Regional slow waves and spindles in human sleep

CPAP Treatment Partly Normalizes Sleep Spindle Features in Obstructive Sleep Apnea

Objective. Obstructive sleep apnea (OSA) decreases sleep spindle density and frequency. We evaluated the effects of continuous positive airway pressure (CPAP) treatment on different features of sleep spindles. Methods. Twenty OSA patients underwent two night polysomnographies in a diagnostic phase and one night polysomnography after 6 months of CPAP treatment. The control group comprised 20 healthy controls. Sleep spindles were analyzed by a previously developed automated method. Unilateral and bilateral spindles were identified in central and frontopolar brain locations. Spindle density and frequency were determined for the first and last half of the NREM time. Results. The density of bilateral central spindles, which did not change in the untreated OSA patients, increased towards the morning hours during CPAP treatment and in the controls. Central spindles did not become faster with sleep in OSA patients and the central spindles remained slow in the left hemisphere even with CPAP. Conclusion. CPAP treatment normalized spindle features only partially. The changes may be associated with deficits in thalamocortical spindle generating loops. Significance. This study shows that some sleep spindle changes persist after CPAP treatment in OSA patients. The association of these changes to daytime symptoms in OSA patients needs to be further evaluated.

Coordinated infraslow neural and cardiac oscillations mark fragility and offline periods in mammalian sleep

Rodents sleep in bouts lasting minutes; humans sleep for hours. What are the universal needs served by sleep given such variability? In sleeping mice and humans, through monitoring neural and cardiac activity (combined with assessment of arousability and overnight memory consolidation, respectively), we find a previously unrecognized hallmark of sleep that balances two fundamental yet opposing needs: to maintain sensory reactivity to the environment while promoting recovery and memory consolidation. Coordinated 0.02-Hz oscillations of the sleep spindle band, hippocampal ripple activity, and heart rate sequentially divide non-rapid eye movement (non-REM) sleep into offline phases and phases of high susceptibility to external stimulation. A noise stimulus chosen such that sleeping mice woke up or slept through at comparable rates revealed that offline periods correspond to raising, whereas fragility periods correspond to declining portions of the 0.02-Hz oscillation in spindle activity. Oscillations were present throughout non-REM sleep in mice, yet confined to light non-REM sleep (stage 2) in humans. In both species, the 0.02-Hz oscillation predominated over posterior cortex. The strength of the 0.02-Hz oscillation predicted superior memory recall after sleep in a declarative memory task in humans. These oscillations point to a conserved function of mammalian non-REM sleep that cycles between environmental alertness and internal memory processing in 20- to 25-s intervals. Perturbed 0.02-Hz oscillations may cause memory impairment and ill-timed arousals in sleep disorders.

Global and local complexity of intracranial EEG decreases during NREM sleep

Key to understanding the neuronal basis of consciousness is the characterization of the neural signatures of changes in level of consciousness during sleep. Here we analysed three measures of dynamical complexity on spontaneous depth electrode recordings from 10 epilepsy patients during wakeful rest (WR) and different stages of sleep: (i) Lempel-Ziv complexity, which is derived from how compressible the data are; (ii) amplitude coalition entropy, which measures the variability over time of the set of channels active above a threshold; (iii) synchrony coalition entropy, which measures the variability over time of the set of synchronous channels. When computed across sets of channels that are broadly distributed across multiple brain regions, all three measures decreased substantially in all participants during early-night non-rapid eye movement (NREM) sleep. This decrease was partially reversed during late-night NREM sleep, while the measures scored similar to WR during rapid eye movement (REM) sleep. This global pattern was in almost all cases mirrored at the local level by groups of channels located in a single region. In testing for differences between regions, we found elevated signal complexity in the frontal lobe. These differences could not be attributed solely to changes in spectral power between conditions. Our results provide further evidence that the level of consciousness correlates with neural dynamical complexity.

Sleep Neurophysiological Dynamics Through the Lens of Multitaper Spectral Analysis

During sleep, cortical and subcortical structures within the brain engage in highly structured oscillatory dynamics that can be observed in the electroencephalogram (EEG). The ability to accurately describe changes in sleep state from these oscillations has thus been a major goal of sleep medicine. While numerous studies over the past 50 years have shown sleep to be a continuous, multifocal, dynamic process, long-standing clinical practice categorizes sleep EEG into discrete stages through visual inspection of 30-s epochs. By representing sleep as a coarsely discretized progression of stages, vital neurophysiological information on the dynamic interplay between sleep and arousal is lost. However, by using principled time-frequency spectral analysis methods, the rich dynamics of the sleep EEG are immediately visible-elegantly depicted and quantified at time scales ranging from a full night down to individual microevents. In this paper, we review the neurophysiology of sleep through this lens of dynamic spectral analysis. We begin by reviewing spectral estimation techniques traditionally used in sleep EEG analysis and introduce multitaper spectral analysis, a method that makes EEG spectral estimates clearer and more accurate than traditional approaches. Through the lens of the multitaper spectrogram, we review the oscillations and mechanisms underlying the traditional sleep stages. In doing so, we will demonstrate how multitaper spectral analysis makes the oscillatory structure of traditional sleep states instantaneously visible, closely paralleling the traditional hypnogram, but with a richness of information that suggests novel insights into the neural mechanisms of sleep, as well as novel clinical and research applications.

