Prolonged wakefulness alters neuronal responsiveness to local electrical stimulation of the neocortex in awake rats

Sleep- and sleep deprivation-related changes of vertex auditory evoked potentials during the estrus cycle in female rats

The estrus cycle in female rodents has been shown to affect a variety of physiological functions. However, little is known about its presumably thorough effect on auditory processing during the sleep-wake cycle and sleep deprivation. Vertex auditory evoked potentials (vAEPs) were evoked by single click tone stimulation and recorded during different stages of the estrus cycle and sleep deprivation performed in metestrus and proestrus in female rats. vAEPs showed a strong sleep-dependency, with the largest amplitudes present during slow wave sleep while the smallest ones during wakefulness. Higher amplitudes and longer latencies were seen in the light phase during all vigilance stages. The largest amplitudes were found during proestrus (light phase) while the shortest latencies were seen during estrus (dark phase) compared to the 2nd day diestrus baseline. High-amplitude responses without latency changes were also seen during metestrus with increased homeostatic sleep drive. More intense and faster processing of auditory information during proestrus and estrus suggesting a more effective perception of relevant environmental cues presumably in preparation for sexual receptivity. A 4-h sleep deprivation resulted in more pronounced sleep recovery in metestrus compared to proestrus without difference in delta power replacement suggesting a better tolerance of sleep deprivation in proestrus. Sleep deprivation decreased neuronal excitability and responsiveness in a similar manner both during metestrus and proestrus, suggesting that the negative consequences of sleep deprivation on auditory processing may have a limited correlation with the estrus cycle stage.

Cortico-thalamo-cortical interactions modulate electrically evoked EEG responses in mice

Perturbational complexity analysis predicts the presence of consciousness in volunteers and patients by stimulating the brain with brief pulses, recording EEG responses, and computing their spatiotemporal complexity. We examined the underlying neural circuits in mice by directly stimulating cortex while recording with EEG and Neuropixels probes during wakefulness and isoflurane anesthesia. When mice are awake, stimulation of deep cortical layers reliably evokes locally a brief pulse of excitation, followed by a biphasic sequence of 120 ms profound off period and a rebound excitation. A similar pattern, partially attributed to burst spiking, is seen in thalamic nuclei and is associated with a pronounced late component in the evoked EEG. We infer that cortico-thalamo-cortical interactions drive the long-lasting evoked EEG signals elicited by deep cortical stimulation during the awake state. The cortical and thalamic off period and rebound excitation, and the late component in the EEG, are reduced during running and absent during anesthesia.

Sleep-like changes in neural processing emerge during sleep deprivation in early auditory cortex

Insufficient sleep is commonplace in modern lifestyle and can lead to grave outcomes, yet the changes in neuronal activity accumulating over hours of extended wakefulness remain poorly understood. Specifically, which aspects of cortical processing are affected by sleep deprivation (SD), and whether they also affect early sensory regions, remain unclear. Here, we recorded spiking activity in the rat auditory cortex along with polysomnography while presenting sounds during SD followed by recovery sleep. We found that frequency tuning, onset responses, and spontaneous firing rates were largely unaffected by SD. By contrast, SD decreased entrainment to rapid (≥20 Hz) click trains, increased population synchrony, and increased the prevalence of sleep-like stimulus-induced silent periods, even when ongoing activity was similar. Recovery NREM sleep was associated with similar effects as SD with even greater magnitude, while auditory processing during REM sleep was similar to vigilant wakefulness. Our results show that processes akin to those in NREM sleep invade the activity of cortical circuits during SD, even in the early sensory cortex.

Sleep Deprivation-Induced Changes in Baseline Brain Activity and Vigilant Attention Performance

Sleep deprivation (SD) negatively affects several aspects of cognitive performance, and one of the most widely-used tools to evaluate these effects is the Psychomotor Vigilance Test (PVT). The present study investigated the possibility of predicting changes induced by SD in vigilant attention performance by evaluating the baseline electroencephalographic (EEG) activity immediately preceding the PVT stimuli onset. All participants (n = 10) underwent EEG recordings during 10 min of PVT before and after a night of SD. For each participant, the root mean square (RMS) of the baseline EEG signal was evaluated for each 1 s time window, and the respective average value was computed. After SD, participants showed slower (and less accurate) performance in the PVT task. Moreover, a close relationship between the changes in the baseline activity with those in cognitive performance was identified at several electrodes (Fp2, F7, F8, P3, T6, O1, Oz, O2), with the highest predictive power at the occipital derivations. These results indicate that vigilant attention impairments induced by SD can be predicted by the pre-stimulus baseline activity changes.

