Regional slow waves and spindles in human sleep

High-voltage, diffuse delta rhythms coincide with wakeful consciousness and complexity in Angelman syndrome

Abundant evidence from slow wave sleep, anesthesia, coma, and epileptic seizures links high-voltage, slow electroencephalogram (EEG) activity to loss of consciousness. This well-established correlation is challenged by the observation that children with Angelman syndrome (AS), while fully awake and displaying volitional behavior, display a hypersynchronous delta (1–4 Hz) frequency EEG phenotype typical of unconsciousness. Because the trough of the delta oscillation is associated with down-states in which cortical neurons are silenced, the presence of volitional behavior and wakefulness in AS amidst diffuse delta rhythms presents a paradox. Moreover, high-voltage, slow EEG activity is generally assumed to lack complexity, yet many theories view functional brain complexity as necessary for consciousness. Here, we use abnormal cortical dynamics in AS to assess whether EEG complexity may scale with the relative level of consciousness despite a background of hypersynchronous delta activity. As characterized by multiscale metrics, EEGs from 35 children with AS feature significantly greater complexity during wakefulness compared with sleep, even when comparing the most pathological segments of wakeful EEG to the segments of sleep EEG least likely to contain conscious mentation and when factoring out delta power differences across states. These findings (i) warn against reverse inferring an absence of consciousness solely on the basis of high-amplitude EEG delta oscillations, (ii) corroborate rare observations of preserved consciousness under hypersynchronization in other conditions, (iii) identify biomarkers of consciousness that have been validated under conditions of abnormal cortical dynamics, and (iv) lend credence to theories linking consciousness with complexity.

A mechanism for learning with sleep spindles

Spindles are ubiquitous oscillations during non-rapid eye movement (NREM) sleep. A growing body of evidence points to a possible link with learning and memory, and the underlying mechanisms are now starting to be unveiled. Specifically, spindles are associated with increased dendritic activity and high intracellular calcium levels, a situation favourable to plasticity, as well as with control of spiking output by feed-forward inhibition. During spindles, thalamocortical networks become unresponsive to inputs, thus potentially preventing interference between memory-related internal information processing and extrinsic signals. At the system level, spindles are co-modulated with other major NREM oscillations, including hippocampal sharp wave-ripples (SWRs) and neocortical slow waves, both previously shown to be associated with learning and memory. The sequential occurrence of reactivation at the time of SWRs followed by neuronal plasticity-promoting spindles is a possible mechanism to explain NREM sleep-dependent consolidation of memories. This article is part of the Theo Murphy meeting issue 'Memory reactivation: replaying events past, present and future'.

The (Un)Conscious Mouse as a Model for Human Brain Functions: Key Principles of Anesthesia and Their Impact on Translational Neuroimaging

In recent years, technical and procedural advances have brought functional magnetic resonance imaging (fMRI) to the field of murine neuroscience. Due to its unique capacity to measure functional activity non-invasively, across the entire brain, fMRI allows for the direct comparison of large-scale murine and human brain functions. This opens an avenue for bidirectional translational strategies to address fundamental questions ranging from neurological disorders to the nature of consciousness. The key challenges of murine fMRI are: (1) to generate and maintain functional brain states that approximate those of calm and relaxed human volunteers, while (2) preserving neurovascular coupling and physiological baseline conditions. Low-dose anesthetic protocols are commonly applied in murine functional brain studies to prevent stress and facilitate a calm and relaxed condition among animals. Yet, current mono-anesthesia has been shown to impair neural transmission and hemodynamic integrity. By linking the current state of murine electrophysiology, Ca2+ imaging and fMRI of anesthetic effects to findings from human studies, this systematic review proposes general principles to design, apply and monitor anesthetic protocols in a more sophisticated way. The further development of balanced multimodal anesthesia, combining two or more drugs with complementary modes of action helps to shape and maintain specific brain states and relevant aspects of murine physiology. Functional connectivity and its dynamic repertoire as assessed by fMRI can be used to make inferences about cortical states and provide additional information about whole-brain functional dynamics. Based on this, a simple and comprehensive functional neurosignature pattern can be determined for use in defining brain states and anesthetic depth in rest and in response to stimuli. Such a signature can be evaluated and shared between labs to indicate the brain state of a mouse during experiments, an important step toward translating findings across species.

Effectiveness of Visual vs. Acoustic Closed-Loop Stimulation on EEG Power Density during NREM Sleep in Humans

The aim of the study was to investigate whether visual stimuli have the same potency to increase electroencephalography (EEG) delta wave power density during non-rapid eye movement (NREM) sleep as do auditory stimuli that may be practical in the treatment of some sleep disturbances. Nine healthy subjects underwent two polysomnography sessions-adaptation and experimental-with EEG electrodes positioned at Fz-Cz. Individually adjusted auditory (pink noise) and visual (light-emitting diode (LED) red light) paired 50-ms signals were automatically presented via headphones/eye mask during NREM sleep, shortly (0.75-0.90 s) after the EEG wave descended below a preset amplitude threshold (closed-loop in-phase stimulation). The alternately repeated 30-s epochs with stimuli of a given modality (light, sound, or light and sound simultaneously) were preceded and followed by 30-s epochs without stimulation. The number of artifact-free 1.5-min cycles taken in the analysis was such that the cycles with stimuli of different modalities were matched by number of stimuli presented. Acoustic stimuli caused an increase (p < 0.01) of EEG power density in the frequency band 0.5-3.0 Hz (slow waves); the values reverted to baseline at post-stimuli epochs. Light stimuli did not influence EEG slow wave power density (p > 0.01) and did not add to the acoustic stimuli effects. Thus, dim red light presented in a closed-loop in-phase fashion did not influence EEG power density during nocturnal sleep.