Large Scale Cortical Functional Networks Associated with Slow-Wave and Spindle-Burst-Related Spontaneous Activity

Cortical sensory systems are active with rich patterns of activity during sleep and under light anesthesia. Remarkably, this activity shares many characteristics with those present when the awake brain responds to sensory stimuli. We review two specific forms of such activity: slow-wave activity (SWA) in the adult brain and spindle bursts in developing brain. SWA is composed of 0.5-4 Hz resting potential fluctuations. Although these fluctuations synchronize wide regions of cortex, recent large-scale imaging has shown spatial details of their distribution that reflect underlying cortical structural projections and networks. These networks are regulated, as prior awake experiences alter both the spatial and temporal features of SWA in subsequent sleep. Activity patterns of the immature brain, however, are very different from those of the adult. SWA is absent, and the dominant pattern is spindle bursts, intermittent high frequency oscillations superimposed on slower depolarizations within sensory cortices. These bursts are driven by intrinsic brain activity, which act to generate peripheral inputs, for example via limb twitches. They are present within developing sensory cortex before they are mature enough to exhibit directed movements and respond to external stimuli. Like in the adult, these patterns resemble those evoked by sensory stimulation when awake. It is suggested that spindle-burst activity is generated purposefully by the developing nervous system as a proxy for true external stimuli. While the sleep-related functions of both slow-wave and spindle-burst activity may not be entirely clear, they reflect robust regulated phenomena which can engage select wide-spread cortical circuits. These circuits are similar to those activated during sensory processing and volitional events. We highlight these two patterns of brain activity because both are prominent and well-studied forms of spontaneous activity that will yield valuable insights into brain function in the coming years.

Nicotinic receptors in mouse prefrontal cortex modulate ultraslow fluctuations related to conscious processing

The prefrontal cortex (PFC) plays an important role in cognitive processes, including access to consciousness. The PFC receives significant cholinergic innervation and nicotinic acetylcholine receptors (nAChRs) contribute greatly to the effects of acetylcholine signaling. Using in vivo two-photon imaging of both awake and anesthetized mice, we recorded spontaneous, ongoing neuronal activity in layer II/III in the PFC of WT mice and mice deleted for different nAChR subunits. As in humans, this activity is characterized by synchronous ultraslow fluctuations and neuronal synchronicity is disrupted by light general anesthesia. Both the α7 and β2 nAChR subunits play an important role in the generation of ultraslow fluctuations that occur to a different extent during quiet wakefulness and light general anesthesia. The β2 subunit is specifically required for synchronized activity patterns. Furthermore, chronic application of mecamylamine, an antagonist of nAChRs, disrupts the generation of ultraslow fluctuations. Our findings provide new insight into the ongoing spontaneous activity in the awake and anesthetized state, and the role of cholinergic neurotransmission in the orchestration of cognitive functions.

Rotating waves during human sleep spindles organize global patterns of activity that repeat precisely through the night

During sleep, the thalamus generates a characteristic pattern of transient, 11-15 Hz sleep spindle oscillations, which synchronize the cortex through large-scale thalamocortical loops. Spindles have been increasingly demonstrated to be critical for sleep-dependent consolidation of memory, but the specific neural mechanism for this process remains unclear. We show here that cortical spindles are spatiotemporally organized into circular wave-like patterns, organizing neuronal activity over tens of milliseconds, within the timescale for storing memories in large-scale networks across the cortex via spike-time dependent plasticity. These circular patterns repeat over hours of sleep with millisecond temporal precision, allowing reinforcement of the activity patterns through hundreds of reverberations. These results provide a novel mechanistic account for how global sleep oscillations and synaptic plasticity could strengthen networks distributed across the cortex to store coherent and integrated memories.

