude and frequency modulations to a comprehensive analysis of the complex spatiotemporal characteristics of the recorded signals. EEG is now considered a powerful tool for measuring neural processes in the same time frame in which they happen (i.e. the subsecond range). However, it is commonly argued that EEG suffers from low spatial resolution, which makes it difficult to localize the generators of EEG activity accurately and reliably. Today, the availability of high‐density EEG (hdEEG) systems, combined with methods for incorporating information on head anatomy and sophisticated source‐localization algorithms, has transformed EEG into an important neuroimaging tool. hdEEG offers researchers and clinicians a rich and varied range of applications. It can be used not only for investigating neural correlates in motor and cognitive neuroscience experiments, but also for clinical diagnosis, particularly in the detection of epilepsy and the characterization of neural impairments in a wide range of neurological disorders. Notably, the integration of hdEEG systems with other physiological recordings, such as kinematic and/or electromyography data, might be especially beneficial to better understand the neuromuscular mechanisms associated with deconditioning in ageing and neuromotor disorders, by mapping the neurokinematic and neuromuscular connectivity patterns directly in the brain. image
... While many aspects of N3 sleep, such as duration, undergo homeostatic regulation, 29 there have been no reports addressing SWA or sleep pressure in healthy human volunteers recently sedated with dexmedetomidine with CLAS. One theory of the role of sleep pressure and SWA homeostasis is the synaptic homeostasis hypothesis 30 (Fig. 1a), where wakefulness leads to a potentiation of synapses that is reflected the following night by increases in sleep SWA. This sleep SWA, a measure of sleep pressure, typically dissipates during overnight sleep as homeostatic processes converge. ...
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Background The alpha-2 adrenergic agonist dexmedetomidine induces EEG patterns resembling those of non-rapid eye movement (NREM) sleep. Fulfilment of slow wave sleep (SWS) homeostatic needs would address the assumption that dexmedetomidine induces functional biomimetic sleep states. Methods In-home sleep EEG recordings were obtained from 13 healthy participants before and after dexmedetomidine sedation. Dexmedetomidine target-controlled infusions and closed-loop acoustic stimulation were implemented to induce and enhance EEG slow waves, respectively. EEG recordings during sedation and sleep were staged using modified American Academy of Sleep Medicine criteria. Slow wave activity (EEG power from 0.5 to 4 Hz) was computed for NREM stage 2 (N2) and NREM stage 3 (N3/SWS) epochs, with the aggregate partitioned into quintiles by time. The first slow wave activity quintile served as a surrogate for slow wave pressure, and the difference between the first and fifth quintiles as a measure of slow wave pressure dissipation. Results Compared with pre-sedation sleep, post-sedation sleep showed reduced N3 duration (mean difference of −17.1 min, 95% confidence interval −30.0 to −8.2, P=0.015). Dissipation of slow wave pressure was reduced (P=0.02). Changes in combined durations of N2 and N3 between pre- and post-sedation sleep correlated with total dexmedetomidine dose, (r=−0.61, P=0.03). Conclusions Daytime dexmedetomidine sedation and closed-loop acoustic stimulation targeting EEG slow waves reduced N3/SWS duration and measures of slow wave pressure dissipation on the post-sedation night in healthy young adults. Thus, the paired intervention induces sleep-like states that fulfil certain homeostatic NREM sleep needs in healthy young adults. Clinical trial registration ClinicalTrials.gov NCT04206059.
... Reactivation of neural circuits engaged during wake is part of the consolidation process during sleep, and this memory consolidation involves synaptic modification (Llinas and Steriade 2006;Born and Feld 2012). A net loss of synapses is found during sleep in the developing mouse cortex (Maret et al. 2011;Yang and Gan 2011), the zebrafish brain (Appelbaum et al. 2010), and the fly nervous system (Donlea et al. 2009;Bushey et al. 2011), indicating that sleep is also important for the downscaling of synaptic connectivity potentiated during wakefulness (Tononi and Cirelli 2003;Diering et al. 2017). Translation plays a critical role in synaptic plasticity that gives rise to memory consolidation, and proteins required for synaptic plasticity increase during the early hours of sleep (Aton et al. 2009). ...
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Individuals with neurodevelopmental disorders experience persistent sleep deficits, and there is increasing evidence that sleep dysregulation is an underlying cause, rather than merely an effect, of the synaptic and behavioral defects observed in these disorders. At the molecular level, dysregulation of the synaptic proteome is a common feature of neurodevelopmental disorders, though the mechanism connecting these molecular and behavioral phenotypes is an ongoing area of investigation. A role for eIF2α in shifting the local proteome in response to changes in the conditions at the synapse has emerged. Here, we discuss recent progress in characterizing the intersection of local synaptic translation and sleep and propose a reciprocal mechanism of dysregulation in the development of synaptic plasticity defects in neurodevelopmental disorders.
... wave activity during sleep reflects net synaptic strength, and underlying slow oscillations may contribute directly to synaptic renormalization (102). ...
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Sleep, circadian rhythms, and mental health are reciprocally interlinked. Disruption to the quality, continuity, and timing of sleep can precipitate or exacerbate psychiatric symptoms in susceptible individuals, while treatments that target sleep—circadian disturbances can alleviate psychopathology. Conversely, psychiatric symptoms can reciprocally exacerbate poor sleep and disrupt clock-controlled processes. Despite progress in elucidating underlying mechanisms, a cohesive approach that integrates the dynamic interactions between psychiatric disorder with both sleep and circadian processes is lacking. This review synthesizes recent evidence for sleep—circadian dysfunction as a transdiagnostic contributor to a range of psychiatric disorders, with an emphasis on biological mechanisms. We highlight observations from adolescent and young adults, who are at greatest risk of developing mental disorders, and for whom early detection and intervention promise the greatest benefit. In particular, we aim to a) integrate sleep and circadian factors implicated in the pathophysiology and treatment of mood, anxiety, and psychosis spectrum disorders, with a transdiagnostic perspective; b) highlight the need to reframe existing knowledge and adopt an integrated approach which recognizes the interaction between sleep and circadian factors; and c) identify important gaps and opportunities for further research.
... The somatostatin expressing GABAergic neurons in basal forebrain were found to inhibit basal forebrain cholinergic, parvalbumine, and glutamatergic neurons via GABAergic synapses (Xu et al., 2015). In addition, many of these cells were sleep-active and sleep promoting, and might suppress all wake-promoting BF cell types during non-REM sleep.SWA was found to facilitate synaptic consolidation or produce synaptic downscaling, thereby increasing signal-to-noise ratios in relevant neural circuits (Tononi et al., 2006). There is stronger DRN than MRN input to prefrontal and entorhinal cortex, so there need to be a way to disentagle their opposite effects on cortical activity in wakefulness and SWS. ...
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Mu-opioids are effective and fast pain relievers, known to inhibit pain pathways. The side effect of their medicinal use is the inhibition of respiration. Knowing the neural circuit involved can help to find how to target it, to avoid respiratory death. I show new idea how mu-opioids and high prenatal nicotine cause respiratory slowdown linked to slow wave sleep. A high dose of mu-opioids activates the medial habenula which activates the interpeduncular nucleus. The IPN causes respiratory slowdown via its output to PAG, DRN, MRN or LPO-RMTg. SWS is linked to a natural slowdown of respiration and heart rate when body is not moving. The MHb and rostromedial tegmental nucleus are known for high amount of mu-opioid receptors. Both were proposed to be activated in the neural circuit that promotes slow wave oscillations, SWS, rest, immune defense, recovery, sharp wave ripples, cortical spindles, replay of temporaly, spatialy and relationally bound memories, synaptogenesis and BDNF linked growth (Vadovičová, 2015). That work showed how the MHb→IPN→MRN circuit activates serotonin release and inhibits the theta states, arousal, alert wakefulness, consciousness and REM sleep linked circuits. Possible effectors, through which the MHb-IPN system decreases respiration and arousal response to hypercapnia are DRN, PAG, MRN and LPO. The IPN can attenuate the dorsolateral PAG alarm functions – arousal, increased respiration and fight/flight response, and modulate the ventral PAG nuclei linked to analgesia and respiratory slowdown. The same MHb-IPN circuit that causes respiratory slowdown, likely causes ventilatory deficits in mammalian neonates, known as sudden infant death syndrome (SIDS), linked to high fetal nicotine intake. My circuit model explains the role of the MHb→IPN→MRN→claustrum + hippocampus circuit in anesthesia, memory replay, cortical SWA, SWS and in theta states suppression. I propose new mechanisms for anesthetic ketamine effects: activation of the IPN→MRN→claustrum→ cortical SWA circuit by activating the 5-HT2A (or similar) receptors. I show why are ketamine and hallucinogens anxiolytic and antidepressant, and how activation of serotonin receptors in vACC/IL increases the safety/well-being signal and cognitive flexibility.