Phase-based coordination of hippocampal and neocortical oscillations during human sleep

During sleep, new memories undergo a gradual transfer from hippocampal (HPC) to neocortical (NC) sites. Precisely timed neural oscillations are thought to mediate this sleep-dependent memory consolidation, but exactly how sleep oscillations instantiate the HPC-NC dialog remains elusive. Employing overnight invasive electroencephalography in ten neurosurgical patients, we identified three broad classes of phase-based communication between HPC and lateral temporal NC. First, we observed interregional phase synchrony for non-rapid eye movement (NREM) spindles, and N2 and rapid eye movement (REM) theta activity. Second, we found asymmetrical N3 cross-frequency phase-amplitude coupling between HPC slow oscillations (SOs) and NC activity spanning the delta to high-gamma/ripple bands, but not in the opposite direction. Lastly, N2 theta and NREM spindle synchrony were themselves modulated by HPC SOs. These forms of interregional communication emphasize the role of HPC SOs in the HPC-NC dialog, and may offer a physiological basis for the sleep-dependent reorganization of mnemonic content.

Establishing the objective sleep phenotype in hypersomnolence disorder with and without comorbid major depression

STUDY OBJECTIVES

To clarify whether hypersomnolence disorder is associated with a specific sleep phenotype and altered neurophysiological function in persons with and without hypersomnolence disorder and major depressive disorder (MDD).

METHODS

Eighty-three unmedicated persons with and without hypersomnolence disorder and/or MDD underwent ad libitum high-density EEG polysomnography. Clinical and sleep architecture variables were compared between groups. Topographic patterns of slow-wave activity (SWA) relative to healthy controls were compared, with correlations between topographic SWA and daytime sleepiness assessed. Reductions in SWA in hypersomnolence disorder were mapped to specific cortical areas using source localization.

RESULTS

Regardless of the presence or absence of comorbid MDD, persons with hypersomnolence disorder had increased sleep duration relative to both controls and persons with MDD without hypersomnolence. Participants with hypersomnolence disorder also demonstrated reduced bilateral centroparietal low-frequency activity during nonrapid eye movement sleep relative to controls, a pattern not observed in persons with MDD but without hypersomnolence. SWA in these regions was negatively correlated with subjective measures of daytime sleepiness. Source localization demonstrated reductions in SWA in the supramarginal gyrus, somatosensory, and transverse temporal cortex in participants with hypersomnolence disorder.

CONCLUSIONS

Hypersomnolence disorder is characterized by increased sleep duration with normal sleep continuity, regardless of the presence or absence of comorbid depression. Reduced local SWA may be a specific neurophysiological finding in hypersomnolence disorder. Further research is warranted to elucidate the mechanisms through which these cortical changes are related to clinical complaints of daytime sleepiness.

Sleep-wake regulation and the hallmarks of the pathogenesis of Alzheimer's disease

While efficient treatments for Alzheimer's disease (AD) remain elusive, a growing body of research has highlighted sleep-wake regulation as a potential modifiable factor to delay disease progression. Evidence accumulated in recent years is pointing toward a tight link between sleep-wake disruption and the three main hallmarks of the pathogenesis of AD, i.e. abnormal amyloid-beta (Aβ) and tau proteins accumulation, and neurodegeneration. However, all three hallmarks are rarely considered together in the same study. In this review, we gather and discuss findings in favor of an association between sleep-wake disruption and each AD hallmark in animal models and in humans, with a focus on the preclinical stages of the disease. We emphasize that these relationships are likely bidirectional for each of these hallmarks. Altogether, current findings provide strong support for considering sleep-wake disruption as a true risk factor in the early unfolding of AD, but more research integrating recent technical advances is needed, particularly with respect to tau protein and neurodegeneration. Interventional longitudinal studies among cognitively healthy older individuals should assess the practical use of improving sleep-wake regulation to slow down the progression of AD pathogenesis.

Cortical zeta-inhibitory peptide injection reduces local sleep need

Local sleep need within cortical circuits exhibits extensive interregional variability and appears to increase following learning during preceding waking. Although the biological mechanisms responsible for generating sleep need are unclear, this local variability could arise as a consequence of wake-dependent synaptic plasticity. To test whether cortical synaptic strength is a proximate driver of sleep homeostasis, we developed a novel experimental approach to alter local sleep need. One hour prior to light onset, we injected zeta-inhibitory peptide (ZIP), a pharmacological antagonist of protein kinase Mζ, which can produce pronounced synaptic depotentiation, into the right motor cortex of freely behaving rats. When compared with saline control, ZIP selectively reduced slow-wave activity (SWA; the best electrophysiological marker of sleep need) within the injected motor cortex without affecting SWA in a distal cortical site. This local reduction in SWA was associated with a significant reduction in the slope and amplitude of individual slow waves. Local ZIP injection did not significantly alter the amount of time spent in each behavioral state, locomotor activity, or EEG/LFP power during waking or REM sleep. Thus, local ZIP injection selectively produced a local reduction in sleep need; synaptic strength, therefore, may play a causal role in generating local homeostatic sleep need within the cortex.

Multimodal assessment shows misalignment of structural and functional thalamocortical connectivity in children and adolescents born very preterm

Thalamocortical connections are altered following very preterm birth but it is unknown whether structural and functional alterations are linked and how they contribute to neurodevelopmental deficits. We used a multimodal approach in 27 very preterm and 35 term-born children and adolescents aged 10-16 years: Structural thalamocortical connectivity was quantified with two measures derived from probabilistic tractography of diffusion tensor data, namely the volume of thalamic segments with cortical connections and mean fractional anisotropy (FA) within the respective segments. High-density sleep EEG was recorded and sleep spindles were identified at each electrode. Sleep spindle density and integrated spindle activity (ISA) were calculated to quantify functional thalamocortical connectivity. In term-born participants, the volume of the global thalamic segment with cortical connections was strongly related to sleep spindles across the entire head (mean r ​= ​.53 ​± .10; range ​= ​0.35 to 0.78). Regionally, the volume of the thalamic segment connecting to frontal brain regions correlated with sleep spindle density in two clusters of electrodes over fronto-temporal brain regions (.42 ​± .06; 0.35 to 0.51 and 0.43 ​± .08; 0.35 to 0.62) and the volume of the thalamic segment connecting to parietal brain regions correlated with sleep spindle density over parietal brain regions (mean r ​= ​.43 ​± .07; 0.35 to 0.61). In very preterm participants, the volume of the thalamic segments was not associated with sleep spindles. In the very preterm group, mean FA within the global thalamic segment was negatively correlated with ISA over a cluster of frontal and temporo-occipital brain regions (mean r ​= ​-.53 ​± .07; -.41 to -.72). No association between mean FA and ISA was found in the term-born group. With this multimodal study protocol, we identified a potential misalignment between structural and functional thalamocortical connectivity in children and adolescents born very preterm. Eventually, this may shed further light on the neuronal mechanisms underlying neurodevelopmental sequelae of preterm birth.