Spatiotemporal characteristics of sleep spindles depend on cortical location

Since their discovery almost one century ago, sleep spindles, 0.5-2s long bursts of oscillatory activity at 9-16Hz during NREM sleep, have been thought to be global and relatively uniform throughout the cortex. Recent work, however, has brought this concept into question but it remains unclear to what degree spindles are global or local and if their properties are uniform or location-dependent. We addressed this question by recording sleep in eight patients undergoing evaluation for epilepsy with intracranial electrocorticography, which combines high spatial resolution with extensive cortical coverage. We find that spindle characteristics are not uniform but are strongly influenced by the underlying cortical regions, particularly for spindle density and fundamental frequency. We observe both highly isolated and spatially distributed spindles, but in highly skewed proportions: while most spindles are restricted to one or very few recording channels at any given time, there are spindles that occur over widespread areas, often involving lateral prefrontal cortices and superior temporal gyri. Their co-occurrence is affected by a subtle but significant propagation of spindles from the superior prefrontal regions and the temporal cortices towards the orbitofrontal cortex. This work provides a brain-wide characterization of sleep spindles as mostly local graphoelements with heterogeneous characteristics that depend on the underlying cortical area. We propose that the combination of local characteristics and global organization reflects the dual properties of the thalamo-cortical generators and provides a flexible framework to support the many functions ascribed to sleep in general and spindles specifically.

Intra- and interregional cortical interactions related to sharp-wave ripples and dentate spikes

The hippocampus generates population events termed sharp-wave ripples (SWRs) and dentate spikes (DSs). While little is known about DSs, SWR-related hippocampal discharges during sleep are thought to replay prior waking activity, reactivating the cortical networks that encoded the initial experience. During slow-wave sleep, such reactivations likely occur during up-states, when most cortical neurons are depolarized. However, most studies have examined the relationship between SWRs and up-states measured in single neocortical regions. As a result, it is currently unclear whether SWRs are associated with particular patterns of widely distributed cortical activity. Additionally, no such investigation has been carried out for DSs. The present study addressed these questions by recording SWRs and DSs from the dorsal hippocampus simultaneously with prefrontal, sensory (visual and auditory), perirhinal, and entorhinal cortices in naturally sleeping rats. We found that SWRs and DSs were associated with up-states in all cortical regions. Up-states coinciding with DSs and SWRs exhibited increased unit activity, power in the gamma band, and intraregional gamma coherence. Unexpectedly, interregional gamma coherence rose much more strongly in relation to DSs than to SWRs. Whereas the increase in gamma coherence was time locked to DSs, that seen in relation to SWRs was not. These observations suggest that SWRs are related to the strength of up-state activation within individual regions throughout the neocortex but not so much to gamma coherence between different regions. Perhaps more importantly, DSs coincided with stronger periods of interregional gamma coherence, suggesting that they play a more important role than previously assumed.

NEW & NOTEWORTHY

Off-line cortico-hippocampal interactions are thought to support memory consolidation. We surveyed the relationship between hippocampal sharp-wave ripples (SWRs) and dentate spikes (DSs) with up-states across multiple cortical regions. SWRs and DSs were associated with increased cortical gamma oscillations. Interregional gamma coherence rose much more strongly in relation to DSs than to SWRs. Moreover, it was time locked to DSs but not SWRs. These results have important implications for current theories of systems memory consolidation during sleep.

Organic electronics for high-resolution electrocorticography of the human brain

Localizing neuronal patterns that generate pathological brain signals may assist with tissue resection and intervention strategies in patients with neurological diseases. Precise localization requires high spatiotemporal recording from populations of neurons while minimizing invasiveness and adverse events. We describe a large-scale, high-density, organic material-based, conformable neural interface device ("NeuroGrid") capable of simultaneously recording local field potentials (LFPs) and action potentials from the cortical surface. We demonstrate the feasibility and safety of intraoperative recording with NeuroGrids in anesthetized and awake subjects. Highly localized and propagating physiological and pathological LFP patterns were recorded, and correlated neural firing provided evidence about their local generation. Application of NeuroGrids to brain disorders, such as epilepsy, may improve diagnostic precision and therapeutic outcomes while reducing complications associated with invasive electrodes conventionally used to acquire high-resolution and spiking data.

Human cortical-hippocampal dialogue in wake and slow-wave sleep

Declarative memory consolidation is hypothesized to require a two-stage, reciprocal cortical-hippocampal dialogue. According to this model, higher frequency signals convey information from the cortex to hippocampus during wakefulness, but in the reverse direction during slow-wave sleep (SWS). Conversely, lower-frequency activity propagates from the information "receiver" to the "sender" to coordinate the timing of information transfer. Reversal of sender/receiver roles across wake and SWS implies that higher- and lower-frequency signaling should reverse direction between the cortex and hippocampus. However, direct evidence of such a reversal has been lacking in humans. Here, we use human resting-state fMRI and electrocorticography to demonstrate that δ-band activity and infraslow activity propagate in opposite directions between the hippocampus and cerebral cortex. Moreover, both δ activity and infraslow activity reverse propagation directions between the hippocampus and cerebral cortex across wake and SWS. These findings provide direct evidence for state-dependent reversals in human cortical-hippocampal communication.