... Regular physical exercise, for example, is known to induce neurogenesis (the birth of new neurons), enhance synaptic plasticity, and improve cognitive functions, thereby bolstering neuroplasticity [36]. Similarly, adequate sleep is essential for synaptic homeostasis, which supports neuroplasticity and promotes learning and memory [37]. ...
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This chapter provides an accessible exploration of the integral role neuroplasticity—the brain’s adaptability—plays in learning, memory, and ultimately, workplace performance. Beginning with an overview of the neurobiology of learning and memory, it elucidates how these processes impact key skills and knowledge in today’s global business environment, and how individual differences affect team performance. The chapter then delves into strategies to enhance neuroplasticity and improve job performance, encompassing cognitive training, brain stimulation, and mindfulness interventions. Finally, it offers practical insights for integrating scientific findings into workplace training and development programs, with a focus on optimizing brain health and harnessing neuroplasticity to boost productivity.
... Si, dans un réseau neuronal, les poids synaptiques arrivent à saturation, il devient impossible d'encoder de nouvelles informations, c'est-àdire de former de nouveaux engrammes. L'hypothèse de l'homéostasie synaptique propose que le sommeil joue un rôle important dans la régulation des poids synaptiques [34] afin d'éviter la saturation et de permettre la formation de nouveaux souvenirs pendant la période d'éveil qui suit. Ce modèle suggère que les poids synaptiques globaux augmentent pendant l'éveil et diminuent pendant le sommeil ( Figure 5). ...
Article
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Le sommeil est crucial pour le renforcement sélectif des souvenirs et la régulation des réseaux neuronaux impliqués dans la formation de la mémoire. Ces fonctions sont sous-tendues par des motifs neuraux spécifiques associés aux différentes phases du sommeil. Dans l’hippocampe, les complexes onde aiguë-ondulation du sommeil à ondes lentes sont associés à des réactivations de l’activité neuronale de l’éveil. En se coordonnant avec les ondes lentes et les fuseaux corticaux, ces réactivations contribuent à la consolidation de la mémoire spatiale. Les ondes lentes sont également un marqueur de l’homéostasie synaptique. La physiologie du sommeil paradoxal et des ondes thêta associées reste à explorer.
... We divided the non-rapid eye movement (NREM) sleep into NREM1-3, with sleep spindles and slow waves in the cerebral cortex mainly occurring in NREM2 and NREM3, respectively 38,39 . Rapideye movement (REM) sleep is associated with dreaming 40,41 , and was characterized by theta activity occurring in the hippocampus (5-8Hz in rodents) [42][43][44] . In short, our data provides evidence that the cerebellum shows sleep-state dependent activity 45-48, . ...
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The cerebellum is important for motor performance and adaptation as well as cognition. Sleep is essential for optimizing of all these functions, but it remains to be elucidated how sleep affects cerebellar processing. It has been suggested that sleep periods with muscle twitches entrain the cerebellum with a copy of motor commands and subsequent sensory feedback signals, to develop predictive coding of movements. If this hypothesis is correct, one expects phasic correlations between the muscle twitches and specific features of the electro-encephalography (EEG) recordings in the cerebellum during various sleep stages as well as the climbing fiber activity in the cerebellar cortex, the modulation of which is relayed from the cerebral cortex via mesodiencephalic junction and inferior olive. Here we provide evidence for coherent correlations between cerebellar and cerebral cortical sleep spindles, twitches as well as patterns of climbing fiber activity. Our data are compatible with the novel concept that muscle twitches evoke complex spike synchronicity during NREM, which in turn affects cerebellar spindle activity and cerebellar-cortical information flow, thereby entraining an internal forward model.
... Slow-wave sleep (SWS), the deepest stage of non-rapid eye movement (NREM) sleep, plays a 27 crucial role in learning and memory consolidation 1,2 ...
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Increasing evidence associates slow-wave sleep (SWS) dysfunction with neurodegeneration. Using a within-subject design in the nonhuman primate model of Parkinson's disease (PD), we found that reduced SWS quantity in mild parkinsonism was accompanied by elevated beta and reduced delta power during SWS in the motor cortex. Our findings support excessive beta oscillations as a mechanism for SWS dysfunction and will inform development of neuromodulation therapies for enhancing SWS in PD.
... The copyright holder for this preprint this version posted October 17, 2023. ; reduction role of sleep and further suggests a more sparse place representation to emerge after sleep 34 . We also observed a negative correlation between firing rate changes across REM and NREM sleep, which is in line with the opposing role of these states in firing rate regulation 35 . ...
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Hippocampal reactivation of waking neuronal assemblies in sleep is a key initial step of systems consolidation. Nevertheless, it is unclear whether reactivated assemblies are static or whether they reorganize gradually over prolonged sleep. Here, we tracked reactivated CA1 assembly patterns over ~20 hours of sleep/rest periods and related them to assemblies seen before or after in a spatial learning paradigm. We found that reactivated assembly patterns were gradually transformed and started to resemble those seen in the subsequent recall session. Periods of rapid eye movement (REM) sleep and non-REM (NREM) had antagonistic roles: while NREM accelerated the assembly drift, REM countered it. Moreover, only a subset of rate-changing pyramidal cells contributed to the drift, while stable firing rate cells maintained unaltered reactivation patterns. Our data suggest that prolonged sleep promotes the spontaneous reorganization of spatial assemblies, which can contribute to daily cognitive map changes or encoding new learning situations.
... In their study, they showed how natural sleep is associated with a 60% increase in the interstitial space, resulting in a higher convective exchange of cerebrospinal fluid with interstitial fluid, while convective fluxes of interstitial fluid increased the rate of Aβ clearance during sleep. Furthermore, REM phase seems to be implicated in sleep-related synaptic consolidation processes [65][66][67], and the higher rate of apneas during sleep in OSA patients could lead to a disruption of this memory promoting processes. Higher levels of cortisol in OSA patients are indicative of hippocampal atrophy and memory impairment, associated with cognitive decline, as reported by Lupien [68]. ...
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Numerous evidence reports direct correlation between cognitive impairment, Alzheimer’s disease and sleep disorders, in particular obstructive sleep apnea. Both obstructive sleep apnea and Alzheimer’s disease are highly prevalent conditions whose incidence increases with age. Several studies demonstrate how sleep-disordered breathing may lead to poor cognition, even though the underlying mechanisms of this association remain partially unclear. According to the most recent studies, obstructive sleep apnea may be considered a modifiable risk factor for cognitive dysfunction. In the present review, the authors aim to integrate recent research examining obstructive sleep apnea and Alzheimer’s disease biomarkers, also focusing on the mechanisms that support this correlation, including but not limited to the role of hypoxia and cardiovascular risk. Moreover, the potential favourable effect of obstructive sleep apnea therapy on cognitive function is discussed, to evaluate the benefits deriving from appropriate treatment of sleep-disordered breathing on cognition.
... However, the exact nature and roles of SWS are not clearly understood and there is still much to learn about SWS generation and its physiologic functions. Tononi and Cirelli [8] examined the electrophysiologic character of SWS and demonstrated its important role in SMR synaptic strength, leading to improved memory and cognitive processing [9,10]. Still, information regarding the prevalence of SWS in different populations, especially patient populations, is incomplete and scarce [11,12]. ...