A sleep spindle framework for motor memory consolidation

Sleep spindle activity has repeatedly been found to contribute to brain plasticity and consolidation of both declarative and procedural memories. Here we propose a framework for motor memory consolidation that outlines the essential contribution of the hierarchical and multi-scale periodicity of spindle activity, as well as of the synchronization and interaction of brain oscillations during this sleep-dependent process. We posit that the clustering of sleep spindles in 'trains', together with the temporally organized alternation between spindles and associated refractory periods, is critical for efficient reprocessing and consolidation of motor memories. We further argue that the long-term retention of procedural memories relies on the synchronized (functional connectivity) local reprocessing of new information across segregated, but inter-connected brain regions that are involved in the initial learning process. Finally, we propose that oscillatory synchrony in the spindle frequency band may reflect the cross-structural reactivation, reorganization and consolidation of motor, and potentially declarative, memory traces within broader subcortical-cortical networks during sleep. This article is part of the Theo Murphy meeting issue 'Memory reactivation: replaying events past, present and future'.

Neuromodulation of Brain State and Behavior

Neural activity and behavior are both notoriously variable, with responses differing widely between repeated presentation of identical stimuli or trials. Recent results in humans and animals reveal that these variations are not random in their nature, but may in fact be due in large part to rapid shifts in neural, cognitive, and behavioral states. Here we review recent advances in the understanding of rapid variations in the waking state, how variations are generated, and how they modulate neural and behavioral responses in both mice and humans. We propose that the brain has an identifiable set of states through which it wanders continuously in a nonrandom fashion, owing to the activity of both ascending modulatory and fast-acting corticocortical and subcortical-cortical neural pathways. These state variations provide the backdrop upon which the brain operates, and understanding them is critical to making progress in revealing the neural mechanisms underlying cognition and behavior.

Memory quality modulates the effect of aging on memory consolidation during sleep: Reduced maintenance but intact gain

Successful consolidation of associative memories relies on the coordinated interplay of slow oscillations and sleep spindles during non-rapid eye movement (NREM) sleep. This enables the transfer of labile information from the hippocampus to permanent memory stores in the neocortex. During senescence, the decline of the structural and functional integrity of the hippocampus and neocortical regions is paralleled by changes of the physiological events that stabilize and enhance associative memories during NREM sleep. However, the currently available evidence is inconclusive as to whether and under which circumstances memory consolidation is impacted during aging. To approach this question, 30 younger adults (19-28 years) and 36 older adults (63-74 years) completed a memory task based on scene-word associations. By tracing the encoding quality of participants' individual memory associations, we demonstrate that previous learning determines the extent of age-related impairments in memory consolidation. Specifically, the detrimental effects of aging on memory maintenance were greatest for mnemonic contents of intermediate encoding quality, whereas memory gain of poorly encoded memories did not differ by age. Ambulatory polysomnography (PSG) and structural magnetic resonance imaging (MRI) data were acquired to extract potential predictors of memory consolidation from each participant's NREM sleep physiology and brain structure. Partial Least Squares Correlation was used to identify profiles of interdependent alterations in sleep physiology and brain structure that are characteristic for increasing age. Across age groups, both the 'aged' sleep profile, defined by decreased slow-wave activity (0.5-4.5 ​Hz), and a reduced presence of slow oscillations (0.5-1 ​Hz), slow, and fast spindles (9-12.5 ​Hz; 12.5-16 ​Hz), as well as the 'aged' brain structure profile, characterized by gray matter reductions in the medial prefrontal cortex, thalamus, entorhinal cortex, and hippocampus, were associated with reduced memory maintenance. However, inter-individual differences in neither sleep nor structural brain integrity alone qualified as the driving force behind age differences in sleep-dependent consolidation in the present study. Our results underscore the need for novel and age-fair analytic tools to provide a mechanistic understanding of age differences in memory consolidation.

Ripples Have Distinct Spectral Properties and Phase-Amplitude Coupling With Slow Waves, but Indistinct Unit Firing, in Human Epileptogenic Hippocampus

Ripple oscillations (80-200 Hz) in the normal hippocampus are involved in memory consolidation during rest and sleep. In the epileptic brain, increased ripple and fast ripple (200-600 Hz) rates serve as a biomarker of epileptogenic brain. We report that both ripples and fast ripples exhibit a preferred phase angle of coupling with the trough-peak (or On-Off) state transition of the sleep slow wave in the hippocampal seizure onset zone (SOZ). Ripples on slow waves in the hippocampal SOZ also had a lower power, greater spectral frequency, and shorter duration than those in the non-SOZ. Slow waves in the mesial temporal lobe modulated the baseline firing rate of excitatory neurons, but did not significantly influence the increased firing rate associated with ripples. In summary, pathological ripples and fast ripples occur preferentially during the On-Off state transition of the slow wave in the epileptogenic hippocampus, and ripples do not require the increased recruitment of excitatory neurons.

Sleep and ageing: from human studies to rodent models

Sleep duration and lifespan vary greatly across Animalia. Human studies have demonstrated that ageing reduces the ability to obtain deep restorative sleep, and this may play a causative role in the development of age-related neurodegenerative disorders. Animal models are widely used in sleep and ageing studies. Importantly, in contrast to human studies, evidence from laboratory rodents suggests that sleep duration is increased with ageing, while evidence for reduced sleep intensity and consolidation is inconsistent. Here we discuss two possible explanations for these species differences. First, methodological differences between studies in humans and laboratory rodents may prevent straightforward comparison. Second, the role of ecological factors, which have a profound influence on both ageing and sleep, must be taken into account. We propose that the dynamics of sleep across the lifespan reflect both age-dependent changes in the neurobiological substrates of sleep as well as the capacity to adapt to the environment.