Neuronal-spiking-based closed-loop stimulation during cortical ON- and OFF-states in freely moving mice

The slow oscillation is a central neuronal dynamic during sleep, and is generated by alternating periods of high and low neuronal activity (ON- and OFF-states). Mounting evidence causally links the slow oscillation to sleep's functions, and it has recently become possible to manipulate the slow oscillation non-invasively and phase-specifically. These developments represent promising clinical avenues, but they also highlight the importance of improving our understanding of how ON/OFF-states affect incoming stimuli and what role they play in neuronal plasticity. Most studies using closed-loop stimulation rely on the electroencephalogram and local field potential signals, which reflect neuronal ON- and OFF-states only indirectly. Here we develop an online detection algorithm based on spiking activity recorded from laminar arrays in mouse motor cortex. We find that online detection of ON- and OFF-states reflects specific phases of spontaneous local field potential slow oscillation. Our neuronal-spiking-based closed-loop procedure offers a novel opportunity for testing the functional role of slow oscillation in sleep-related restorative processes and neural plasticity.

Propofol anesthesia concentration rather than abrupt behavioral unresponsiveness linearly degrades responses in the rat primary auditory cortex

Despite extensive knowledge of its molecular and cellular effects, how anesthesia affects sensory processing remains poorly understood. In particular, it remains unclear whether anesthesia modestly or robustly degrades activity in primary sensory regions, and whether such changes are linked to anesthesia drug concentration versus behavioral unresponsiveness, which are typically confounded. Here, we used slow gradual intravenous propofol anesthesia induction together with auditory stimulation and intermittent assessment of behavioral responsiveness while recording epidural electroencephalogram, and neuronal spiking activity in primary auditory cortex (PAC) of eight rats. We found that all main components of neuronal activity including spontaneous firing rates, onset response magnitudes, onset response latencies, postonset neuronal silence duration, late-locking to 40 Hz click-trains, and offset responses, gradually changed in a dose-dependent manner with increasing anesthesia levels without showing abrupt shifts around loss of righting reflex or other time-points. Thus, the dominant factor affecting PAC responses is the anesthesia drug concentration rather than any sudden, dichotomous behavioral state changes. Our findings explain a wide array of seemingly conflicting results in the literature that, depending on the precise definition of wakefulness (vigilant vs. drowsy) and anesthesia (light vs. deep/surgical), report a spectrum of effects in primary regions ranging from minimal to dramatic differences.

Behavioral and physiological monitoring for awake neurovascular coupling experiments: a how-to guide

Significance: Functional brain imaging in awake animal models is a popular and powerful technique that allows the investigation of neurovascular coupling (NVC) under physiological conditions. However, ubiquitous facial and body motions (fidgeting) are prime drivers of spontaneous fluctuations in neural and hemodynamic signals. During periods without movement, animals can rapidly transition into sleep, and the hemodynamic signals tied to arousal state changes can be several times larger than sensory-evoked responses. Given the outsized influence of facial and body motions and arousal signals in neural and hemodynamic signals, it is imperative to detect and monitor these events in experiments with un-anesthetized animals. Aim: To cover the importance of monitoring behavioral state in imaging experiments using un-anesthetized rodents, and describe how to incorporate detailed behavioral and physiological measurements in imaging experiments. Approach: We review the effects of movements and sleep-related signals (heart rate, respiration rate, electromyography, intracranial pressure, whisking, and other body movements) on brain hemodynamics and electrophysiological signals, with a focus on head-fixed experimental setup. We summarize the measurement methods currently used in animal models for detection of those behaviors and arousal changes. We then provide a guide on how to incorporate this measurements with functional brain imaging and electrophysiology measurements. Results: We provide a how-to guide on monitoring and interpreting a variety of physiological signals and their applications to NVC experiments in awake behaving mice. Conclusion: This guide facilitates the application of neuroimaging in awake animal models and provides neuroscientists with a standard approach for monitoring behavior and other associated physiological parameters in head-fixed animals.