Article
Background and Objective Prior research suggests that slow wave sleep (SWS) is disrupted in people with obstructive sleep apnea (OSA). However, it was not clear whether the reduction in SWS is related to abnormal breathing or the extent of OSA as determined by the minimum oxygen saturation. Further, there is limited research on the relationship between oxygen saturation and SWS. The present study examined the relationship between SWS and minimum oxygen saturation levels in patients with OSA.Methods The sample consisted of 589 patients with OSA (mean age: 48.54 years) who completed full-night polysomnography.Results Results showed that there was a significant difference in SWS scores across three apnea-hypopnea index (AHI) groups (AHI score 5–15 for mild apnea, 16–30 for moderate apnea, and >30 for severe apnea). Lower SWS scores were observed in the severe apnea group. Additionally, results indicated that as oxygen saturation decreased, the SWS scores decreased.Conclusions Results from this study indicate that oxygen saturation significantly predicts SWS amounts. These findings suggest that interventions for low oxygen saturation could enhance the amounts of SWS. The clinical ramifications of these findings are worthy of consideration.
... Since the only difference between the groups is the exposure of rats to a stimulating environment known to induce plasticity, our results suggest that NREM Slow and Delta oscillations, also termed slow wave activity (SWA), which is a measure usually associated with sleep homeostasis, may be more sensitive to wake content rather than wake duration. Our results thus align with the proposition that a marker of sleep homeostasis (i.e., SWA) is correlated with increased brain plasticity [51]. More systematic studies testing various types of wake content and length would provide important insight into this question and clarify the driver and nature of sleep homeostasis. ...
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Brain plasticity is induced by learning during wakefulness and is consolidated during sleep. But the molecular mechanisms involved are poorly understood and their relation to experience-dependent changes in brain activity remains to be clarified. Localized mRNA translation is im-portant for the structural changes at synapses supporting brain plasticity consolidation. Sleep has been shown activate the translation mTOR pathway, via phosphorylation of 4E-BPs, during brain plasticity, but whether this activation is specific to synapses is not known. We investigated this question using acute exposure of rats to an enriched environment (EE). We measured brain activity with EEGs and 4E-BPs phosphorylation at cortical and cerebellar synapses with Western Blot. Sleep significantly increased the conversion of 4E-BPs to its hyperphosphorylated form at synapses, especially after EE exposure. EE exposure increased oscillations in the alpha band dur-ing active exploration and in the theta to beta (4-30Hz) range, as well as spindle density, during NREM sleep. Theta activity during exploration and NREM spindle frequency predicted changes in 4E-BPs hyperphosphorylation at synapses. Our results provide a link between EEG and mo-lecular markers of plasticity across wake and sleep.
... Insufficient sleep and varying sleep schedules can affect various body processes ranging from the consolidation of memory, alertness and mood, cardiovascular system, immune system, hormone, temperature, and [3][4][5][6] glucose regulation. Generally, existing literature has shown that sleep deprivation is harmful to the 7 health and general well-being of an individual. In line with the rising need to develop means of coping with the effects of sleep deprivation (such as daytime sleepiness), the college-aged population tends to consume more caffeine as presented in different products such as caffeinated drinks (e.g. ...
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Context: University students who deprive themselves of enough nocturnal sleep due to academic activities are at risk of the deleterious effects of sleep deprivation that usually follow. To reverse these effects, they tend to consume substances such as caffeine to counteract fatigue and possibly give them the feeling of alertness they need to perform their daily activities given that there is a popular concern that the academic demands of University training can cause significant stress and the need to gain insight into the effects of caffeine on students.Objective: This study set out to assess the self-reported effects of the consumption of caffeine-containing products on nocturnal sleep and daytime functioning among students of Novena University, Ogume Delta State, Nigeria.Materials and Methods: The study adopted a descriptive cross-sectional design conducted among 400 students comprising 217 males and 183 females selected through random sampling. Data were collected using a 27-item questionnaire containing four sections; socio-demographic characteristics, caffeine consumption pattern, sleeping habits, and daytime functioning. The data was analysed using SPSS version 23 and presented in descriptive and inferential statistics at P <0.05 level of significance.Results: More than one-third of the respondents (68.50%) affirmed consuming caffeine-containing products such as caffeinated drinks and beverages. Only 21.50% affirmed practicing sleep deprivation and 40.10% agreed that their consumption of caffeine-containing products increases during times of academic stress. There was a significant relationship between the hours of sleep of the respondents and their consumption of caffeine. More than half of the respondents (71.90%) affirmed experiencing daytime sleepiness while about 40% affirmed experiencing caffeine-induced daytime dysfunction.Conclusion: There was a significant relationship between the level of caffeine consumption and students’ sleep quality. Caffeine-induced sleep deprivation and caffeine-induced daytime dysfunction are widespread among undergraduate students in the study population.
... Tononi and Cirelli [11,12] have elaborated upon their popular "synaptic homeostatic hypothesis", which postulates that synaptic facilitation builds up (upregulates) throughout the day and is then downregulated during sleep. An alternative concept is that cortical synapses are depressed (downregulated) by waking activities and upregulated by sleep SO via silent (down) states [13]. ...
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Although a critical link between non-rapid eye movement (NREM) sleep and epilepsy has long been suspected, the interconnecting mechanisms have remained obscure. However, recent advances in sleep research have provided some clues. Sleep homeostatic plasticity is now recognized as an engine of the synaptic economy and a feature of the brain’s ability to adapt to changing demands. This allows epilepsy to be understood as a cost of brain plasticity. On the one hand, plasticity is a force for development, but on the other it opens the possibility of epileptic derailment. Here, we provide a summary of the phenomena that link sleep and epilepsy. The concept of “system epilepsy”, or epilepsy as a network disease, is introduced as a general approach to understanding the major epilepsy syndromes, i.e., epilepsies building upon functional brain networks. We discuss how epileptogenesis results in certain major epilepsies following the derailment of NREM sleep homeostatic plasticity. Post-traumatic epilepsy is presented as a general model for this kind of epileptogenesis.
... Sleep spindles are a hallmark of non-rapid eye movement (NREM) sleep and are crucial for facilitating memory consolidation and learning (1)(2)(3). Alterations in these spindles are emerging as sensitive biomarkers for sleep disorders and neuropsychiatric conditions, including neurodegenerative diseases of ageing. In dementia and the precursor stages of mild cognitive impairment, alterations in sleep spindle architecture are observed (4)(5)(6)(7). ...
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Sleep spindles are a hallmark of non-REM sleep and play a fundamental role in memory consolidation. Alterations in these spindles are emerging as sensitive biomarkers for neurodegenerative diseases of ageing. Understanding the clinical presentations associated with spindle alterations may help to elucidate the functional role of these distinct electroencephalographic oscillations and the pathophysiology of sleep and neurodegenerative disorders. Here, we use a data-driven approach to examine the sleep, memory and default mode network connectivity phenotypes associated with sleep spindle architecture in older adults (mean age = 66 years). Participants were recruited from a specialist clinic for early diagnosis and intervention for cognitive decline, with a proportion showing mild cognitive deficits on neuropsychological testing. In a sample of 88 people who underwent memory assessment, overnight polysomnography and resting state fMRI, a k-means cluster analysis was applied to spindle measures of interest: fast spindle density, spindle duration and spindle amplitude. This resulted in three clusters, characterised by preserved spindle architecture with higher fast spindle density and longer spindle duration (Cluster 1), and alterations in spindle architecture (Clusters 2 and 3). These clusters were further characterised by reduced memory (Clusters 2 and 3) and nocturnal hypoxemia, associated with sleep apnea (Cluster 3). Resting state fMRI analysis confirmed that default mode connectivity was related to spindle architecture, although directionality of this relationship differed across the cluster groups. Together these results confirm a diversity in spindle architecture in older adults, associated with clinically meaningful phenotypes, including memory function and sleep apnea. They suggest that resting state default mode connectivity during the awake state can be associated with sleep spindle architecture, however this is highly dependent on clinical phenotype. Establishing relationships between clinical and neuroimaging features and sleep spindle alterations, will advance our understanding of the bidirectional relationships between sleep changes and neurodegenerative diseases of ageing.
... Consequently, the effect of sleep on human memory has gained significant attention in psychology and neuroscience research over the past two decades, resulting in thousands of dedicated publications. Moreover, several theories and models have been developed to explain the beneficial effect of sleep on memory, e.g., [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23] . ...