Fast fMRI can detect oscillatory neural activity in humans

Oscillatory neural dynamics play an important role in the coordination of large-scale brain networks. High-level cognitive processes depend on dynamics evolving over hundreds of milliseconds, so measuring neural activity in this frequency range is important for cognitive neuroscience. However, current noninvasive neuroimaging methods are not able to precisely localize oscillatory neural activity above 0.2 Hz. Electroencephalography and magnetoencephalography have limited spatial resolution, whereas fMRI has limited temporal resolution because it measures vascular responses rather than directly recording neural activity. We hypothesized that the recent development of fast fMRI techniques, combined with the extra sensitivity afforded by ultra-high-field systems, could enable precise localization of neural oscillations. We tested whether fMRI can detect neural oscillations using human visual cortex as a model system. We detected small oscillatory fMRI signals in response to stimuli oscillating at up to 0.75 Hz within single scan sessions, and these responses were an order of magnitude larger than predicted by canonical linear models. Simultaneous EEG-fMRI and simulations based on a biophysical model of the hemodynamic response to neuronal activity suggested that the blood oxygen level-dependent response becomes faster for rapidly varying stimuli, enabling the detection of higher frequencies than expected. Accounting for phase delays across voxels further improved detection, demonstrating that identifying vascular delays will be of increasing importance with higher-frequency activity. These results challenge the assumption that the hemodynamic response is slow, and demonstrate that fMRI has the potential to map neural oscillations directly throughout the brain.

Spatiotemporal Organization and Cross-Frequency Coupling of Sleep Spindles in Primate Cerebral Cortex

STUDY OBJECTIVES

The sleep spindle has been implicated in thalamic sensory gating, cortical development, and memory consolidation. These multiple functions may depend on specific spatiotemporal emergence and interactions with other spindles and other forms of brain activity. Therefore, we measured sleep spindle cortical distribution, regional heterogeneity, synchronization, and phase relationships with other electroencephalographic components in freely moving primates.

METHODS

Transcortical field potentials were recorded from Japanese monkeys via telemetry and were analyzed using the Hilbert-Huang transform.

RESULTS

Spindle (12-20 Hz) current sources were identified over a wide region of the frontoparietal cortex. Most spindles occurred independently in their own frequency, but some appeared concordant between cortical areas with frequency interdependence, particularly in nearby regions and bilaterally symmetrical regions. Spindles in the dorsolateral prefrontal cortex appeared around the surface-positive and depth-negative phase of transcortically recorded slow oscillations (< 1 Hz), whereas centroparietal spindles emerged around the opposite phase. The slow-oscillation phase reversed between the prefrontal and central regions. Gamma activities increased before spindle onset. Several regional heterogeneities in properties of human spindles were replicated in the monkeys, including frequency, density, and inter-cortical time lags, although their topographic patterns were different from those of humans. The phase-amplitude coupling between spindle and gamma activity was also replicated.

CONCLUSIONS

Spindles in widespread cortical regions are possibly driven by independent rhythm generators, but are temporally associated to spindles in other regions and to slow and gamma oscillations by corticocortical and thalamocortical pathways.

Timing matters: open-loop stimulation does not improve overnight consolidation of word pairs in humans

The application of auditory clicks during non‐rapid eye movement (NREM) sleep phase‐locked to the up state of the slow oscillation (closed‐loop stimulation) has previously been shown to enhance the consolidation of declarative memories. We designed and applied sequences of three clicks during deep NREM sleep to achieve a quasi‐phase‐dependent open‐loop stimulation. This stimulation was successful in eliciting slow oscillation power in the stimulation period. Although fast and slow spindle power were markedly decreased during the stimulation period, memory consolidation did not differ from control. During putative up states fast spindle power remained, however, at control levels. We conclude that concurrence of slow oscillations and fast spindles suffices to maintain memory consolidation at control levels despite an overall decreased spindle activity.

Sleep Spindles as an Electrographic Element: Description and Automatic Detection Methods

Sleep spindle is a peculiar oscillatory brain pattern which has been associated with a number of sleep (isolation from exteroceptive stimuli, memory consolidation) and individual characteristics (intellectual quotient). Oddly enough, the definition of a spindle is both incomplete and restrictive. In consequence, there is no consensus about how to detect spindles. Visual scoring is cumbersome and user dependent. To analyze spindle activity in a more robust way, automatic sleep spindle detection methods are essential. Various algorithms were developed, depending on individual research interest, which hampers direct comparisons and meta-analyses. In this review, sleep spindle is first defined physically and topographically. From this general description, we tentatively extract the main characteristics to be detected and analyzed. A nonexhaustive list of automatic spindle detection methods is provided along with a description of their main processing principles. Finally, we propose a technique to assess the detection methods in a robust and comparable way.