[Speech and behavioral contaminations as non-epileptic automatic behavior in Parkinson's disease]

Parkinson's disease is characterized by a variety of motor and non-motor symptoms. More than two hundred years have passed since its description, but we still discover its new manifestations. Abnormal behaviors include impulse control disorders, dopamine dysregulation syndrome, psychotic disorders and others. However, two new phenomena have been recently described in patients with PD. It can manifest in the form of doing inappropriate actions which patient doesn't recognize, or pronouncing/writing unsuitable words and phrases. Patients can't remember such episodes, but find «signs» of their unconscious activity or hear about it from attestors. This article represents a review of literature on unrelated communication interlude and automatic behavior in Parkinson's disease and discusses its possible reasons.

A wake-up call: Sleep physiology and related translational discrepancies in studies of rapid-acting antidepressants

Depression is frequently associated with sleep problems, and clinical improvement often coincides with the normalization of sleep architecture and realignment of circadian rhythm. The effectiveness of treatments targeting sleep in depressed patients, such as sleep deprivation, further demonstrates the confluence of sleep and mood. Moreover, recent studies showing that the rapid-acting antidepressant ketamine influences processes related to sleep-wake neurobiology have led to novel hypotheses explaining rapid and sustained antidepressant effects. Despite the available evidence, studies addressing ketamine’s antidepressant effects have focused on pharmacology and often overlooked the role of physiology. To explore this discrepancy in research on rapid-acting antidepressants, we examined articles published between 2009–2019. A keyword search algorithm indicated that vast majority of the articles completely ignored sleep. Out of the 100 most frequently cited preclinical and clinical research papers, 89 % and 71 %, respectively, did not mention sleep at all. Furthermore, only a handful of these articles disclosed key experimental variables, such as the times of treatment administration or behavioral testing, let alone considered the potential association between these variables and experimental observations. Notably, in preclinical studies, treatments were preferentially administered during the inactive period, which is the polar opposite of clinical practice and research. We discuss the potential impact of this practice on the results in the field. Our hope is that this perspective will serve as a wake-up call to (re)-examine rapid-acting antidepressant effects with more appreciation for the role of sleep and chronobiology.

General Anesthesia Disrupts Complex Cortical Dynamics in Response to Intracranial Electrical Stimulation in Rats

The capacity of human brain to sustain complex cortical dynamics appears to be strongly associated with conscious experience and consistently drops when consciousness fades. For example, several recent studies in humans found a remarkable reduction of the spatiotemporal complexity of cortical responses to local stimulation during dreamless sleep, general anesthesia, and coma. However, this perturbational complexity has never been directly estimated in non-human animals in vivo previously, and the mechanisms that prevent neocortical neurons to engage in complex interactions are still unclear. Here, we quantify the complexity of electroencephalographic (EEG) responses to intracranial electrical stimulation in rats, comparing wakefulness to propofol, sevoflurane, and ketamine anesthesia. The evoked activity changed from highly complex in wakefulness to far simpler with propofol and sevoflurane. The reduced complexity was associated with a suppression of high frequencies that preceded a reduced phase-locking, and disruption of functional connectivity and pattern diversity. We then showed how these parameters dissociate with ketamine and depend on intensity and site of stimulation. Our results support the idea that brief periods of activity-dependent neuronal silence can interrupt complex interactions in neocortical circuits, and open the way for further mechanistic investigations of the neuronal basis for consciousness and loss of consciousness across species.

Sleepiness as a Local Phenomenon

Sleep occupies a third of our life and is a primary need for all animal species studied so far. Nonetheless, chronic sleep restriction is a growing source of morbidity and mortality in both developed and developing countries. Sleep loss is associated with the subjective feeling of sleepiness and with decreased performance, as well as with detrimental effects on general health, cognition, and emotions. The ideas that small brain areas can be asleep while the rest of the brain is awake and that local sleep may account for at least some of the cognitive and behavioral manifestations of sleepiness are making their way into the scientific community. We herein clarify the different ways sleep can intrude into wakefulness, summarize recent scientific advances in the field, and offer some hypotheses that help framing sleepiness as a local phenomenon.

Cognitive fluctuations in Lewy body dementia: towards a pathophysiological framework

Fluctuating cognition is a complex and disabling symptom that is seen most frequently in the context of Lewy body dementias encompassing dementia with Lewy bodies and Parkinson’s disease dementia. In fact, since their description over three decades ago, cognitive fluctuations have remained a core diagnostic feature of dementia with Lewy bodies, the second most common dementia in the elderly. In the absence of reliable biomarkers for Lewy body pathology, the inclusion of such patients in therapeutic trials depends on the accurate identification of such core clinical features. Yet despite their diagnostic relevance, cognitive fluctuations remain poorly understood, in part due to the lack of a cohesive clinical and scientific explanation of the phenomenon itself. Motivated by this challenge, the present review examines the history, clinical phenomenology and assessment of cognitive fluctuations in the Lewy body dementias. Based on these data, the key neuropsychological, neurophysiological and neuroimaging correlates of cognitive fluctuations are described and integrated into a novel testable heuristic framework from which new insights may be gained.