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Understanding the complex relationship between sleep and memory is a major challenge in neuroscience. Many studies on memory consolidation in humans suggest that sleep triggers offline memory processes, resulting in less forgetting of declarative memory and performance stabilization in non-declarative memory. However, issues related to non-optimal experimental designs, task characteristics and measurements, and inappropriate data analysis practices can significantly affect the interpretation of the effect of sleep on memory. In this article, we discuss these issues and suggest constructive solutions to address them. We believe that implementing these solutions in future sleep and memory research will significantly advance this field by improving the understanding of the specific role of sleep in memory consolidation.
... Simultaneously, an increased density of synaptic nodules requires more energy because synaptic nodules occupy more space. Hence, reduced synaptic effectiveness and stress may further impair synaptic homeostasis and contribute to greater hLRRK2-induced sleep disorders 69 . In conclusion, we believe that LRRK2 plays a role in regulating synaptic vesicle SV recycling/endocytosis in the pathogenic characteristics of PD and is also a crucial molecule in the pathological features of early PD. ...
Article
This review focuses on melatonin's role in advancing Parkinson's disease (PD) pathogenesis by inhibiting synaptic dysfunction and neuroinflammation. The early pathological changes in PD, caused by SNCA/PARK1 and LRRK2/PARK8-mediated synaptic vesicle endocytosis during the early pathogenesis of PD, are briefly reviewed. The pathological changes related to synaptic plasticity and dendrites caused by synaptic dysfunction in neurotoxin 6-hydroxydopamine (6-OHDA) and 1-methl-4-phenyl-1,2,3,6-tetrahydropyridin (MPTP)-induced PD models are also discussed. The molecular mechanisms of pathological changes in PD, caused by the activation of microglia, astrocytes, and inflammatory vesicles, are discussed. The effectiveness of melatonin (MLT) in the restoration of dopaminergic neurons in the substantia nigra (SNc) has been established. MLT can upregulate dendritic numbers and restore synaptic plasticity by inhibiting alpha-synuclein aggregation and neurotoxicity. These functions of MLT improve sleep patterns in PD patients and suppresses synaptic dysfunction by inhibiting the overactivation of the PKA/CREB/BDNF signaling pathway and reactive oxygen species (ROS) production. MLT can maintain the typical transport and release of neurotransmitters. MLT also reduces neuroinflammation by promoting microglia 2 (M2) polarization, which reduces the expression of inflammatory cytokines. Additionally, MLT stimulates the activation of the retinoic acid receptor-related orphan receptor α (RORα) ligand and inhibits the activation of the Recombinant Sirtuin 1 (SIRT1)-dependent pathway, the NLR family pyridine structure domain 3 (NLRP3) inflammasome. By integrating the latest advances in synaptic dysfunction and neuroinflammation-related PD, researchers can develop clinical interventions for treating PD and further explore the pathological hallmarks of prodromal PD.
... NREM followed by REM sleep, the roles of NREM and REM play in memory consolidation as well as the function of this cycling are not known. The putative role of sleep varies widely from active an process of memory consolidation(70) to homeostatic regulation of network activity and connectivity(71). Here we show in a simplified biophysical model, that both NREM and REM sleep may play differential and critical roles in sleep dependent memory consolidation, and that their specific function may be mediated via muscarinic pathway response to changing concentrations of ACh.The network consists of two populations of excitatory pyramidal cells: the backbone cells that form memory representations during active waking, and the less excitable (LE) excitatory cell layer from which additional neurons are recruited into memory representation during sleep. ...
Preprint
Across vertebrate species, sleep consists of repeating cycles of NREM followed by REM. However, the respective functions of NREM, REM, and their stereotypic cycling pattern are not well understood. Using a simplified biophysical network model, we show that NREM and REM sleep can play differential and critical roles in memory consolidation primarily regulated, based on state-specific changes in cholinergic signaling. Within this network, decreasing and increasing muscarinic acetylcholine (ACh) signaling during bouts of NREM and REM, respectively, differentially alters neuronal excitability and excitatory/inhibitory balance. During NREM, deactivation of inhibitory neurons leads to network-wide disinhibition and bursts of synchronized activity led by firing in engram neurons. These features strengthen connections from the original engram neurons to less-active network neurons. In contrast, during REM, an increase in network inhibition suppresses firing in all but the most-active excitatory neurons, leading to competitive strengthening/pruning of the memory trace. We tested the predictions of the model against in vivo recordings from mouse hippocampus during active sleep-dependent memory storage. Consistent with modeling results, we find that functional connectivity between CA1 neurons changes differentially at transition from NREM to REM sleep during learning. Returning to the model, we find that an iterative sequence of state-specific activations during NREM/REM cycling is essential for memory storage in the network, serving a critical role during simultaneous consolidation of multiple memories. Together these results provide a testable mechanistic hypothesis for the respective roles of NREM and REM sleep, and their universal relative timing, in memory consolidation. Significance statement Using a simplified computational model and in vivo recordings from mouse hippocampus, we show that NREM and REM sleep can play differential roles in memory consolidation. The specific neurophysiological features of the two sleep states allow for expansion of memory traces (during NREM) and prevention of overlap between different memory traces (during REM). These features are likely essential in the context of storing more than one new memory simultaneously within a brain network.
... Yet, it is conceivable that cessation also shares characteristics with deep sleep or other states that are characterized by a lack of awareness at the (neuro)physiological level, as from an evolutionary point of view, it seems unlikely that one can induce an entirely novel state that the body did not evolve to occupy in the past. These may include physiological changes that would support an ability to sustain the state for longer time periods, without, for example, being disrupted by signals of hunger or thirst, in particular a reduction in arousal, body temperature and metabolic rate, as also seen during sleep (Tononi and Cirelli, 2006). Indeed, anecdotal evidence suggests that the body of practitioners in NS is cooled down, their heart rate is lowered, and their breathing barely perceptible. ...
Article
Absence of consciousness can occur due to a concussion, anesthetization, intoxication, epileptic seizure, or other fainting/syncope episode caused by lack of blood flow to the brain. However , some meditation practitioners also report that it is possible to undergo a total absence of consciousness during meditation, lasting up to 7 days, and that these "cessations" can be consistently induced. One form of extended cessation (i.e., nirodha sam apatti) is thought to be different from sleep because practitioners are said to be completely impervious to external stimulation. That is, they cannot be 'woken up' from the cessation state as one might be from a dream. Cessations are also associated with the absence of any time experience or tiredness, and are said to involve a stiff rather than a relaxed body. Emergence from meditation-induced cessations is said to have profound effects on subsequent cognition and experience (e.g., resulting in a sudden sense of clarity, openness, and possibly insights). In this paper, we briefly outline the historical context for cessation events, present preliminary data from two labs, set a research agenda for their study, and provide an initial framework for understanding what meditation induced cessation may reveal about the mind and brain. We conclude by integrating these so-called nirodha and nirodha sam apatti experiences-as they are known in classical Buddhism-into current cognitive-neurocomputational and active inference frameworks of meditation. Progress in Brain Research, ISSN 0079-6123, https://doi.
... Algunas moléculas se han estudiado como biomarcadores en respuesta a la restricción del sueño en etapa crónica en roedores y humanos como el ácido oxálico y el diacilglicerol (Tononi & Cirelli, 2003). Respecto a los biomarcadores relacionados a los paneles de biomarcadores de reducciones de sueño agudo relacionados al metabolismo lipídico, ubiquitinación, y regulación de mitosis/ meiosis, unión a la actina, señalización de la insulina, diferenciación cardio miogénica y diferenciación celular como (ABCA1, ...
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Sleep is vital for all mammals including humans, its distortion implies different health risks and pathologies such as depression, and cardiovascular diseases, and in the end, it can lead to death. In this sense, it is important to find the molecular bases of sleep, among them the genes and their proteins that play a key role in the homeostasis of the living being. Information was collected using the PubMed/Scopus databases in English with a 10-year history using the PICO methodology to determine the words P=Genes, I=Molecular basis, C=Not applicable, O=Sleep. Original articles were determined into two large groups, among these are the “Clock Genes” and other “Genes and Proteins” related to sleep. Among the important clock genes identified are those linked to dopamine (DRD 2) and (DAT 1) and other genes such as pdm3 that participate in the genesis of the innervation of the dopaminergic system and the ANXA3 and 17GAM genes which has shown that overexpression of these is related to sleep deprivation. Understanding the molecular bases of sleep and its gaps still to be studied are key to future studies such as identifying targets and drugs to treat sleep disorders.