Sparse asynchronous cortical generators can produce measurable scalp EEG signals

We investigate to what degree the synchronous activation of a smooth patch of cortex is necessary for observing EEG scalp activity. We perform extensive simulations to compare the activity generated on the scalp by different models of cortical activation, based on intracranial EEG findings reported in the literature. The spatial activation is modeled as a cortical patch of constant activation or as random sets of small generators (0.1 to 3cm(2) each) concentrated in a cortical region. Temporal activation models for the generation of oscillatory activity are either equal phase or random phase across the cortical patches. The results show that smooth or random spatial activation profiles produce scalp electric potential distributions with the same shape. Also, in the generation of oscillatory activity, multiple cortical generators with random phase produce scalp activity attenuated on average only 2 to 4 times compared to generators with equal phase. Sparse asynchronous cortical generators can produce measurable scalp EEG. This is a possible explanation for seemingly paradoxical observations of simultaneous disorganized intracranial activity and scalp EEG signals. Thus, the standard interpretation of scalp EEG might constitute an oversimplification of the underlying brain activity.

Obstructive sleep apnea decreases central nervous system-derived proteins in the cerebrospinal fluid

We hypothesized that one mechanism underlying the association between obstructive sleep apnea (OSA) and Alzheimer's disease is OSA leading to decreased slow wave activity (SWA), increased synaptic activity, decreased glymphatic clearance, and increased amyloid-β. Polysomnography and lumbar puncture were performed in OSA and control groups. SWA negatively correlated with cerebrospinal fluid (CSF) amyloid-β-40 among controls and was decreased in the OSA group. Unexpectedly, amyloid-β-40 was decreased in the OSA group. Other neuronally derived proteins, but not total protein, were also decreased in the OSA group, suggesting that OSA may affect the interaction between interstitial and cerebrospinal fluid. Ann Neurol 2016;80:154-159.

Accuracy of Automatic Polysomnography Scoring Using Frontal Electrodes

STUDY OBJECTIVES

The economic cost of performing sleep monitoring at home is a major deterrent to adding sleep data during home studies for investigation of sleep apnea and to investigating non-respiratory sleep complaints. Michele Sleep Scoring System (MSS) is a validated automatic system that utilizes central electroencephalography (EEG) derivations and requires minimal editing. We wished to determine if MSS' accuracy is maintained if frontal derivations are used instead. If confirmed, home sleep monitoring would not require home setup or lengthy manual scoring by technologists.

METHODS

One hundred two polysomnograms (PSGs) previously recorded from patients with assorted sleep disorders were scored using MSS once with central and once with frontal derivations. Total sleep time, sleep/stage R sleep onset latencies, awake time, time in different sleep stages, arousal/awakening index and apnea-hypopnea index were compared. In addition, odds ratio product (ORP), a continuous index of sleep depth/quality (Sleep 2015;38:641-54), was generated for every 30-sec epoch in each PSG and epoch-by-epoch comparison of ORP was performed.

RESULTS

Intraclass correlation coefficients (ICCs) ranged from 0.89 to 1.0 for the various sleep variables (0.96 ± 0.03). For epoch-by-epoch comparisons of ORP, ICC was > 0.85 in 96 PSGs. Lower values in the other six PSGs were related to signal artifacts in either derivation. ICC for whole-record average ORP was 0.98.

CONCLUSIONS

MSS is as accurate with frontal as with central EEG derivations. The use of frontal electrodes along with MSS should make it possible to obtain high-quality sleep data without requiring home setup or lengthy scoring time by expert technologists.

Responses in Rat Core Auditory Cortex are Preserved during Sleep Spindle Oscillations

STUDY OBJECTIVES

Sleep is defined as a reversible state of reduction in sensory responsiveness and immobility. A long-standing hypothesis suggests that a high arousal threshold during non-rapid eye movement (NREM) sleep is mediated by sleep spindle oscillations, impairing thalamocortical transmission of incoming sensory stimuli. Here we set out to test this idea directly by examining sensory-evoked neuronal spiking activity during natural sleep.

METHODS

We compared neuronal (n = 269) and multiunit activity (MUA), as well as local field potentials (LFP) in rat core auditory cortex (A1) during NREM sleep, comparing responses to sounds depending on the presence or absence of sleep spindles.

RESULTS

We found that sleep spindles robustly modulated the timing of neuronal discharges in A1. However, responses to sounds were nearly identical for all measured signals including isolated neurons, MUA, and LFPs (all differences < 10%). Furthermore, in 10% of trials, auditory stimulation led to an early termination of the sleep spindle oscillation around 150-250 msec following stimulus onset. Finally, active ON states and inactive OFF periods during slow waves in NREM sleep affected the auditory response in opposite ways, depending on stimulus intensity.

CONCLUSIONS

Responses in core auditory cortex are well preserved regardless of sleep spindles recorded in that area, suggesting that thalamocortical sensory relay remains functional during sleep spindles, and that sensory disconnection in sleep is mediated by other mechanisms.