Closed-Loop Acoustic Stimulation During Sleep in Children With Epilepsy: A Hypothesis-Driven Novel Approach to Interact With Spike-Wave Activity and Pilot Data Assessing Feasibility

Slow waves, the electroencephalographic (EEG) hallmark of deep sleep, can be systematically manipulated by acoustic stimulation: stimulation time-locked to the down phase of slow waves reduces, whereas stimulation time-locked to the up phase increases slow waves. Spike-waves during sleep seem to be related to slow waves, raising the question of whether spike-waves can be systematically influenced by such acoustic stimulation. In five pediatric patients, all-night EEG was recorded, combined with real-time slow wave detection. Throughout the night, acoustic stimulation was performed in a 3 × 5-min-block design (no stimulation—stimulation—no stimulation). Tones were applied time-locked either to the up or to the down phase of the detected slow waves in an alternating pattern. All patients tolerated the acoustic stimulation during sleep well. They showed high sleep quality and no signs of clinical or non-convulsive electrographic seizures. Our preliminary analysis shows no systematic effect of acoustic stimulation on spike-wave activity. Moreover, with our stimulation approach tones were distributed over a rather broad phase-range during the DOWN or UP stimulation and showed inter-individual differences in their distribution. In this study, we applied for the first time an acoustic closed-loop slow wave stimulation tool for a non-invasive manipulation of spike-wave activity. Thus, our pilot data show that closed-loop acoustic stimulation is feasible and well tolerated in children with spike wave activity during sleep. Improved precision in phase targeting and personalized stimulation parameters in a larger sample of subjects might be needed to show systematic effects.

A fast and general method to empirically estimate the complexity of brain responses to transcranial and intracranial stimulations

BACKGROUND

The Perturbational Complexity Index (PCI) was recently introduced to assess the capacity of thalamocortical circuits to engage in complex patterns of causal interactions. While showing high accuracy in detecting consciousness in brain-injured patients, PCI depends on elaborate experimental setups and offline processing, and has restricted applicability to other types of brain signals beyond transcranial magnetic stimulation and high-density EEG (TMS/hd-EEG) recordings.

OBJECTIVE

We aim to address these limitations by introducing PCI^ST, a fast method for estimating perturbational complexity of any given brain response signal.

METHODS

PCI^ST is based on dimensionality reduction and state transitions (ST) quantification of evoked potentials. The index was validated on a large dataset of TMS/hd-EEG recordings obtained from 108 healthy subjects and 108 brain-injured patients, and tested on sparse intracranial recordings (SEEG) of 9 patients undergoing intracranial single-pulse electrical stimulation (SPES) during wakefulness and sleep.

RESULTS

When calculated on TMS/hd-EEG potentials, PCI^ST performed with the same accuracy as the original PCI, while improving on the previous method by being computed in less than a second and requiring a simpler set-up. In SPES/SEEG signals, the index was able to quantify a systematic reduction of intracranial complexity during sleep, confirming the occurrence of state-dependent changes in the effective connectivity of thalamocortical circuits, as originally assessed through TMS/hd-EEG.

CONCLUSIONS

PCI^ST represents a fundamental advancement towards the implementation of a reliable and fast clinical tool for the bedside assessment of consciousness as well as a general measure to explore the neuronal mechanisms of loss/recovery of brain complexity across scales and models.

Primed to Sleep: The Dynamics of Synaptic Plasticity Across Brain States

It is commonly accepted that brain plasticity occurs in wakefulness and sleep. However, how these different brain states work in concert to create long-lasting changes in brain circuitry is unclear. Considering that wakefulness and sleep are profoundly different brain states on multiple levels (e.g., cellular, molecular and network activation), it is unlikely that they operate exactly the same way. Rather it is probable that they engage different, but coordinated, mechanisms. In this article we discuss how plasticity may be divided across the sleep-wake cycle, and how synaptic changes in each brain state are linked. Our working model proposes that waking experience triggers short-lived synaptic events that are necessary for transient plastic changes and mark (i.e., 'prime') circuits and synapses for further processing in sleep. During sleep, synaptic protein synthesis at primed synapses leads to structural changes necessary for long-term information storage.