... Depending on area of most spike wave activity variable degrees of impact on learning, cognition, behaviour and motor functions manifest. This highlights the crucial role of slow wave sleep in the neuroplasticity that govern normal neuropsychological development 8 . Positron Emission Tomography studies using 18 F-fluorodeoxyglucose has demonstrated hypermetabolism in the region of focal continued spike wave activity, in children having normal MRI. ...
... One of the strengths of the active inference approach is that model accuracy and complexity are jointly optimized under the free-energy minimization scheme. In this specific case, the reduction of complexity would be carried out during REM sleep by pruning redundant synaptic connections, a proposal largely in line with the synaptic homeostasis hypothesis of sleep Cirelli, 2006, Tononi andCirelli, 2014]. Hobson and Friston (2012) additionally proposed that dreams would be a manifestation of priorsdriven inferential processes where top-down predictions continue to be emitted but sensory predictions errors and motor behavior (except for rapid-eyes movements or during sleep related disorders) are suppressed by a circadian shift from aminergic to cholinergic neuromodulation inhibiting sensory and motor neurons [Hobson and Friston, 2012]. ...
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The idea of meditation as a scientific tool to understand the “embodied mind” was initially suggested by neuroscientist Francisco Varela and his collaborators in a ground-breaking publication in 1991. Thirty years later, a growing amount of scientific evidence confirms that meditation can have beneficial impacts on the body and mind. Despite encouraging physiological and psychological models, a general understanding of the mechanisms at play during meditative practices, grounded in neurosciences, is still lacking. Additionally, the comprehension of human cognition based on the predictive processing theory, and its cerebral implementation, could offer a unifying explanation for processes as diverse as perception, attention, learning, and action. Founded on Bayesian statistics, this theory models the brain as an “inference organ” which simultaneously predicts and constrains, proactively, the sensations the organism receives from both its own body and the outer world, with the main purpose of maintaining itself in a viable state. The primary objective of this PhD was to elucidate, within this theoretical framework, some of the neuronal and computational mechanisms of different meditative practices. Our general hypothesis is that the regulation of attention and emotions by meditation is associated with an adjustment of the brain's predictive processes. The degrees of confidence in the validity of predictions and sensations, among other factors, would be differently altered, leading to more malleable and adaptive cognitive priors. This transformation of the way of approaching mental experience as well as external influences, may explain the proven psychotherapeutic effects of mindfulness meditation to cope with depressive relapse, anxiety, chronic pain or addictions. Keywords: meditation, mindfulness, meditation retreat, embodied cognition, predictive processing, predictive coding, Bayesian inference, perceptual inference, active inference, electroencephalography, event-related potentials, mismatch negativity, Bayesian modeling, computational modeling, pain, pain catastrophization, cognitive defusion
... Apart from grouping spindles and ripples in their up-states, one striking feature of the SO-locked analysis was the active inhibition of FRs (below baseline levels) during down-states ( Figure 3B). This effect (also referred to as OFF-periods) is well documented across species (Cash et al., 2009;Nir et al., 2011;Steriade et al., 1993;Vyazovskiy and Harris, 2013) and points to a dynamic alternation between active consolidation processes during up-states and homeostatic recalibration and/or pruning of irrelevant circuits during down-states (Tononi and Cirelli, 2006;Vyazovskiy et al., 2009). ...
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Learning and plasticity rely on fine-tuned regulation of neuronal circuits during offline periods. An unresolved puzzle is how the sleeping brain - in the absence of external stimulation or conscious effort - controls neuronal firing rates (FRs) and communication within and across circuits, supporting synaptic and systems consolidation. Using intracranial Electroencephalography (iEEG) combined with multiunit activity (MUA) recordings from the human hippocampus and surrounding medial temporal lobe (MTL) areas, we here show that governed by slow oscillation (SO) up-states, sleep spindles set a timeframe for ripples to occur. This sequential coupling leads to a stepwise increase in (i) neuronal FRs, (ii) short-latency cross-correlations among local neuronal assemblies and (iii) cross-regional MTL interactions. Triggered by SOs and spindles, ripples thus establish optimal conditions for spike-timing dependent plasticity and systems consolidation. These results unveil how the coordinated coupling of specific sleep rhythms orchestrates neuronal processing and communication during human sleep.
... Collectively, these data demonstrate that sleep functions, particularly with regard to synaptic plasticity and cognition, cannot be assumed to be uniform across brain circuits. Hypotheses such as the synaptic homeostasis hypothesis of sleep function [31,44] (which proposes that synapses throughout the brain are "downscaled" to offset net potentiation in brain circuits during wake) have been useful for generating specific experimental tests. However, accumulating evidence has made clear that sleep and sleep loss do not drive uniform changes across neuron types, or brain circuits [2,45]. ...
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Post-learning sleep plays an important role in hippocampal memory processing, including contextual fear memory (CFM) consolidation. Here, we used targeted recombination in activated populations (TRAP) to label context-encoding engram neurons in the hippocampal dentate gyrus (DG) and assessed reactivation of these neurons during post-learning sleep. We find that post-learning sleep deprivation (SD), which impairs CFM consolidation, selectively disrupts reactivation in inferior blade DG engram neurons. This change was linked to more general suppression of neuronal activity markers in the inferior, but not superior, DG blade by SD. To further characterize how learning and subsequent sleep or SD affect these (and other) hippocampal subregions, we used subregion-specific spatial profiling of transcripts and proteins. We found that transcriptomic responses to sleep loss differed greatly between hippocampal regions CA1, CA3, and DG inferior blade, superior blade, and hilus. Critically, learning-driven transcriptomic changes, measured 6 h following contextual fear learning, were limited to the two DG blades, differed dramatically between the blades, and were absent from all other regions. Similarly, protein abundance in these hippocampal subregions were differentially impacted by sleep vs. SD and by prior learning, with the majority of alterations to protein expression restricted to DG. Together, these data suggest that the DG plays an essential role in the consolidation of hippocampal memories, and that the effects of sleep and sleep loss on the hippocampus are highly subregion-specific, even within the DG itself.
... These cycles must be maintained for healthy body function in awake state [28]. Developing tools that can detect the changes in dynamic sleep stages over EEG signal are highly essential for studying patients with sleep disorders [29]. Here we use our γ-divergence to detect changes in the dynamics of the EEG to detect the transition from one state to another. ...
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Divergences or similarity measures between probability distributions have become a very useful tool for studying different aspects of statistical objects such as time series, networks and images. Notably not every divergence provides identical results when applied to the same problem. Therefore it is convenient to have the widest possible set of divergences to be applied to the problems under study. Besides this choice an essential step in the analysis of every statistical object is the mapping of each one of their representing values into an alphabet of symbols conveniently chosen. In this work we attack both problems, that is, the choice of a family of divergences and the way to do the map into a symbolic sequence. For advancing in the first task we work with the family of divergences known as the Burbea-Rao centroids (BRC) and for the second one we proceed by mapping the original object into a symbolic sequence through the use of ordinal patterns. Finally we apply our proposals to analyse simulated and real time series and to real textured images. The main conclusion of our work is that the best BRC, at least in the studied cases, is the Jensen Shannon divergence, besides the fact that it verifies some interesting formal properties.
... Homeostatic plasticity of Up-states Up-states have been proposed to have multiple functional roles, including memory consolidation and synaptic homeostasis (Tononi and Cirelli, 2003;Sirota and Buzsáki, 2005;Marshall et al., 2006;Vyazovskiy et al., 2008;Diekelmann and Born, 2010). Consistent with previous studies, our results suggest that Upstates also play a role in the homeostatic regulation of neural activity (Goel and Buonomano, 2013;Motanis and Buonomano, 2015). ...