Sleeping with Hippocampal Damage

The hippocampus plays a critical role in sleep-related memory processes [1-3], but it is unclear which specific sleep features are dependent upon this brain structure. The examination of sleep physiology in patients with focal bilateral hippocampal damage and amnesia could supply important evidence regarding these links. However, there is a dearth of such studies, despite these patients providing compelling insights into awake cognition [4, 5]. Here, we sought to identify the contribution of the hippocampus to the sleep phenotype by characterizing sleep via comprehensive qualitative and quantitative analyses in memory-impaired patients with selective bilateral hippocampal damage and matched control participants using in-home polysomnography on 4 nights. We found that, compared to control participants, patients had significantly reduced slow-wave sleep-likely due to decreased density of slow waves-as well as slow-wave activity. In contrast, slow and fast spindles were indistinguishable from those of control participants. Moreover, patients expressed slow oscillations (SOs), and SO-fast spindle coupling was observed. However, on closer scrutiny, we noted that the timing of spindles within the SO cycle was delayed in the patients. The shift of patients' spindles into the later phase of the up-state within the SO cycle may indicate a mismatch in timing across the SO-spindle-ripple events that are associated with memory consolidation [6, 7]. The substantial effect of selective bilateral hippocampal damage on large-scale oscillatory activity in the cortex suggests that, as with awake cognition, the hippocampus plays a significant role in sleep physiology, which may, in turn, be necessary for efficacious episodic memory.

Divergent neuronal activity patterns in the avian hippocampus and nidopallium

Sleep-related brain activity occurring during non-rapid eye-movement (NREM) sleep is proposed to play a role in processing information acquired during wakefulness. During mammalian NREM sleep, the transfer of information from the hippocampus to the neocortex is thought to be mediated by neocortical slow-waves and their interaction with thalamocortical spindles and hippocampal sharp-wave ripples (SWRs). In birds, brain regions composed of pallial neurons homologous to neocortical (pallial) neurons also generate slow-waves during NREM sleep, but little is known about sleep-related activity in the hippocampus and its possible relationship to activity in other pallial regions. We recorded local field potentials (LFP) and analogue multiunit activity (AMUA) using a 64-channel silicon multi-electrode probe simultaneously inserted into the hippocampus and medial part of the nidopallium (i.e., caudal medial nidopallium; NCM) or separately into the caudolateral nidopallium (NCL) of adult female zebra finches (Taeniopygia guttata) anesthetized with isoflurane, an anesthetic known to induce NREM sleep-like slow-waves. We show that slow-waves in NCM and NCL propagate as waves of neuronal activity. In contrast, the hippocampus does not show slow-waves, nor sharp-wave ripples, but instead displays localized gamma activity. In conclusion, neuronal activity in the avian hippocampus differs from that described in mammals during NREM sleep, suggesting that hippocampal memories are processed differently during sleep in birds and mammals.

Spatio-temporal properties of sleep slow waves and implications for development

Objective sleep quality can be measured by electroencephalography (EEG), a non-invasive technique to quantify electrical activity generated by the brain. With EEG, sleep depth is measured by appearance and an increase in slow wave activity (scalp-SWA). EEG slow waves (scalp-SW) are the manifestation of underlying synchronous membrane potential transitions between silent (DOWN) and active (UP) states. This bistable periodic rhythm is defined as slow oscillation (SO). During its "silent state" cortical neurons are hyperpolarized and appear inactive, while during its "active state" cortical neurons are depolarized, fire spikes and exhibit continuous synaptic activity, excitatory and inhibitory. In adults, data from high-density EEG revealed that scalp-SW propagate across the cortical mantle in complex patterns. However, scalp-SW propagation undergoes modifications across development. We present novel data from children, indicating that scalp-SW originate centro-parietally, and emerge more frontally by adolescence. Based on the concept that SO and SW could actively modify neuronal connectivity, we discuss whether they fulfill a key purpose in brain development by actively conveying modifications of the maturing brain.

Stimulation Augments Spike Sequence Replay and Memory Consolidation during Slow-Wave Sleep

Newly acquired memory traces are spontaneously reactivated during slow-wave sleep (SWS), leading to the consolidation of recent memories. Empirical studies found that sensory stimulation during SWS can selectively enhance memory consolidation with the effect depending on the phase of stimulation. In this new study, we aimed to understand the mechanisms behind the role of sensory stimulation on memory consolidation using computational models implementing effects of neuromodulators to simulate transitions between awake and SWS sleep, and synaptic plasticity to allow the change of synaptic connections due to the training in awake or replay during sleep. We found that when closed-loop stimulation was applied during the Down states of sleep slow oscillation, particularly right before the transition from Down to Up state, it significantly affected the spatiotemporal pattern of the slow waves and maximized memory replay. In contrast, when the stimulation was presented during the Up states, it did not have a significant impact on the slow waves or memory performance after sleep. For multiple memories trained in awake, presenting stimulation cues associated with specific memory trace could selectively augment replay and enhance consolidation of that memory and interfere with consolidation of the others (particularly weak) memories. Our study proposes a synaptic-level mechanism of how memory consolidation is affected by sensory stimulation during sleep.SIGNIFICANCE STATEMENT Stimulation, such as training-associated cues or auditory stimulation, during sleep can augment consolidation of the newly encoded memories. In this study, we used a computational model of the thalamocortical system to describe the mechanisms behind the role of stimulation in memory consolidation during slow-wave sleep. Our study suggests that stimulation preferentially strengthens memory traces when delivered at a specific phase of the slow oscillation, just before the Down to Up state transition when it makes the largest impact on the spatiotemporal pattern of sleep slow waves. In the presence of multiple memories, presenting sensory cues during sleep could selectively strengthen selected memories. Our study proposes a synaptic-level mechanism of how memory consolidation is affected by sensory stimulation during sleep.