Astrocytes regulate cortical state switching in vivo

The role of astrocytes in neuronal function has received increasing recognition, but disagreement remains about their function at the circuit level. Here we use in vivo two-photon calcium imaging of neocortical astrocytes while monitoring the activity state of the local neuronal circuit electrophysiologically and optically. We find that astrocytic calcium activity precedes spontaneous circuit shifts to the slow-oscillation-dominated state, a neocortical rhythm characterized by synchronized neuronal firing and important for sleep and memory. Further, we show that optogenetic activation of astrocytes switches the local neuronal circuit to this slow-oscillation state. Finally, using two-photon imaging of extracellular glutamate, we find that astrocytic transients in glutamate co-occur with shifts to the synchronized state and that optogenetically activated astrocytes can generate these glutamate transients. We conclude that astrocytes can indeed trigger the low-frequency state of a cortical circuit by altering extracellular glutamate, and therefore play a causal role in the control of cortical synchronizations.

Functions and Mechanisms of Sleep

Sleep is a complex physiological process that is regulated globally, regionally, and locally by both cellular and molecular mechanisms. It occurs to some extent in all animals, although sleep expression in lower animals may be co-extensive with rest. Sleep regulation plays an intrinsic part in many behavioral and physiological functions. Currently, all researchers agree there is no single physiological role sleep serves. Nevertheless, it is quite evident that sleep is essential for many vital functions including development, energy conservation, brain waste clearance, modulation of immune responses, cognition, performance, vigilance, disease, and psychological state. This review details the physiological processes involved in sleep regulation and the possible functions that sleep may serve. This description of the brain circuitry, cell types, and molecules involved in sleep regulation is intended to further the reader's understanding of the functions of sleep.

Form and Function of Sleep Spindles across the Lifespan

Since the advent of EEG recordings, sleep spindles have been identified as hallmarks of non-REM sleep. Despite a broad general understanding of mechanisms of spindle generation gleaned from animal studies, the mechanisms underlying certain features of spindles in the human brain, such as “global” versus “local” spindles, are largely unknown. Neither the topography nor the morphology of sleep spindles remains constant throughout the lifespan. It is likely that changes in spindle phenomenology during development and aging are the result of dramatic changes in brain structure and function. Across various developmental windows, spindle activity is correlated with general cognitive aptitude, learning, and memory; however, these correlations vary in strength, and even direction, depending on age and metrics used. Understanding these differences across the lifespan should further clarify how these oscillations are generated and their function under a variety of circumstances. We discuss these issues, and their translational implications for human cognitive function. Because sleep spindles are similarly affected in disorders of neurodevelopment (such as schizophrenia) and during aging (such as neurodegenerative conditions), both types of disorders may benefit from therapies based on a better understanding of spindle function.

The Contribution of Thalamocortical Core and Matrix Pathways to Sleep Spindles

Sleep spindles arise from the interaction of thalamic and cortical neurons. Neurons in the thalamic reticular nucleus (TRN) inhibit thalamocortical neurons, which in turn excite the TRN and cortical neurons. A fundamental principle of anatomical organization of the thalamocortical projections is the presence of two pathways: the diffuse matrix pathway and the spatially selective core pathway. Cortical layers are differentially targeted by these two pathways with matrix projections synapsing in superficial layers and core projections impinging on middle layers. Based on this anatomical observation, we propose that spindles can be classified into two classes, those arising from the core pathway and those arising from the matrix pathway, although this does not exclude the fact that some spindles might combine both pathways at the same time. We find evidence for this hypothesis in EEG/MEG studies, intracranial recordings, and computational models that incorporate this difference. This distinction will prove useful in accounting for the multiple functions attributed to spindles, in that spindles of different types might act on local and widespread spatial scales. Because spindle mechanisms are often hijacked in epilepsy and schizophrenia, the classification proposed in this review might provide valuable information in defining which pathways have gone awry in these neurological disorders.

Overexpression of Dyrk1A, a Down Syndrome Candidate, Decreases Excitability and Impairs Gamma Oscillations in the Prefrontal Cortex

The dual-specificity tyrosine phosphorylation-regulated kinase DYRK1A is a serine/threonine kinase involved in neuronal differentiation and synaptic plasticity and a major candidate of Down syndrome brain alterations and cognitive deficits. DYRK1A is strongly expressed in the cerebral cortex, and its overexpression leads to defective cortical pyramidal cell morphology, synaptic plasticity deficits, and altered excitation/inhibition balance. These previous observations, however, do not allow predicting how the behavior of the prefrontal cortex (PFC) network and the resulting properties of its emergent activity are affected. Here, we integrate functional, anatomical, and computational data describing the prefrontal network alterations in transgenic mice overexpressingDyrk1A(TgDyrk1A). Usingin vivoextracellular recordings, we show decreased firing rate and gamma frequency power in the prefrontal network of anesthetized and awakeTgDyrk1Amice. Immunohistochemical analysis identified a selective reduction of vesicular GABA transporter punctae on parvalbumin positive neurons, without changes in the number of cortical GABAergic neurons in the PFC ofTgDyrk1Amice, which suggests that selective disinhibition of parvalbumin interneurons would result in an overinhibited functional network. Using a conductance-based computational model, we quantitatively demonstrate that this alteration could explain the observed functional deficits including decreased gamma power and firing rate. Our results suggest that dysfunction of cortical fast-spiking interneurons might be central to the pathophysiology of Down syndrome.