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Cortical computations emerge from the dynamics of neurons embedded in complex cortical circuits. Within these circuits neuronal ensembles, which represent subnetworks with shared functional connectivity, emerge in an experience-dependent manner. Here we induced ensembles in ex vivo cortical circuits from mice of either sex by differentially activating subpopulations through chronic optogenetic stimulation. We observed a decrease in voltage correlation, and importantly a synaptic decoupling between the stimulated and non-stimulated populations. We also observed a decrease in firing rate during Up-states in the stimulated population. These ensemble-specific changes were accompanied by decreases in intrinsic excitability in the stimulated population, and a decrease in connectivity between stimulated and non-stimulated pyramidal neurons. By incorporating the empirically observed changes in intrinsic excitability and connectivity into a spiking neural network model, we were able to demonstrate that changes in both intrinsic excitability and connectivity accounted for the decreased firing rate, but only changes in connectivity accounted for the observed decorrelation. Our findings help ascertain the mechanisms underlying the ability of chronic patterned stimulation to create ensembles within cortical circuits. And, importantly, show that while Up-states are a global network-wide phenomenon, functionally distinct ensembles can preserve their identity during Up-states through differential firing rates and correlations.SIGNIFICANCE STATEMENT:The connectivity and activity patterns of local cortical circuits are shaped by experience. This experience-dependent reorganization of cortical circuits is driven by complex interactions between different local learning rules, external input, and reciprocal feedback between many distinct brain areas. Here we used an ex vivo approach to demonstrate how simple forms of chronic external stimulation can shape local cortical circuits in terms of their correlated activity and functional connectivity. The absence of feedback between different brain areas and full control of external input allowed for a tractable system to study the underlying mechanisms and development of a computational model. Results show that differential stimulation of subpopulations of neurons significantly reshapes cortical circuits and forms subnetworks referred to as neuronal ensembles.
... Collectively, these data demonstrate that sleep functions, particularly with regard to synaptic plasticity and cognition, cannot be assumed to be uniform across brain circuits. Hypotheses such as the synaptic homeostasis hypothesis of sleep function [31,44] (which proposes that synapses throughout the brain are "downscaled" to offset net potentiation in brain circuits during wake) have been useful for generating specific experimental tests. However, accumulating evidence has made clear that sleep and sleep loss do not drive uniform changes across neuron types, or brain circuits [2,45]. ...
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Post-learning sleep plays an important role in hippocampal memory processing, including contextual fear memory (CFM) consolidation. Here, we used targeted recombination in activated populations (TRAP) to label context-encoding engram neurons in the hippocampal dentate gyrus (DG) and assessed reactivation of these neurons during post-learning sleep. We find that post-learning sleep deprivation (SD), which impairs CFM consolidation, selectively disrupts reactivation in inferior blade DG engram neurons. This change was linked to more general suppression of neuronal activity markers in the inferior, but not superior, DG blade by SD. To further characterize how learning and subsequent sleep or SD affect these (and other) hippocampal subregions, we used subregion-specific spatial profiling of transcripts and proteins. We found that transcriptomic responses to sleep loss differed greatly between hippocampal regions CA1, CA3, and DG inferior blade, superior blade, and hilus. Critically, learning-driven transcriptomic changes, measured 6 h following contextual fear learning, were limited to the two DG blades, differed dramatically between the blades, and were absent from all other regions. Similarly, protein abundance in these hippocampal subregions were differentially impacted by sleep vs. SD and by prior learning, with the majority of alterations to protein expression restricted to DG. Together, these data suggest that the DG plays an essential role in the consolidation of hippocampal memories, and that the effects of sleep and sleep loss on the hippocampus are highly subregion-specific, even within the DG itself. Introduction:
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Background Sleep disorders are closely related to disease, especially the impact on cancer has received increasing attention. This study aimed to investigate whether sleep traits have a causal relationship with colorectal cancer (CRC) through a Two-sample Mendelian randomization study (MR). Methods In this study, we selected genetic instrumental variables (IVs) for seven sleep traits (sleep duration, get up in the morning, chronotype, nap during day, insomnia, snoring, and daytime dozing) from pooled data of published genome-wide association studies (GWAS). Two-sample MR and multivariate MR analysis study were first conducted to assess the causal association between sleep traits and CRC. The reverse MR analysis was evaluated to the causal relationship between CRC and sleep traits. Inverse variance weighting (IVW), MR Egger, and weighted median were applied to perform the primary MR Analysis. Results The multivariate MR analysis found that sleep duration (p = 0.038) and get up in the morning (p = 0.043) were protective effect on CRC, snoring (p = 0.031) were associated with the risk of CRC, get up in the morning (p = 0.003) would reduce the risk of colon cancer, chronotype (p = 0.035) were associated with the risk of colon cancer, and insomnia (p = 0.027) was the protective factor of rectal cancer. There is no evidence found that a causal association between other sleep traits and CRC, colon cancer and rectum cancer through the IVW. Conclusion This study indicated that sleep duration and get up in the morning might keep us away from CRC, especially colon cancer, and snoring is the adverse effect on CRC.
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Sleep has important clinical implications for neurorehabilitation after stroke. We aimed to systematically explore sleep (including naps) as an essential factor in the neurorehabilitation of patients after stroke. After titles and abstracts were screened, 49 full texts were reviewed, and 7 were included in this review. Data were extracted and assessed for quality and risk of bias. We looked at any neurorehabilitation setting, and compared sleep with no sleep and explored these factors in stroke patients versus healthy individuals. Rehabilitation is critical for many activities that may need to be learned or re-learned following stroke and for returning to everyday life. In this context, sleep is essential in neurorehabilitation and physical therapy practice as it supports neuroplasticity, memory, and learning. The available data suggest that sleep should be considered in the treatment plan for successfully targeted physiotherapy to optimize cognitive and motor learning. Physical therapists should advise about sleep hygiene and therapies to improve sleep, both quality and quantity.
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Sleep in animals plays roles that appear specific to the brain, including synaptic homeostasis [1], neurotransmitter regulation [2], cellular repair [3], memory consolidation [4], and neural plasticity [5,6]. Would any of these functions of sleep be relevant to an animal without a brain? The upside-down jellyfish Cassiopea xamachana , like other cnidarians, lacks a centralized nervous system, yet the animal sleeps [7]. By tracking the propensity of the radially spaced ganglia to initiate muscle contractions over several days we determined how neural activity changes between sleep and wake in a decentralized nervous system. Ganglia-network sleep/ wake activity patterns range from being highly specialized to a few ganglia, to being completely unspecialized. Ganglia specialization also changes over time, indicating a high degree of plasticity in the neural network. The ganglia that lead activity can persist or switch between sleep/wake transitions, signifying a level of local control of the behavioral state in a decentralized nervous system. Following sleep deprivation, ganglia usage becomes far more sleep-specialized, demonstrating reduced network plasticity. Together, these findings identify a novel behavioral control system that is decentralized and yet displays temporal specialization and centralization, and show a role for sleep in maintaining neural network plasticity, revealing a conserved function of sleep in this brain-less animal.
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Background- Yoga nidra practice in novices is known to improve sleep. Its effect on objective parameters on sleep and on cognitive performance is not well known. The aim of the study was to study the effect of yoga nidra practice on cognition and night time sleep using objective parameters. Methods- 41 healthy volunteers were enrolled and baseline sleep diary collected. Subjects underwent overnight polysomnography and cognition testing battery comprising of Motor praxis test (MPT), emotion recognition task (ERT), digital symbol substitution task (DSST), visual object learning task (VOLT), abstract matching (AIM), line orientation task (LOT), matrix reasoning task (MRT), fractal-2-back test (NBACK), psychomotor vigilance task (PVT-10 min) and balloon analog risk task (BART). Yoga nidra was practiced for two weeks after training. Cognition testing battery was done at baseline and at one and two weeks of practice to compare. The cognitive tasks were further analysed using Python library and power spectra density values (PSD) calculated for EEG frequencies at central, frontal and occipital locations. Repeat sleep diary and polysomnography to assess pre- post yoga nidra intervention effects were studied. Results- Improved reaction times for all 10 cognition tasks was seen. Polysomnography (PSG) revealed significant difference in post intervention as compared to baseline. Data in change (95%CI; p-value) showed change in sleep efficiency, wake after sleep onset and delta µV2 in deep sleep : +3.62% (0.3, 5.15; p-value=0.03) , -20min (-35.78, -5.02; p=0.003) and +4.19 (0.5, 9.5; p=0.04) respectively. Accuracy was found to be significantly increased for VOLT (95% CI: 0.08, 0.17; p=0.002), AIM (95% CI: 0.03, 0.12; p= 0.02) after two weeks of practice and NBACK (95% CI: 0.02, 0.13; p=0.04) with one week of yoga nidra practice. ERT accuracy scores with yoga nidra practice showed increased recognition scores in happy, fear and anger stimuli (95% CI: 0.07, 0.24; p=0.004) but reduced scores with neutral stimuli (95% CI: -0.3, -0.05; p=0.04) after two weeks of yoga nidra practice. Conclusion- Yoga nidra practice improves cognitive processing and helps improve night-time sleep in healthy novices.
