Current Topics in Medicinal Chemistry - Volume 11, Issue 19, 2011

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Sleep is clearly not only a whole-brain or global phenomenon, but can also be a local phenomenon. This accounts for the fact that the primary states of being (wakefulness, NREM sleep, and REM sleep) are not necessarily mutually exclusive, and components of these states may appear in various combinations, with fascinating clinical consequences. Examples include: sleep inertia, narcolepsy, sleep paralysis, lucid dreaming, REM sleep behavior disorder, sleepwalking, sleep terrors, out-of-body experiences, and reports of alien abduction. The incomplete declaration of state likewise has implications for consciousness - which also has fluid boundaries. Fluctuations in the degree of consciousness are likely explained by abnormalities of a “spatial and temporal binding rhythm” which normally results in a unified conscious experience. Dysfunctional binding may play a role in anesthetic states, autism, schizophrenia, and neurodegenerative disorders. Further study of the broad spectrum of dissociated states of sleep and wakefulness that are closely linked with states of consciousness and unconsciousness by basic neuroscientists, clinicians, and members of the legal profession will provide scientific, clinical and therapeutic insights, with forensic implications.

Reciprocal interactions between wakefulness and sleep substantially influence human brain function in both states of vigilance. On the one hand, there is evidence that regionally-specialized brain activity during wakefulness is modulated by the interaction between a local use-dependent buildup of homeostatic sleep pressure and circadian signals. On the other hand, brain activity during sleep, although mainly constrained by genuine sleep oscillations, shows wakedependent regionally-specific modulations, which are involved in the dissipation of local homeostatic sleep pressure and memory consolidation.

Waking neurobehavioral performance is temporally regulated by a sleep/wake homeostatic process and a circadian process in interaction with a time-on-task effect. Neurobehavioral impairment resulting from these factors is taskspecific, and characterized by performance variability. Several aspects of these phenomena are not well understood, and cannot be explained solely by a top-down (subcortically driven) view of sleep/wake and performance regulation. We present a bottom-up theory, where we postulate that task performance is degraded by local, use-dependent sleep in neuronal groups subserving cognitive processes associated with the task at hand. The theory offers explanations for the temporal dependence of neurobehavioral performance on time awake, time on task, and their interaction; for the effectiveness of task switching and rest breaks to overcome the time-on-task effect (but not the effects of sleep deprivation); for the taskspecific nature of neurobehavioral impairment; and for the stochastic property of performance variability.

In the present paper, we reviewed a large body of evidence, mainly from quantitative EEG studies of our laboratory, supporting the notion that sleep is a local and use-dependent process. Quantitative analyses of sleep EEG recorded from multiple cortical derivations clearly indicate that every sleep phenomenon, from sleep onset to the awakening, is strictly local in nature. Sleep onset first occurs in frontal areas, and a frontal predominance of low-frequency power persists in the first part of the night, when the homeostatic processes mainly occur, and then it vanishes. Upon awakening, we showed an asynchronous EEG activation of different cortical areas, the more anterior ones being the first to wake up. During extended periods of wakefulness, the increase of sleepiness-related low-EEG frequencies is again evident over the frontal derivations. Similarly, experimental manipulations of sleep length by total sleep deprivation, partial sleep curtailment or even selective slow-wave sleep deprivation lead to a slow-wave activity rebound localized especially on the anterior derivations. Thus, frontal areas are crucially involved in sleep homeostasis. According to the local use-dependent theory, this would derive from a higher sleep need of the frontal cortex, which in turn is due to its higher levels of activity during wakefulness. The fact that different brain regions can simultaneously exhibit different sleep intensities indicates that sleep is not a spatially global and uniform state, as hypothesized in the theory. We have also reviewed recent evidence of localized effects of learning and plasticity on EEG sleep measures. These studies provide crucial support to a key concept in the theory, the one claiming that local sleep characteristics should be use-dependent. Finally, we have reported data corroborating the notion that sleep is not necessarily present simultaneously in the entire brain. Our stereo-EEG recordings clearly indicate that sleep and wakefulness can co-exist in different areas, suggesting that vigilance states are not necessarily temporally discrete states. We conclude that understanding local variations in sleep propensity and depth, especially as a result of brain plasticity, may provide in the near future insightful hints into the fundamental functions of sleep.