SIGNIFICANCE STATEMENT

DYRK1Ais a major candidate gene in Down syndrome. Its overexpression results into altered cognitive abilities, explained by defective cortical microarchitecture and excitation/inhibition imbalance. An open question is how these deficits impact the functionality of the prefrontal cortex network. Combining functional, anatomical, and computational approaches, we identified decreased neuronal firing rate and deficits in gamma frequency in the prefrontal cortices of transgenic mice overexpressingDyrk1A We also identified a reduction of vesicular GABA transporter punctae specifically on parvalbumin positive interneurons. Using a conductance-based computational model, we demonstrate that this decreased inhibition on interneurons recapitulates the observed functional deficits, including decreased gamma power and firing rate. Our results suggest that dysfunction of cortical fast-spiking interneurons might be central to the pathophysiology of Down syndrome.

Developmental Changes in Sleep Spindle Characteristics and Sigma Power across Early Childhood

Sleep spindles, a prominent feature of the non-rapid eye movement (NREM) sleep electroencephalogram (EEG), are linked to cognitive abilities. Early childhood is a time of rapid cognitive and neurophysiological maturation; however, little is known about developmental changes in sleep spindles. In this study, we longitudinally examined trajectories of multiple sleep spindle characteristics (i.e., spindle duration, frequency, integrated spindle amplitude, and density) and power in the sigma frequency range (10-16 Hz) across ages 2, 3, and 5 years (n = 8; 3 males). At each time point, nocturnal sleep EEG was recorded in-home after 13-h of prior wakefulness. Spindle duration, integrated spindle amplitude, and sigma power increased with age across all EEG derivations (C3A2, C4A1, O2A1, and O1A2; all ps < 0.05). We also found a developmental decrease in mean spindle frequency (p < 0.05) but no change in spindle density with increasing age. Thus, sleep spindles increased in duration and amplitude but decreased in frequency across early childhood. Our data characterize early developmental changes in sleep spindles, which may advance understanding of thalamocortical brain connectivity and associated lifelong disease processes. These findings also provide unique insights into spindle ontogenesis in early childhood and may help identify electrophysiological features related to healthy and aberrant brain maturation.

Parietal Fast Sleep Spindle Density Decrease in Alzheimer's Disease and Amnesic Mild Cognitive Impairment

Several studies have identified two types of sleep spindles: fast (13-15 Hz) centroparietal and slow (11-13 Hz) frontal spindles. Alterations in spindle activity have been observed in Alzheimer's disease (AD) and Mild Cognitive Impairment (MCI). Only few studies have separately assessed fast and slow spindles in these patients showing a reduction of fast spindle count, but the possible local specificity of this phenomenon and its relation to cognitive decline severity are not clear. Moreover, fast and slow spindle density have never been assessed in AD/MCI. We have assessed fast and slow spindles in 15 AD patients, 15 amnesic MCI patients, and 15 healthy elderly controls (HC). Participants underwent baseline polysomnographic recording (19 cortical derivations). Spindles during nonrapid eye movements sleep were automatically detected, and spindle densities of the three groups were compared in the derivations where fast and slow spindles exhibited their maximum expression (parietal and frontal, resp.). AD and MCI patients showed a significant parietal fast spindle density decrease, positively correlated with Minimental State Examination scores. Our results suggest that AD-related changes in spindle density are specific for frequency and location, are related to cognitive decline severity, and may have an early onset in the pathology development.

Double Roles of Macrophages in Human Neuroimmune Diseases and Their Animal Models

Macrophages are important immune cells of the innate immune system that are involved in organ-specific homeostasis and contribute to both pathology and resolution of diseases including infections, cancer, obesity, atherosclerosis, and autoimmune disorders. Multiple lines of evidence point to macrophages as a remarkably heterogeneous cell type. Different phenotypes of macrophages exert either proinflammatory or anti-inflammatory roles depending on the cytokines and other mediators that they are exposed to in the local microenvironment. Proinflammatory macrophages secrete detrimental molecules to induce disease development, while anti-inflammatory macrophages produce beneficial mediators to promote disease recovery. The conversion of the phenotypes of macrophages can regulate the initiation, development, and recovery of autoimmune diseases. Human neuroimmune diseases majorly include multiple sclerosis (MS), neuromyelitis optica (NMO), myasthenia gravis (MG), and Guillain-Barré syndrome (GBS) and macrophages contribute to the pathogenesis of these neuroimmune diseases. In this review, we summarize the double roles of macrophage in neuroimmune diseases and their animal models to further explore the mechanisms of macrophages involved in the pathogenesis of these disorders, which may provide a potential therapeutic approach for these disorders in the future.