Understanding the interplay of sleep and aging: Methodological challenges

In quest of new avenues to explain, predict, and treat pathophysiological conditions during aging, research on sleep and aging has flourished. Despite the great scientific potential to pinpoint mechanistic pathways between sleep, aging, and pathology, only little attention has been paid to the suitability of analytic procedures applied to study these interrelations. On the basis of electrophysiological sleep and structural brain data of healthy younger and older adults, we identify, illustrate, and resolve methodological core challenges in the study of sleep and aging. We demonstrate potential biases in common analytic approaches when applied to older populations. We argue that uncovering age-dependent alterations in the physiology of sleep requires the development of adjusted and individualized analytic procedures that filter out age-independent interindividual differences. Age-adapted methodological approaches are thus required to foster the development of valid and reliable biomarkers of age-associated cognitive pathologies.

Infraslow coordination of slow wave activity through altered neuronal synchrony

Slow wave activity (SWA; the EEG power between 0.5 and 4 Hz during non-rapid eye movement sleep [NREM]) is the best electrophysiological marker of sleep need; SWA dissipates across the night and increases following sleep deprivation. In addition to these well-documented homeostatic SWA trends, SWA exhibits extensive variability across shorter timescales (seconds to minutes) and between local cortical regions. The physiological underpinnings of SWA variability, however, remain poorly characterized. In male Sprague-Dawley rats, we observed that SWA exhibits pronounced infraslow fluctuations (~40- to 120-s periods) that are coordinated across disparate cortical locations. Peaks in SWA across infraslow cycles were associated with increased slope, amplitude, and duration of individual slow waves and a reduction in the total number of waves and proportion of multipeak waves. Using a freely available data set comprised of extracellular unit recordings during consolidated NREM episodes in male Long-Evans rats, we further show that infraslow SWA does not appear to arise as a consequence of firing rate modulation of putative excitatory or inhibitory neurons. Instead, infraslow SWA was associated with alterations in neuronal synchrony surrounding "On"/"Off" periods and changes in the number and duration of "Off" periods. Collectively, these data provide a mechanism by which SWA can be coordinated across disparate cortical locations and thereby connect local and global expression of this patterned neuronal activity. In doing so, infraslow SWA may contribute to the regulation of cortical circuits during sleep and thereby play a critical role in sleep function.

Intra-"cortical" activity during avian non-REM and REM sleep: variant and invariant traits between birds and mammals

Several mammalian-based theories propose that the varying patterns of neuronal activity occurring in wakefulness and sleep reflect different modes of information processing. Neocortical slow-waves, hippocampal sharp-wave ripples, and thalamocortical spindles occurring during mammalian non-rapid eye-movement (NREM) sleep are proposed to play a role in systems-level memory consolidation. Birds show similar NREM and REM (rapid eye-movement) sleep stages to mammals; however, it is unclear whether all neurophysiological rhythms implicated in mammalian memory consolidation are also present. Moreover, it is unknown whether the propagation of slow-waves described in the mammalian neocortex occurs in the avian "cortex" during natural NREM sleep. We used a 32-channel silicon probe connected to a transmitter to make intracerebral recordings of the visual hyperpallium and thalamus in naturally sleeping pigeons (Columba livia). As in the mammalian neocortex, slow-waves during NREM sleep propagated through the hyperpallium. Propagation primarily occurred in the thalamic input layers of the hyperpallium, regions that also showed the greatest slow-wave activity (SWA). Spindles were not detected in both the visual hyperpallium, including regions receiving thalamic input, and thalamus, using a recording method that readily detects spindles in mammals. Interestingly, during REM sleep fast gamma bursts in the hyperpallium (when present) were restricted to the thalamic input layers. In addition, unlike mice, the decrease in SWA from NREM to REM sleep was the greatest in these layers. Taken together, these variant and invariant neurophysiological aspects of avian and mammalian sleep suggest that there may be associated mechanistic and functional similarities and differences between avian and mammalian sleep.

Sleep Spindles: Mechanisms and Functions

Sleep spindles are burstlike signals in the electroencephalogram (EEG) of the sleeping mammalian brain and electrical surface correlates of neuronal oscillations in thalamus. As one of the most inheritable sleep EEG signatures, sleep spindles probably reflect the strength and malleability of thalamocortical circuits that underlie individual cognitive profiles. We review the characteristics, organization, regulation, and origins of sleep spindles and their implication in non-rapid-eye-movement sleep (NREMS) and its functions, focusing on human and rodent. Spatially, sleep spindle-related neuronal activity appears on scales ranging from small thalamic circuits to functional cortical areas, and generates a cortical state favoring intracortical plasticity while limiting cortical output. Temporally, sleep spindles are discrete events, part of a continuous power band, and elements grouped on an infraslow time scale over which NREMS alternates between continuity and fragility. We synthesize diverse and seemingly unlinked functions of sleep spindles for sleep architecture, sensory processing, synaptic plasticity, memory formation, and cognitive abilities into a unifying sleep spindle concept, according to which sleep spindles 1) generate neural conditions of large-scale functional connectivity and plasticity that outlast their appearance as discrete EEG events, 2) appear preferentially in thalamic circuits engaged in learning and attention-based experience during wakefulness, and 3) enable a selective reactivation and routing of wake-instated neuronal traces between brain areas such as hippocampus and cortex. Their fine spatiotemporal organization reflects NREMS as a physiological state coordinated over brain and body and may indicate, if not anticipate and ultimately differentiate, pathologies in sleep and neurodevelopmental, -degenerative, and -psychiatric conditions.

Evidence for Sleep in Sharks and Rays: Behavioural, Physiological, and Evolutionary Considerations

Sleep is widespread across the animal kingdom. However, most comparative sleep data exist for terrestrial vertebrates, with much less known about sleep in amphibians, bony fishes, and invertebrates. There is an absence of knowledge on sleep in cartilaginous fishes. Sharks and rays are amongst the earliest vertebrates, and may hold clues to the evolutionary history of sleep and sleep states found in more derived animals, such as mammals and birds. Here, we review the literature concerning activity patterns, sleep behaviour, and electrophysiological evidence for sleep in cartilaginous (and bony) fishes following an exhaustive literature search that found more than 80 relevant studies in laboratory and field environments. Evidence for sleep in sharks and rays that respire without swimming is preliminary; evidence for sleep in continuously swimming fishes is currently absent. We discuss ways in which the latter group might sleep concurrent with sustained movement, and conclude with suggestions for future studies in order to provide more comprehensive data on when, how, and why sharks and rays sleep.