In a recent series of experiments, we demonstrated that a visuomotor adaptation task, 12 hours of left arm immobilization, and rapid transcranial magnetic stimulation (rTMS) during waking can each induce local changes in the topography of electroencephalographic (EEG) slow wave activity (SWA) during subsequent non-rapid eye movement (NREM) sleep. However, the poor spatial resolution of EEG and the difficulty of relating scalp potentials to the activity of the underlying cortex limited the interpretation of these results. In order to better understand local cortical regulation of sleep, we used source modeling to show that plastic changes in specific cortical areas during waking produce correlated changes in SWA during sleep in those same areas. We found that implicit learning of a visuomotor adaptation task induced an increase in SWA in right premotor and sensorimotor cortices when compared to a motor control. These same areas have previously been shown to be selectively involved in the performance of this task. We also found that arm immobilization resulted in a decrease in SWA in sensorimotor cortex. Inducing cortical potentiation with repetitive transcranial magnetic stimulation (rTMS) caused an increase in SWA in the targeted area and a decrease in SWA in the contralateral cortex. Finally, we report the first evidence that these modulations in SWA may be related to the dynamics of individual slow waves. We conclude that there is a local, plasticity dependent component to sleep regulation and confirm previous inferences made from the scalp data.

Neural activity utilizes energy resources and requires replenishment of metabolites through vascular dilation. During wake, cortical neurons usually have depolarized membrane potentials and exhibit frequent spontaneous action potentials, requiring an increased metabolic delivery to activated tissue and causing blood vessels to dilate. Quiet sleep (QS) is characterized by alternating membrane potential between a depolarized and hyperpolarized state. The hyperpolarized state has a lower membrane potential and exhibits few action potentials, which may be less metabolically demanding. In order to investigate the relationship between evoked neural and metabolic responses across wake and sleep states, we combined electrical and optical imaging techniques. We implanted rats with screw electrodes to measure evoked response potentials (ERPs), and used a light emitting diode (LED) and photodiode to measure evoked changes in local hemodynamics based on hemoglobin absorption properties. During QS, hemodynamic changes were larger in amplitude compared to wake and rapid eye movement (REM) sleep. In this review, we explore the potential mechanisms for the larger hemodynamic changes. Wake periods may correspond to decreased vessel compliance as they expand to supply tissue with metabolites while sleep periods may decrease metabolic demand and allow vessels to relax and restore compliance.

The cellular substrates of sleep are incompletely described, but historically they have been thought to be neuronal. According to one view, sleep is produced by interactions between wake-promoting neurons, sleep-inducing neurons, and sleep-inducing substances released by neurons (e.g. adenosine)[1, 2]. Alternatively, sleep pressure may arise independently among subsets of neurons in a use-dependent fashion within the neocortex (i.e. ‘local’ sleep) [3, 4]. Implicit in both views is the notion that changes in neuronal activity (or plasticity) is the principle mechanism driving sleep homeostasis. Recent findings, however, suggest that the glial cells known as astrocytes may play critical roles in mammalian sleep.

This article starts with a brief review of the thalamocortical system architecture, which is composed of the projecting thalamic nuclei, the thalamic reticular nucleus, and the neocortex. Then we provide a description of the three states of vigilances followed by a detailed review of major brain rhythms present in the thalamocortical system, ranging from very slow to very fast oscillations. We provide descriptions of known mechanisms and hypotheses for unknown mechanisms for the generation of the different rhythms. The last part offers a detailed review on sleep slow oscillation describing its properties in the thalamocortical system, proposing a mechanism of generation of active states and a description of their propagation.