Consciousness in hibernation and synthetic torpor

While human hibernation would provide many advantages for medical applications and space exploration, the intrinsic risks of the procedure itself, as well as those involved if the procedure were to be misused, need to be assessed. Moreover, the distinctive brain state that is present during a hibernation-like state raises questions regarding the state of consciousness of the subject. Since, in animal studies, the cortical activity of this state differs from that of sleep, coma, or even general anesthesia, and resembles a sort of "slowed wakefulness", it is uncertain whether residual consciousness may still be present. In this review, I will present a brief summary of the literature on hibernation and of the current state of the art in inducing a state of artificial hibernation (synthetic torpor); I will then focus on the brain changes that are observed during hibernation, on how these could modify the neural substrate of consciousness, and on the possible use of hibernation as a model for quantum biology. Finally, some ethical considerations on the use of synthetic torpor technology will be presented.

Sleep- and Wake-Like States in Small Networks In Vivo and In Vitro

Wakefulness and sleep are highly complex and heterogeneous processes, involving multiple neurotransmitter systems and a sophisticated interplay between global and local networks of neurons and non-neuronal cells. Macroscopic approaches applied at the level of the whole organism, view sleep as a global behaviour and allow for investigation into aspects such as the effects of insufficient or disrupted sleep on cognitive function, metabolism, thermoregulation and sensory processing. While significant progress has been achieved using such large-scale approaches, the inherent complexity of sleep-wake regulation has necessitated the development of methods which tackle specific aspects of sleep in isolation. One way this may be achieved is by investigating specific cellular or molecular phenomena in the whole organism in situ, either during spontaneous or induced sleep-wake states. This approach has greatly advanced our knowledge about the electrophysiology and pharmacology of ion channels, specific receptors, intracellular pathways and the small networks implicated in the control and regulation of the sleep-wake cycle. Importantly though, there are a variety of external and internal factors that influence global behavioural states which are difficult to control for using these approaches. For this reason, over the last few decades, ex vivo experimental models have become increasingly popular and have greatly advanced our understanding of many fundamental aspects of sleep, including the neuroanatomy and neurochemistry of sleep states, sleep regulation, the origin and dynamics of specific sleep oscillations, network homeostasis as well as the functional roles of sleep. This chapter will focus on the use of small neuronal networks as experimental models and will highlight the most significant and novel insights these approaches have provided.

Theta waves in children's waking electroencephalogram resemble local aspects of sleep during wakefulness

Vyazovskiy and colleagues found in rats’ multi-unit recordings brief periods of silence (off-states) in local populations of cortical neurons during wakefulness which closely resembled the characteristic off-states during sleep. These off-states became more global and frequent with increasing sleep pressure and were associated with the well-known increase of theta activity under sleep deprivation in the surface EEG. Moreover, the occurrence of such off-states was related to impaired performance. While these animal experiments were based on intracranial recordings, we aimed to explore whether the human surface EEG may also provide evidence for such a local sleep-like intrusion during wakefulness. Thus, we analysed high-density wake EEG recordings during an auditory attention task in the morning and evening in 12 children. We found that, theta waves became more widespread in the evening and the occurrence of widespread theta waves was associated with slower reaction times in the attention task. These results indicate that widespread theta events measured on the scalp might be markers of local sleep in humans. Moreover, such markers of local sleep, seem to be related to the well described performance decline under high sleep pressure.

Deep sleep maintains learning efficiency of the human brain

It is hypothesized that deep sleep is essential for restoring the brain’s capacity to learn efficiently, especially in regions heavily activated during the day. However, causal evidence in humans has been lacking due to the inability to sleep deprive one target area while keeping the natural sleep pattern intact. Here we introduce a novel approach to focally perturb deep sleep in motor cortex, and investigate the consequences on behavioural and neurophysiological markers of neuroplasticity arising from dedicated motor practice. We show that the capacity to undergo neuroplastic changes is reduced by wakefulness but restored during unperturbed sleep. This restorative process is markedly attenuated when slow waves are selectively perturbed in motor cortex, demonstrating that deep sleep is a requirement for maintaining sustainable learning efficiency.

Deep sleep is hypothesized to restore the brain's capacity to learn. Here the authors provide causal evidence by specifically perturbing slow wave activity over the motor cortex during NREM sleep in humans and demonstrate a reduction in neurophysiological markers of plasticity and capacity for motor learning.