Improved identification and differentiation from epileptiform activity of human hippocampal sharp wave ripples during NREM sleep

In rodents, pyramidal cell firing patterns from waking may be replayed in nonrapid eye movement sleep (NREM) sleep during hippocampal sharp wave ripples (HC-SWR). In humans, HC-SWR have only been recorded with electrodes implanted to localize epileptogenicity. Here, we characterize human HC-SWR with rigorous rejection of epileptiform activity, requiring multiple oscillations and coordinated sharp waves. We demonstrated typical SWR in those rare HC recordings which lack interictal epileptiform spikes (IIS) and with no or minimal seizure involvement. These HC-SWR have a similar rate (~12 min^-1 on average, variable across NREM stages and anterior/posterior HC) and apparent intra-HC topography (ripple maximum in putative stratum pyramidale, slow wave in radiatum) as rodents, though with lower frequency (~85 Hz compared to ~140 Hz in rodents). Similar SWR are found in HC with IIS, but no significant seizure involvement. These SWR were modulated by behavior, being largely absent (<2 min^-1 ) except during NREM sleep in both Stage 2 (~9 min^-1 ) and Stage 3 (~15 min^-1 ), distinguishing them from IIS. This study quantifies the basic characteristics of a strictly selected sample of SWR recorded in relatively healthy human hippocampi.

Analysis Pipeline for Extracting Features of Cortical Slow Oscillations

Cortical slow oscillations (≲1 Hz) are an emergent property of the cortical network that integrate connectivity and physiological features. This rhythm, highly revealing of the characteristics of the underlying dynamics, is a hallmark of low complexity brain states like sleep, and represents a default activity pattern. Here, we present a methodological approach for quantifying the spatial and temporal properties of this emergent activity. We improved and enriched a robust analysis procedure that has already been successfully applied to both in vitro and in vivo data acquisitions. We tested the new tools of the methodology by analyzing the electrocorticography (ECoG) traces recorded from a custom 32-channel multi-electrode array in wild-type isoflurane-anesthetized mice. The enhanced analysis pipeline, named SWAP (Slow Wave Analysis Pipeline), detects Up and Down states, enables the characterization of the spatial dependency of their statistical properties, and supports the comparison of different subjects. The SWAP is implemented in a data-independent way, allowing its application to other data sets (acquired from different subjects, or with different recording tools), as well as to the outcome of numerical simulations. By using the SWAP, we report statistically significant differences in the observed slow oscillations (SO) across cortical areas and cortical sites. Computing cortical maps by interpolating the features of SO acquired at the electrode positions, we give evidence of gradients at the global scale along an oblique axis directed from fronto-lateral toward occipito-medial regions, further highlighting some heterogeneity within cortical areas. The results obtained using the SWAP will be essential for producing data-driven brain simulations. A spatial characterization of slow oscillations will also trigger a discussion on the role of, and the interplay between, the different regions in the cortex, improving our understanding of the mechanisms of generation and propagation of delta rhythms and, more generally, of cortical properties.

Delta oscillations phase limit neural activity during sevoflurane anesthesia

Understanding anesthetic mechanisms with the goal of producing anesthetic states with limited systemic side effects is a major objective of neuroscience research in anesthesiology. Coherent frontal alpha oscillations have been postulated as a mechanism of sevoflurane general anesthesia. This postulate remains unproven. Therefore, we performed a single-site, randomized, cross-over, high-density electroencephalogram study of sevoflurane and sevoflurane-plus-ketamine general anesthesia in 12 healthy subjects. Data were analyzed with multitaper spectral, global coherence, cross-frequency coupling, and phase-dependent methods. Our results suggest that coherent alpha oscillations are not fundamental for maintaining sevoflurane general anesthesia. Taken together, our results suggest that subanesthetic and general anesthetic sevoflurane brain states emerge from impaired information processing instantiated by a delta-higher frequency phase-amplitude coupling syntax. These results provide fundamental new insights into the neural circuit mechanisms of sevoflurane anesthesia and suggest that anesthetic states may be produced by extracranial perturbations that cause delta-higher frequency phase-amplitude interactions.

Sleep modulates effective connectivity: A study using intracranial stimulation and recording

OBJECTIVE

Sleep is an active process with an important role in memory. Epilepsy patients often display a disturbed sleep architecture, with consequences on cognition. We aimed to investigate the effect of sleep on cortical networks' organization.

METHODS

We analyzed cortico-cortical evoked responses elicited by single pulse electrical stimulation (SPES) using intracranial depth electrodes in 25 patients with drug-resistant focal epilepsy explored using stereo-EEG. We applied the SPES protocol during wakefulness and NREM - N2 sleep. We analyzed 31,710 significant responses elicited by 799 stimulations covering most brain structures, epileptogenic or non-epileptogenic. We analyzed effective connectivity between structures using a graph-theory approach.

RESULTS

Sleep increases excitability in the brain, regardless of epileptogenicity. Local and distant connections are differently modulated by sleep, depending on the tissue epileptogenicity. In non-epileptogenic areas, frontal lobe connectivity is enhanced during sleep. There is increased connectivity between the hippocampus and temporal neocortex, while perisylvian structures are disconnected from the temporal lobe. In epileptogenic areas, we found a clear interhemispheric difference, with decreased connectivity in the right hemisphere during sleep.

CONCLUSIONS

Sleep modulates brain excitability and reconfigures functional brain networks, depending on tissue epileptogenicity.

SIGNIFICANCE

We found specific patterns of information flow during sleep in physiologic and pathologic structures, with possible implications for cognition.