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Dreams are mental experiences, including perceptions, thoughts, and emotions, that occur during sleep. In dreams, hallucinatory perceptions, particularly visual and motoric, are often accompanied by negative emotions. When people dream, they perceive them as real even though they are bizarre and distorted in time and space. People often cannot recall their dreams, even though people dream every night. Dreaming is a strange physiological phenomenon. Research has demonstrated that dreaming is closely associated with rapid eye movement (REM) sleep. It is known that dreaming also occurs during non-REM (NREM) sleep, but the content appears to be different. Dreams during REM sleep tend to be longer, more vivid, more story-like, and more bizarre than those during NREM sleep. In this review, the neural circuits underlying dreaming and the physiological functions associated with it are summarized. Two major theories have been proposed regarding the neural circuits involved in dreaming. One is that dreams are generated by the activation of neural activity in the brainstem and its signal transmission to the cortex. The other is that dreams are caused by forebrain activation by dopamine. Whereas the physiological function of dreams remains unclear, several hypotheses have been proposed that are associated with memory and emotions.
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Introduction Electroconvulsive therapy (ECT) is an effective intervention for patients with major depressive disorder (MDD). Despite longstanding use, the underlying mechanisms of ECT are unknown, and there are no objective prognostic biomarkers that are routinely used for ECT response. Two electroencephalographic (EEG) markers, sleep slow waves and sleep spindles, could address these needs. Both sleep microstructure EEG markers are associated with synaptic plasticity, implicated in memory consolidation, and have reduced expression in depressed individuals. We hypothesize that ECT alleviates depression through enhanced expression of sleep slow waves and sleep spindles, thereby facilitating synaptic reconfiguration in pathologic neural circuits. Methods Correlating ECT Response to EEG Markers (CET-REM) is a single-center, prospective, observational investigation. Wireless wearable headbands with dry EEG electrodes will be utilized for at-home unattended sleep studies to allow calculation of quantitative measures of sleep slow waves (EEG SWA, 0.5–4 Hz power) and sleep spindles (density in number/minute). High-density EEG data will be acquired during ECT to quantify seizure markers. Discussion This innovative study focuses on the longitudinal relationships of sleep microstructure and ECT seizure markers over the treatment course. We anticipate that the results from this study will improve our understanding of ECT.
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Fast synaptic inhibition is a primary determinant of cortical activity patterns, and it is mediated predominantly by ionotropic, chloride-conducting receptors. Consequently, modulation of chloride homeostasis is ideally placed to regulate activity. We therefore investigated the stability of steady-state [Cl-]i in adult mice neocortex, using in vivo two photon imaging. We found a two-fold increase in baseline [Cl-]i in layer 2/3 pyramidal neurons, from day to night, with marked effects upon both physiological cortical processing and seizure susceptibility. Importantly, the night-time activity can be converted to day-time patterns by local inhibition of NKCC1. Consistent with these findings, the surface expression and phosphorylation states of the cation-chloride cotransporters, NKCC1 and KCC2, are diurnally modulated, with reduced chloride extrusion capacity at night. These data indicate that [Cl-]i modulation is likely to be an important determinant of variable cortical excitability, through the day.
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We tested whether brain glycogen reserves were depleted by sleep deprivation (SD) in Long-Evans rats 20-59 days old. Animals were sleep deprived beginning at lights on and then immediately killed by microwave irradiation. Glycogen and glucose levels were measured by a fluorescence enzymatic assay. In all age groups, SD reduced cerebellar glycogen levels by an average of 26% after 6 h of SD. No changes were observed in the cortex after 6 h of SD, but in the oldest animals, 12 h of SD increased cortical glycogen levels. There was a developmental increase in basal glycogen levels in both the cortex and cerebellum that peaked at 34 days and declined thereafter. Robust differences in cortical and cerebellar glycogen levels in response to enforced waking may reflect regional differences in energy utilization and regulation during wakefulness. These results show that brain glycogen reserves are sensitive to SD.
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Low-frequency stimulation (LFS) at 1 Hz for 15 min is an effective protocol to induce homosynaptic long-term depression (LTD) in visual cortical slices. It is reported that LFS becomes ineffective when brain-derived neurotrophic factor (BDNF) is applied to slices. It is not known, however, whether such a protocol induces LTD in visual cortex in vivo, and whether endogenous BDNF has the same or similar action. To address these questions, we recorded field potentials of rat visual cortex evoked by stimulation of lateral geniculate nucleus, white matter, or cortical layer IV. We found that LFS did not induce LTD of cortical responses in vivo. To test the possibility that spontaneous activity from retinas would interfere with the induction of LTD, both eyes were removed or inactivated by tetrodotoxin. LTD was not induced in these conditions either. To test whether the difference in temperature between the two preparations is a factor for the discrepancy, the temperature of slices was increased from 31 to 37 degrees C. LTD was induced in slices at either temperature. Then, we hypothesized that endogenous BNDF and its receptors, TrkB, prevent the induction of LTD. To test this, we infused the cortex with an inhibitor of Trk receptor tyrosine kinases, anti-TrkB IgG1, anti-BDNF, and anti-neurotrophin 4/5 antibodies. LTD was induced when the BDNF-TrkB system was blocked. In slices, the level of phosphorylation of Trks was found to decrease with time. These results indicate that activation of TrkB signal pathway prevents LFS from inducing synaptic depression in visual cortex in vivo.
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Prefrontal cortex (PFC)-related functions are particularly sensitive to sleep loss. However, their repeated examination is intricate because of methodological constraints such as practice effects and loss of novelty. We investigated to what extent the circadian timing system and the sleep homeostat influence PFC-related performance in differently difficult versions of a single task. Parallel versions of a planning task combined with a control group investigation were used to control for practice effects. Thirteen healthy volunteers (five women and eight men, range 57-74 years) completed a 40-h sleep deprivation (SD) and a 40-h multiple nap protocol (NAP) under constant routine conditions. Each participant performed 11 easy and 11 difficult task versions under either SD or NAP conditions. The cognitive and motor components of performance could be distinguished and analysed separately. Only by thoroughly controlling for superimposed secondary factors such as practice or sequence effects, could a significant influence of circadian timing and sleep pressure be clearly detected in planning performance in the more difficult, but not easier maze tasks. These results indicate that sleep loss-related decrements in planning performance depend on difficulty level, and that apparently insensitive tasks can turn out to be sensitive to sleep loss and circadian variation.
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During slow-wave sleep, rat brain glycogen increases within a few minutes to about 70% above waking levels. Upon awakening, the increment is lost within 2-5 min. After repeated episodes of sleep, brain glycogen levels are comparable to those observed after only a single episode of sleep. Liver glycogen is unaffected by slow-wave sleep.