Different Effects of Sleep Deprivation and Torpor on EEG Slow-Wave Characteristics in Djungarian Hamsters

It has been shown previously in Djungarian hamsters that the initial electroencephalography (EEG) slow-wave activity (power in the 0.5–4.0 Hz band; SWA) in non-rapid eye movement (NREM) sleep following an episode of daily torpor is consistently enhanced, similar to the SWA increase after sleep deprivation (SD). However, it is unknown whether the network mechanisms underlying the SWA increase after torpor and SD are similar. EEG slow waves recorded in the neocortex during sleep reflect synchronized transitions between periods of activity and silence among large neuronal populations. We therefore set out to investigate characteristics of individual cortical EEG slow waves recorded during NREM sleep after 4 h SD and during sleep after emergence from an episode of daily torpor in adult male Djungarian hamsters. We found that during the first hour after both SD and torpor, the SWA increase was associated with an increase in slow-wave incidence and amplitude. However, the slopes of single slow waves during NREM sleep were steeper in the first hour after SD but not after torpor, and, in contrast to sleep after SD, the magnitude of change in slopes after torpor was unrelated to the changes in SWA. Furthermore, slow-wave slopes decreased progressively within the first 2 h after SD, while a progressive increase in slow-wave slopes was apparent during the first 2 h after torpor. The data suggest that prolonged waking and torpor have different effects on cortical network activity underlying slow-wave characteristics, while resulting in a similar homeostatic sleep response of SWA. We suggest that sleep plays an important role in network homeostasis after both waking and torpor, consistent with a recovery function for both states.

Stereotypic wheel running decreases cortical activity in mice

Prolonged wakefulness is thought to gradually increase ‘sleep need' and influence subsequent sleep duration and intensity, but the role of specific waking behaviours remains unclear. Here we report the effect of voluntary wheel running during wakefulness on neuronal activity in the motor and somatosensory cortex in mice. We find that stereotypic wheel running is associated with a substantial reduction in firing rates among a large subpopulation of cortical neurons, especially at high speeds. Wheel running also has longer-term effects on spiking activity across periods of wakefulness. Specifically, cortical firing rates are significantly higher towards the end of a spontaneous prolonged waking period. However, this increase is abolished when wakefulness is dominated by running wheel activity. These findings indicate that wake-related changes in firing rates are determined not only by wake duration, but also by specific waking behaviours.

Sleep need is thought to accumulate gradually over waking periods and is associated with changes in neuronal activity. Here the authors show that in mice cortical firing rates increase between the beginning and end of wakefulness periods but this increase is not seen in waking periods with voluntary stereotypic wheel running.

Eyes Open on Sleep and Wake: In Vivo to In Silico Neural Networks

Functional and effective connectivity of cortical areas are essential for normal brain function under different behavioral states. Appropriate cortical activity during sleep and wakefulness is ensured by the balanced activity of excitatory and inhibitory circuits. Ultimately, fast, millisecond cortical rhythmic oscillations shape cortical function in time and space. On a much longer time scale, brain function also depends on prior sleep-wake history and circadian processes. However, much remains to be established on how the brain operates at the neuronal level in humans during sleep and wakefulness. A key limitation of human neuroscience is the difficulty in isolating neuronal excitation/inhibition drive in vivo. Therefore, computational models are noninvasive approaches of choice to indirectly access hidden neuronal states. In this review, we present a physiologically driven in silico approach, Dynamic Causal Modelling (DCM), as a means to comprehend brain function under different experimental paradigms. Importantly, DCM has allowed for the understanding of how brain dynamics underscore brain plasticity, cognition, and different states of consciousness. In a broader perspective, noninvasive computational approaches, such as DCM, may help to puzzle out the spatial and temporal dynamics of human brain function at different behavioural states.

Sleep Deprivation and Recovery Sleep Prior to a Noxious Inflammatory Insult Influence Characteristics and Duration of Pain

STUDY OBJECTIVES

Insufficient sleep and chronic pain are public health epidemics. Sleep loss worsens pain and predicts the development of chronic pain. Whether previous, acute sleep loss and recovery sleep determine pain levels and duration remains poorly understood. This study tested whether acute sleep deprivation and recovery sleep prior to formalin injection alter post-injection pain levels and duration.