Distributed slow-wave dynamics during sleep predict memory consolidation and its impairment in schizophrenia

The slow waves (SW) of non-rapid eye movement (NREM) sleep reflect neocortical components of network activity during sleep-dependent information processing; their disruption may therefore impair memory consolidation. Here, we quantify sleep-dependent consolidation of motor sequence memory, alongside sleep EEG-derived SW properties and synchronisation, and SW–spindle coupling in 21 patients suffering from schizophrenia and 19 healthy volunteers. Impaired memory consolidation in patients culminated in an overnight improvement in motor sequence task performance of only 1.6%, compared with 15% in controls. During sleep after learning, SW amplitudes and densities were comparable in healthy controls and patients. However, healthy controls showed a significant 45% increase in frontal-to-occipital SW coherence during sleep after motor learning in comparison with a baseline night (baseline: 0.22 ± 0.05, learning: 0.32 ± 0.05); patient EEG failed to show this increase (baseline: 0.22 ± 0.04, learning: 0.19 ± 0.04). The experience-dependent nesting of spindles in SW was similarly disrupted in patients: frontal-to-occipital SW–spindle phase-amplitude coupling (PAC) significantly increased after learning in healthy controls (modulation index baseline: 0.17 ± 0.02, learning: 0.22 ± 0.02) but not in patients (baseline: 0.13 ± 0.02, learning: 0.14 ± 0.02). Partial least-squares regression modelling of coherence and PAC data from all electrode pairs confirmed distributed SW coherence and SW–spindle coordination as superior predictors of overnight memory consolidation in healthy controls but not in patients. Quantifying the full repertoire of NREM EEG oscillations and their long-range covariance therefore presents learning-dependent changes in distributed SW and spindle coordination as fingerprints of impaired cognition in schizophrenia.

Interictal epileptiform discharges shape large-scale intercortical communication

Dynamic interactions between remote but functionally specialized brain regions enable complex information processing. This intercortical communication is disrupted in the neural networks of patients with focal epilepsy, and epileptic activity can exert widespread effects within the brain. Using large-scale human intracranial electroencephalography recordings, we show that interictal epileptiform discharges (IEDs) are significantly coupled with spindles in discrete, individualized brain regions outside of the epileptic network. We found that a substantial proportion of these localized spindles travel across the cortical surface. Brain regions that participate in this IED-driven oscillatory coupling express spindles that have a broader spatial extent and higher tendency to propagate than spindles occurring in uncoupled regions. These altered spatiotemporal oscillatory properties identify areas that are shaped by epileptic activity independent of IED or seizure detection. Our findings suggest that IED-spindle coupling may be an important mechanism of interictal global network dysfunction that could be targeted to prevent disruption of normal neural activity.

Dynamic Metabolic Changes in the Human Thalamus at the Transition From Waking to Sleep - Insights From Simultaneous Functional MR Spectroscopy and Polysomnography

An important contribution of the thalamus to the transition from wakefulness to sleep is a consistent finding in animal studies. In humans, only little is currently known about the specific role of the thalamus in regulating wake-sleep transitions. Although changes in thalamic blood flow and activity have been reported, the underlying molecular mechanisms have not been investigated. Knowledge about neurotransmitter changes at the wake-to-sleep transition would be indispensable for a better translation of basic animal research findings to humans. Here, we start to fill this important scientific gap. More specifically, we benefit from recent advances in magnetic resonance (MR) spectroscopy, which allow for the non-invasive, local-specific and high-quality detection of naturally occurring metabolite changes in the human brain. We demonstrate in nine young adults able to produce consolidated sleep in the MR spectroscopy scanner, a specific decrease in thalamic glutamate concentration from wakefulness to stage N2 sleep. The magnitude of this decrease was highly correlated with individual N2 sleep duration. When five participants of the original experiment were kept awake in a separate control condition, no decrease in thalamic glutamate levels occurred. The study highlights for the first time in humans that dynamic changes in distinct brain metabolites can be reliably detected at the transition from waking to sleep. The reported methodology to simultaneously acquire functional MR spectroscopy data and neurophysiological signals offers great potential for investigating the molecular mechanisms underlying the transition between and the maintenance of sleep and wake states in humans.

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.

Generating Brain Waves, the Power of Astrocytes

Synchronization of neuronal activity in the brain underlies the emergence of neuronal oscillations termed “brain waves”, which serve various physiological functions and correlate with different behavioral states. It has been postulated that at least ten distinct mechanisms are involved in the formulation of these brain waves, including variations in the concentration of extracellular neurotransmitters and ions, as well as changes in cellular excitability. In this mini review we highlight the contribution of astrocytes, a subtype of glia, in the formation and modulation of brain waves mainly due to their close association with synapses that allows their bidirectional interaction with neurons, and their syncytium-like activity via gap junctions that facilitate communication to distal brain regions through Ca²⁺ waves. These capabilities allow astrocytes to regulate neuronal excitability via glutamate uptake, gliotransmission and tight control of the extracellular K⁺ levels via a process termed K⁺ clearance. Spatio-temporal synchrony of activity across neuronal and astrocytic networks, both locally and distributed across cortical regions, underpins brain states and thereby behavioral states, and it is becoming apparent that astrocytes play an important role in the development and maintenance of neural activity underlying these complex behavioral states.

Learning, memory and consolidation mechanisms for behavioral control in hierarchically organized cortico-basal ganglia systems

This article aims to provide a synthesis on the question how brain structures cooperate to accomplish hierarchically organized behaviors, characterized by low‐level, habitual routines nested in larger sequences of planned, goal‐directed behavior. The functioning of a connected set of brain structures—prefrontal cortex, hippocampus, striatum, and dopaminergic mesencephalon—is reviewed in relation to two important distinctions: (a) goal‐directed as opposed to habitual behavior and (b) model‐based and model‐free learning. Recent evidence indicates that the orbitomedial prefrontal cortices not only subserve goal‐directed behavior and model‐based learning, but also code the “landscape” (task space) of behaviorally relevant variables. While the hippocampus stands out for its role in coding and memorizing world state representations, it is argued to function in model‐based learning but is not required for coding of action–outcome contingencies, illustrating that goal‐directed behavior is not congruent with model‐based learning. While the dorsolateral and dorsomedial striatum largely conform to the dichotomy between habitual versus goal‐directed behavior, ventral striatal functions go beyond this distinction. Next, we contextualize findings on coding of reward‐prediction errors by ventral tegmental dopamine neurons to suggest a broader role of mesencephalic dopamine cells, viz. in behavioral reactivity and signaling unexpected sensory changes. We hypothesize that goal‐directed behavior is hierarchically organized in interconnected cortico‐basal ganglia loops, where a limbic‐affective prefrontal‐ventral striatal loop controls action selection in a dorsomedial prefrontal–striatal loop, which in turn regulates activity in sensorimotor‐dorsolateral striatal circuits. This structure for behavioral organization requires alignment with mechanisms for memory formation and consolidation. We propose that frontal corticothalamic circuits form a high‐level loop for memory processing that initiates and temporally organizes nested activities in lower‐level loops, including the hippocampus and the ripple‐associated replay it generates. The evidence on hierarchically organized behavior converges with that on consolidation mechanisms in suggesting a frontal‐to‐caudal directionality in processing control.