Sleep is homeostatically regulated in all species that have been carefully studied. In mammals and birds, the best characterized marker of sleep pressure is slow wave activity (SWA), defined as the electroencephalogram (EEG) power between 0.5 and 4 Hz during NREM sleep. SWA peaks at sleep onset and decreases with time spent asleep, and reflects the synchronous firing of cortical neurons coordinated by an underlying slow oscillation, the fundamental cellular phenomenon of NREM sleep. We have recently proposed the synaptic homeostasis hypothesis of sleep, which claims that an important function of sleep is to maintain synaptic balance. This hypothesis states that plastic processes during wake are biased towards synaptic potentiation, resulting in a net increase in synaptic strength in many brain circuits. Such increased synaptic weight would be unsustainable in the long run, due to increased demand for energy, space and supplies, and risk of synaptic saturation. Thus, according to the synaptic homeostasis hypothesis, sleep is important to renormalize synaptic strength to a baseline level that is sustainable and beneficial for memory and performance. There is strong evidence that the amplitude and slope of EEG slow waves is related to the number of neurons that enter an up state or a down state of the slow oscillation near-synchronously, and that synchrony is directly related to the number, strength, and efficacy of synaptic connections among them. Thus, the average synaptic strength (number or efficacy of synapses) reached in a given cortical area at the end of the major wake phase should be reflected by the level of SWA in the EEG at sleep onset. Moreover, according to the hypothesis, sleep SWA is not only a useful proxy of wake-related cortical synaptic strength, but could mediate the renormalization of neural circuits by favoring net synaptic depression, perhaps aided by low levels of norepinephrine, serotonin, and acetylcholine during NREM sleep. Here we briefly review human and animal studies showing that, consistent with this hypothesis, 1) in the adult cerebral cortex wake is associated with a net increase in synaptic strength, and sleep with a net decrease; and 2) SWA reflects not just prior “use” of specific neuronal circuits, but rather the occurrence of plastic changes, with increases in SWA after synaptic potentiation, and decreases in SWA after synaptic depression. We end by discussing current challenges to this hypothesis and future research directions.

Our recent report demonstrated that a small subset of GABAergic interneurons in the cerebral cortex of rodents expresses Fos protein, a marker for neuronal activity, during SWS [1]. The population of sleep-active neurons consists of strongly immunohistochemically-stained cells for the enzyme neuronal nitric oxide synthase (Type I cells). By virtue of their widespread localization within the cerebral cortex and their widespread projections to other cortical cell types, cortical neuronal nitric oxide synthase-positive neurons are positioned to play a central role in the local regulation of sleep waveforms within the cerebral cortex. Here, we review the possible functions of neuronal nitric oxide synthase and its diffusible gas product, nitric oxide, in regulating neuronal activity, synaptic plasticity and cerebral blood flow within the context of local sleep regulation in the cerebral cortex. We also summarize what is known, in addition to their expression of neuronal nitric oxide synthase, about the biochemical phenotype, synaptic connectivity and electrophysiological properties of this novel sleep-active population of cells. Finally, we raise some critical unanswered questions about the role of this population in local sleep regulation within the cerebral cortex and describe some experimental approaches that might be used to address those questions.

The logic and potential mechanisms for a new paradigm, the local use-dependent view of sleep as a distributed dynamic process in brain, are presented. This new paradigm is needed because the current dominant top-down imposition of sleep on the brain by sleep regulatory centers is either silent or is of inadequate explanatory value for many well-known sleep phenomena, e.g. sleep inertia. Two mechanistic falsifiable hypotheses linking sleep to cell use and the emergence of sleep/wake states are presented. These hypotheses are not mutually exclusive and both firmly link sleep to activitydependent epigenetic brain plasticity and the need to integrate and balance waking activity induced-network connectivity changes. The views presented herein emphasize the inseparability of sleep mechanisms from a connectivity sleep function.