METHODS

Male Sprague-Dawley rats (n = 48) underwent sleep deprivation or ad libitum sleep for 9 hours. Thereafter, rats received a subcutaneous injection of formalin or saline into a hind paw. In the recovery sleep group, rats were allowed 24 h between sleep deprivation and the injection of formalin. Mechanical and thermal nociception were assessed using the von Frey test and Hargreaves' method. Nociceptive measures were performed at 1, 3, 7, 10, 14, 17 and 21 days post-injection.

RESULTS

Formalin caused bilateral mechanical hypersensitivity (allodynia) that persisted for up to 21 days post-injection. Sleep deprivation significantly enhanced bilateral allodynia. There was a synergistic interaction when sleep deprivation preceded a formalin injection. Rats allowed a recovery sleep period prior to formalin injection developed allodynia only in the injected limb, with higher mechanical thresholds (less allodynia) and a shorter recovery period. There were no persistent changes in thermal nociception.

CONCLUSION

The data suggest that acute sleep loss preceding an inflammatory insult enhances pain and can contribute to chronic pain. The results encourage studies in a model of surgical pain to test whether enhancing sleep reduces pain levels and duration.

Lempel-Ziv complexity of cortical activity during sleep and waking in rats

Understanding the dynamics of brain activity manifested in the EEG, local field potentials (LFP), and neuronal spiking is essential for explaining their underlying mechanisms and physiological significance. Much has been learned about sleep regulation using conventional EEG power spectrum, coherence, and period-amplitude analyses, which focus primarily on frequency and amplitude characteristics of the signals and on their spatio-temporal synchronicity. However, little is known about the effects of ongoing brain state or preceding sleep-wake history on the nonlinear dynamics of brain activity. Recent advances in developing novel mathematical approaches for investigating temporal structure of brain activity based on such measures, as Lempel-Ziv complexity (LZC) can provide insights that go beyond those obtained with conventional techniques of signal analysis. Here, we used extensive data sets obtained in spontaneously awake and sleeping adult male laboratory rats, as well as during and after sleep deprivation, to perform a detailed analysis of cortical LFP and neuronal activity with LZC approach. We found that activated brain states—waking and rapid eye movement (REM) sleep are characterized by higher LZC compared with non-rapid eye movement (NREM) sleep. Notably, LZC values derived from the LFP were especially low during early NREM sleep after sleep deprivation and toward the middle of individual NREM sleep episodes. We conclude that LZC is an important and yet largely unexplored measure with a high potential for investigating neurophysiological mechanisms of brain activity in health and disease.

Sleep, recovery, and metaregulation: explaining the benefits of sleep

A commonly held view is that extended wakefulness is causal for a broad spectrum of deleterious effects at molecular, cellular, network, physiological, psychological, and behavioral levels. Consequently, it is often presumed that sleep plays an active role in providing renormalization of the changes incurred during preceding waking. Not surprisingly, unequivocal empirical evidence supporting such a simple bi-directional interaction between waking and sleep is often limited or controversial. One difficulty is that, invariably, a constellation of many intricately interrelated factors, including the time of day, specific activities or behaviors during preceding waking, metabolic status and stress are present at the time of measurement, shaping the overall effect observed. In addition to this, although insufficient or disrupted sleep is thought to prevent efficient recovery of specific physiological variables, it is also often difficult to attribute specific changes to the lack of sleep proper. Furthermore, sleep is a complex phenomenon characterized by a multitude of processes, whose unique and distinct contributions to the purported functions of sleep are difficult to determine, because they are interrelated. Intensive research effort over the last decades has greatly progressed current understanding of the cellular and physiological processes underlying the regulation of vigilance states. Notably, it also highlighted the infinite complexity within both waking and sleep, and revealed a number of fundamental conceptual and technical obstacles that need to be overcome in order to fully understand these processes. A promising approach could be to view sleep not as an entity, which has specific function(s) and is subject to direct regulation, but as a manifestation of the process of metaregulation, which enables efficient moment-to-moment integration between internal and external factors, preceding history and current homeostatic needs.

The dynamics of cortical neuronal activity in the first minutes after spontaneous awakening in rats and mice

STUDY OBJECTIVE

Upon awakening from sleep, a fully awake brain state is not reestablished immediately, but the origin and physiological properties of the distinct brain state during the first min after awakening are unclear. To investigate whether neuronal firing immediately upon arousal is different from the remaining part of the waking episode, we recorded and analyzed the dynamics of cortical neuronal activity in the first 15 min after spontaneous awakenings in freely moving rats and mice.

DESIGN

Intracortical recordings of the local field potential and neuronal activity in freely-moving mice and rats.