Somatostatin+/nNOS+ neurons are involved in delta electroencephalogram activity and cortical-dependent recognition memory

Slow-wave activity (SWA) is an oscillatory neocortical activity occurring in the electroencephalogram delta (δ) frequency range (~0.5-4 Hz) during nonrapid eye movement sleep. SWA is a reliable indicator of sleep homeostasis after acute sleep loss and is involved in memory processes. Evidence suggests that cortical neuronal nitric oxide synthase (nNOS) expressing neurons that coexpress somatostatin (SST) play a key role in regulating SWA. However, previous studies lacked selectivity in targeting specific types of neurons that coexpress nNOS-cells which are activated in the cortex after sleep loss. We produced a mouse model that knocks out nNOS expression in neurons that coexpress SST throughout the cortex. Mice lacking nNOS expression in SST positive neurons exhibited significant impairments in both homeostatic low-δ frequency range SWA production and a recognition memory task that relies on cortical input. These results highlight that SST+/nNOS+ neurons are involved in the SWA homeostatic response and cortex-dependent recognition memory.

Large-scale structure and individual fingerprints of locally coupled sleep oscillations

Slow oscillations and sleep spindles, the canonical electrophysiological oscillations of nonrapid eye movement sleep, are thought to gate incoming sensory information, underlie processes of sleep-dependent memory consolidation, and are altered in various neuropsychiatric disorders. Accumulating evidence of the predominantly local expression of these individual oscillatory rhythms suggests that their cross-frequency interactions may have a similar local component. However, it is unclear whether locally coordinated sleep oscillations exist across the cortex, and whether and how these dynamics differ between fast and slow spindles, and sleep stages. Moreover, substantial individual variability in the expression of both spindles and slow oscillations raises the possibility that their temporal organization shows similar individual differences. Using two nights of multichannel electroencephalography recordings from 24 healthy individuals, we characterized the topography of slow oscillation-spindle coupling. We found that while slow oscillations are highly restricted in spatial extent, the phase of the local slow oscillation modulates local spindle activity at virtually every cortical site. However, coupling dynamics varied with spindle class, sleep stage, and cortical region. Moreover, the slow oscillation phase at which spindles were maximally expressed differed markedly across individuals while remaining stable across nights. These findings both add an important spatial aspect to our understanding of the temporal coupling of sleep oscillations and demonstrate the heterogeneity of coupling dynamics, which must be taken into account when formulating mechanistic accounts of sleep-related memory processing.

Across-night dynamics in traveling sleep slow waves throughout childhood

Study Objectives

Sleep slow waves behave like traveling waves and are thus a marker for brain connectivity. Across a night of sleep in adults, wave propagation is scaled down, becoming more local. Yet, it is unknown whether slow wave propagation undergoes similar across-night dynamics in childhood-a period of extensive cortical rewiring.

Methods

High-density electroencephalography (EEG; 128 channels) was recorded during sleep in three groups of healthy children: 2.0-4.9 years (n = 11), 5.0-8.9 years (n = 9) and 9.0-16.9 years (n = 9). Slow wave propagation speed, distance, and cortical involvement were quantified. To characterize across-night dynamics, the 20% most pronounced (highest amplitude) slow waves were subdivided into five time-based quintiles.

Results

We found indications that slow wave propagation distance decreased across a night of sleep. We observed an interesting interaction of across-night slow wave propagation dynamics with age (p < 0.05). When comparing the first and last quintiles, there was a trend level difference between age groups: 2- to 4.9-year-old children showed an 11.9% across-night decrease in slow wave propagation distance, which was not observed in the older two age groups. Regardless of age, cortical involvement decreased by 10.4%-23.7% across a night of sleep. No across-night changes were observed in slow wave speed.

Conclusions

Findings provide evidence that signatures of brain connectivity undergo across-night dynamics specific to maturational periods. These results suggest that across-night dynamics in slow wave propagation distance reflect heightened plasticity in underlying cerebral networks specific to developmental periods.

Sleep-Wake Cycle in Young and Older Mice

Sleep plays a key role in multiple cognitive functions and sleep pattern changes with aging. Human studies revealed that aging decreases sleep efficiency and reduces the total sleep time, the time spent in slow-wave sleep (SWS), and the delta power (1–4 Hz) during sleep; however, some studies of sleep and aging in mice reported opposing results. The aim of our work is to estimate how features of sleep–wake state in mice during aging could correspond to age-dependent changes observed in human. In this study, we investigated the sleep/wake cycle in young (3 months old) and older (12 months old) C57BL/6 mice using local-field potentials (LFPs). We found that older adult mice sleep more than young ones but only during the dark phase of sleep-wake cycle. Sleep fragmentation and sleep during the active phase (dark phase of cycle), homologous to naps, were higher in older mice. Older mice show a higher delta power in frontal cortex, which was accompanied with similar trend for age differences in slow wave density. We also investigated regional specificity of sleep–wake electrographic activities and found that globally posterior regions of the cortex show more rapid eye movement (REM) sleep whereas somatosensory cortex displays more often SWS patterns. Our results indicate that the effects of aging on the sleep–wake activities in mice occur mainly during the dark phase and the electrode location strongly influence the state detection. Despite some differences in sleep–wake cycle during aging between human and mice, some features of mice sleep share similarity with human sleep during aging.