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From previous studies by the present authors (see PA, Vols 66:5938, 67:116, 68:10491, 68:8270), conflicting results were obtained concerning whether EEG measures of sleep disturbance differentiate among subtypes of depression. 66 previously studied Ss (see record 1982-30491-001), who were diagnosed as having endogenous or non-endogenous depression, had their sleep EEG recorded for 2 nights. Ss were rated on the Hamilton Rating Scale for Depression (HRS), and insomnia was categorized as being initial insomnia (II), middle insomnia (MI), or delayed insomnia (DI). EEG variables were sleep latency (SL), awake (A), and early morning awake (EMA). Observer rating of sleep disturbance was compared with the analogous sleep EEG variable. Regression analysis showed significant relationships for II with SL and MI with A, but not for DI with EMA. With each HRS rating as the dependent variable, all 3 sleep EEG measures were used as independent variables, along with status and diagnosis. Results differed in that the relationship between II and SL was not significant after the stronger relationship between II and A had been accounted for. Self- and observer-ratings of insomnia were equally good (or poor) at predicting EEG measures of sleep disturbance. Results help to explain why previous HRS ratings of sleep did not contribute to a discriminant function separating unipolar endogenous depressives from non-endogenous depressives. (16 ref) (PsycINFO Database Record (c) 2012 APA, all rights reserved)
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Using transcranial Doppler ultrasonography, we measured in 6 healthy young men cerebral blood flow velocity (CBFV) in the middle cerebral artery as well as oxygen saturation by a non-invasive method. Continuous recordings were taken starting from a point before the onset of sleep, throughout the duration of normal nighttime sleep, ending after awakening. During stages 2, 3 and 4, CBFV was approximately 15% lower than during the waking period preceding sleep. CBFV during rapid eye movement sleep did not differ from the presleep waking value, whereas the postsleep waking value was 6.6% lower. In 5 subjects CBFV showed a transient rise after sleep onset. Oxygen saturation was lower during sleep than during waking.
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The origin of both sleep and memory appears to be closely associated with the evolution of mechanisms of enhancement and maintenance of synaptic efficacy. The development of activity-dependent synaptic plasticity apparently was the first evolutionary adaptation of nervous systems beyond a capacity to respond to environmental stimuli by mere reflexive actions. After the origin of activity-dependent synaptic plasticity, whereby single activations of synapses led to short-term efficacy enhancement, lengthy maintenance of enhancements probably was achieved by repetitive activations ("dynamic stabilization"). One source of selective pressure for the evolutionary origin of neurons and neural circuits with oscillatory firing capacities may have been a need for repetitive spontaneous activations to maintain synaptic efficacy in circuits that were in infrequent use. This process is referred to as "non-utilitarian" dynamic stabilization. Dynamic stabilization of synapses in "simple" invertebrates occurs primarily through frequent use. In complex, locomoting forms, it probably occurs through both frequent use and non-utilitarian activations during restful waking. With the evolution of increasing repertories and complexities of behavioral and sensory capabilities--with vision usually being the vastly pre-eminent sense brain complexity increased markedly. Accompanying the greater complexity, needs for storage and maintenance of hereditary and experiential information (memories) increased greatly. It is suggested that these increases led to conflicts between sensory input processing during restful waking and concomitant non-utilitarian dynamic stabilization of infrequently used memory circuits. The selective pressure for the origin of primitive sleep may have been a resulting need to achieve greater depression of central processing of sensory inputs largely complex visual information than occurs during restful waking. The electrical activities of the brain during sleep (aside from those that subserve autonomic activities) may function largely to maintain sleep and to dynamically stabilize infrequently used circuitry encoding memories. Sleep may not have been the only evolutionary adaptation to conflicts between dynamic stabilization and sensory input processing. In some ectothermic vertebrates, sleep may have been postponed or rendered unnecessary by a more readily effected means of resolution of the conflicts, namely, extensive retinal processing of visual information during restful waking. By this means, processing of visual information in central regions of the brain may have been maintained at a sufficiently low level to allow adequate concomitant dynamic stabilization. As endothermy evolved, the skeletal muscle hypotonia of primitive sleep may have become insufficient to prevent sleep-disrupting skeletal muscle contractions during non-utilitarian dynamic stabilization of motor circuitry at the accompanying higher body temperatures and metabolic rates. Selection against such disruption during dynamic stabilization of motor circuitry may have led to the inhibition of skeletal muscle tone during a portion of primitive sleep, the portion designated as rapid-eye-movement sleep. Many marine mammals that are active almost continuously engage only in unihemispheric non-rapid-eye-movement sleep. They apparently do not require rapid-eye-movement sleep and accompanying non-utilitarian dynamic stabilization of motor circuitry, because this circuitry is in virtually continuous use. Studies of hibernation by arctic ground squirrels suggest that each hour of sleep may stabilize brain synapses for as long as 4 h. Phasic irregularities in heart and respiratory rates during rapid-eye-movement sleep may be a consequence of superposition of dynamic stabilization of motor circuitry on the rhythmic autonomic control mechanisms. Some information encoded in circuitry being dynamically stabilized during sleep achieves unconscious awareness in authentic and var
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This study was designed to find out if bed rest, which is known to markedly reduce peripheral lymph flow, immediately after strenuous exercise could affect the behaviour of creatine kinase activity (CK) in serum. Eleven endurance athletes performed an 18 km cross-country run, after which six of the subjects were placed in bed rest group (BR) for 23 hours, while a group of five control subjects maintained their normal habitual activity (C). After the bed rest all subjects performed a light jogging bout for 45 min. Seven hours after the exercise serum CK was increased threefold (p < 0.05) in both groups. During the next 16 hours serum CK increased further 30% in C (p < 0.05) but decreased (p < 0.05) in a similar magnitude in BR. Light jogging elicited a transient CK increase of 16% (p < 0.05) in C, but there was no change in BR. The fact that serum CK increased similarly in both groups during the first hours after the exercise shows that the transport of CK from muscles into circulation can be maintained for some hours despite absence of muscular activity. However, the later post-exercise serum CK response may be diminished by bed rest (effect of posture and/or lack of muscle function). The reduced response is also seen in the CK response to a repeated exercise. These observations suggest that a short-term physical inactivity (bed rest) may reduce both the lymphatic transport of CK and the release of enzyme from muscle fibres.
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Patterns of neuronal activity recorded in CA1 of the hippocampus and in neocortex during waking-behavior, are reactivated during subsequent slow-wave sleep (SWS). It has been suggested that this reactivation may originate in the hippocampal CA3 region, where modifiable excitatory recurrent connections are abundant and where sharp-waves in which the reactivation is most robust, appear to arise. The present experiment investigated whether ensemble firing patterns of granule cells in the fascia dentata (FD), an area 'upstream' from CA3, are also reactivated during sleep. Populations of FD granule cells were recorded from during spatial behavior and during prior and subsequent SWS. firing rate correlations between cell-pairs with overlapping place fields were significantly enhanced during post behavioral sleep compared to pre behavioral sleep. Correlations between cells with non-overlapping place fields or which were silent during maze behavior, were not changed. Thus reactivation of experience-specific correlation states also occurs in granule cells during sleep. Because these cells do not have excitatory interconnections, but form a major input to CA3 pyramidal cells, current models predicted that sleep reactivation would appear first in CA3. There are, however, both extensive polysynaptic excitatory interactions among granule cells and feedback from CA3 pyramidal cells. Granule cells also receive indirect input from neocortical regions known to undergo trace reactivation. Although a simple model for a CA3 origin of the reactivation phenomenon cannot be confirmed, the present results extend our understanding of the generality of this phenomenon.
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Regional differences in EEG slow wave activity (SWA) during sleep after sleep deprivation (SD) may be a consequence of differential metabolic activation of cortical areas. We investigated the relationship between the regional EEG dynamics and 2-deoxyglucose (DG) uptake after SD in mice. Six hours' SD were combined with natural unilateral whisker stimulation in an enriched environment to selectively activate the barrel cortex and motor areas. As expected, an interhemispheric asymmetry of 2-DG uptake was found in the barrel cortex immediately after SD. To test whether sleep contributes to recovery of the asymmetry, the stimulation was followed by either undisturbed sleep or by an additional SD. The asymmetry vanished after recovery sleep but also after the additional period of wakefulness without stimulation. In addition, relative 2-DG uptake in the primary motor cortex and retrosplenial area was significantly higher immediately after the SD than after the additional sleep or wakefulness, whereas no other region differed between the groups. Whisker stimulation elicited a greater increase in EEG SWA during non rapid eye movement sleep in the stimulated hemisphere than in the control hemisphere; this increase lasted for 10 h. Within a hemisphere, the initial increase in SWA was higher in the frontal than in the parietal derivation. We conclude that the regional SWA differences during sleep are use-dependent and may be related to the regional pattern of metabolism during the previous waking episode. However, the regional metabolic recovery is not dependent on sleep, and is not directly reflected in changes in SWA during sleep.