SETTING

Basic sleep research laboratory.

PATIENTS OR PARTICIPANTS

WKY adult male rats, C57BL/6 adult male mice.

INTERVENTIONS

N/A.

MEASUREMENTS AND RESULTS

In both species the average population spiking activity upon arousal was initially low, though substantial variability in the dynamics of firing activity was apparent between individual neurons. A distinct population of neurons was found that was virtually silent in the first min upon awakening. The overall lower population spiking initially after awakening was associated with the occurrence of brief periods of generalized neuronal silence (OFF periods), whose frequency peaked immediately after awakening and then progressively declined. OFF periods incidence upon awakening was independent of ongoing locomotor activity but was sensitive to immediate preceding sleep/wake history. Notably, in both rats and mice if sleep before a waking episode was enriched in rapid eye movement sleep, the incidence of OFF periods was initially higher as compared to those waking episodes preceded mainly by nonrapid eye movement sleep.

CONCLUSION

We speculate that an intrusion of sleep-like patterns of cortical neuronal activity into the wake state immediately after awakening may account for some of the changes in the behavior and cognitive function typical of what is referred to as sleep inertia.

CITATION

Vyazovskiy VV, Cui N, Rodriguez AV, Funk C, Cirelli C, Tononi G. The dynamics of cortical neuronal activity in the first minutes after spontaneous awakening in rats and mice.

Sleep and synaptic homeostasis

In the last decades a substantial knowledge about sleep mechanisms has been accumulated. However, the function of sleep still remains elusive. The difficulty with unraveling sleep's function may arise from the lack of understanding of how the multitude of processes associated with waking and sleep-from gene expression and single neuron activity to the whole brain dynamics and behavior-functionally and mechanistically relate to each other. Therefore, novel conceptual frameworks, which integrate and take into account the variety of phenomena occurring during waking and sleep at different levels, will likely lead to advances in our understanding of the function of sleep, above and beyond what merely descriptive or correlative approaches can provide. One such framework, the synaptic homeostasis hypothesis, focuses on wake- and sleep-dependent changes in synaptic strength. The core claim of this hypothesis is that learning and experience during wakefulness are associated with a net increase in synaptic strength. In turn, the proposed function of sleep is to provide synaptic renormalization, which has important implications with respect to energy needs, intracranial space, metabolic supplies, and, importantly, enables further plastic changes. In this article we review the empirical evidence for this hypothesis, which was obtained at several levels-from gene expression and cellular excitability to structural synaptic modifications and behavioral outcomes. We conclude that although the mechanisms behind the proposed role of sleep in synaptic homeostasis are undoubtedly complex, this conceptual framework offers a unique opportunity to provide mechanistic and functional explanation for many previously disparate observations, and define future research strategies.

Is sleep essential for neural plasticity in humans, and how does it affect motor and cognitive recovery?

There is a general consensus that sleep is strictly linked to memory, learning, and, in general, to the mechanisms of neural plasticity, and that this link may directly affect recovery processes. In fact, a coherent pattern of empirical findings points to beneficial effect of sleep on learning and plastic processes, and changes in synaptic plasticity during wakefulness induce coherent modifications in EEG slow wave cortical topography during subsequent sleep. However, the specific nature of the relation between sleep and synaptic plasticity is not clear yet. We reported findings in line with two models conflicting with respect to the underlying mechanisms, that is, the “synaptic homeostasis hypothesis” and the “consolidation” hypothesis, and some recent results that may reconcile them. Independently from the specific mechanisms involved, sleep loss is associated with detrimental effects on plastic processes at a molecular and electrophysiological level. Finally, we reviewed growing evidence supporting the notion that plasticity-dependent recovery could be improved managing sleep quality, while monitoring EEG during sleep may help to explain how specific rehabilitative paradigms work. We conclude that a better understanding of the sleep-plasticity link could be crucial from a rehabilitative point of view.

Sleep and the single neuron: the role of global slow oscillations in individual cell rest

Sleep is universal in animals, but its specific functions remain elusive. We propose that sleep's primary function is to allow individual neurons to perform prophylactic cellular maintenance. Just as muscle cells must rest after strenuous exercise to prevent long-term damage, brain cells must rest after intense synaptic activity. We suggest that periods of reduced synaptic input ('off periods' or 'down states') are necessary for such maintenance. This in turn requires a state of globally synchronized neuronal activity, reduced sensory input and behavioural immobility - the well-known manifestations of sleep.