Synchronization and Propagation of Global Sleep Spindles

Sleep spindles occur thousands of times during normal sleep and can be easily detected by visual inspection of EEG signals. These characteristics make spindles one of the most studied EEG structures in mammalian sleep. In this work we considered global spindles, which are spindles that are observed simultaneously in all EEG channels. We propose a methodology that investigates both the signal envelope and phase/frequency of each global spindle. By analysing the global spindle phase we showed that 90% of spindles synchronize with an average latency time of 0.1 s. We also measured the frequency modulation (chirp) of global spindles and found that global spindle chirp and synchronization are not correlated. By investigating the signal envelopes and implementing a homogeneous and isotropic propagation model, we could estimate both the signal origin and velocity in global spindles. Our results indicate that this simple and non-invasive approach could determine with reasonable precision the spindle origin, and allowed us to estimate a signal speed of 0.12 m/s. Finally, we consider whether synchronization might be useful as a non-invasive diagnostic tool.

Stimulating forebrain communications: Slow sinusoidal electric fields over frontal cortices dynamically modulate hippocampal activity and cortico-hippocampal interplay during slow-wave states

Slow-wave states are characterized by the most global physiological phenomenon in the mammalian brain, the large-amplitude slow oscillation (SO; ~1Hz) composed of alternating states of activity (ON/UP states) and silence (OFF/DOWN states) at the network and single cell levels. The SO is cortically generated and appears as a traveling wave that can propagate across the cortical surface and can invade the hippocampus. This cortical rhythm is thought to be imperative for sleep-dependent memory consolidation, potentially through increased interactions with the hippocampus. The SO is correlated with learning and its presumed enhancement via slow rhythmic electrical field stimulation improves subsequent mnemonic performance. However, the mechanism by which such field stimulation influences the dynamics of ongoing cortico-hippocampal communication is unknown. Here we show - using multi-site recordings in urethane-anesthetized rats - that sinusoidal electrical field stimulation applied to the frontal region of the cerebral cortex creates a platform for improved cortico-hippocampal communication. Moderate-intensity field stimulation entrained hippocampal slow activity (likely by way of the temporoammonic pathway) and also increased sharp-wave ripples, the signature memory replay events of the hippocampus, and further increased cortical spindles. Following cessation of high-intensity stimulation, SO interactions in the cortical-to-hippocampal direction were reduced, while the reversed hippocampal-to-cortical communication at both SO and gamma bandwidths was enhanced. Taken together, these findings suggest that cortical field stimulation may function to boost memory consolidation by strengthening cortico-hippocampal and hippocampo-cortical interplay at multiple nested frequencies in an intensity-dependent fashion.

NREM2 and Sleep Spindles Are Instrumental to the Consolidation of Motor Sequence Memories

Although numerous studies have convincingly demonstrated that sleep plays a critical role in motor sequence learning (MSL) consolidation, the specific contribution of the different sleep stages in this type of memory consolidation is still contentious. To probe the role of stage 2 non-REM sleep (NREM2) in this process, we used a conditioning protocol in three different groups of participants who either received an odor during initial training on a motor sequence learning task and were re-exposed to this odor during different sleep stages of the post-training night (i.e., NREM2 sleep [Cond-NREM2], REM sleep [Cond-REM], or were not conditioned during learning but exposed to the odor during NREM2 [NoCond]). Results show that the Cond-NREM2 group had significantly higher gains in performance at retest than both the Cond-REM and NoCond groups. Also, only the Cond-NREM2 group yielded significant changes in sleep spindle characteristics during cueing. Finally, we found that a change in frequency of sleep spindles during cued-memory reactivation mediated the relationship between the experimental groups and gains in performance the next day. These findings strongly suggest that cued-memory reactivation during NREM2 sleep triggers an increase in sleep spindle activity that is then related to the consolidation of motor sequence memories.

High Resolution Topography of Age-Related Changes in Non-Rapid Eye Movement Sleep Electroencephalography

Sleeping brain activity reflects brain anatomy and physiology. The aim of this study was to use high density (256 channel) electroencephalography (EEG) during sleep to characterize topographic changes in sleep EEG power across normal aging, with high spatial resolution. Sleep was evaluated in 92 healthy adults aged 18–65 years old using full polysomnography and high density EEG. After artifact removal, spectral power density was calculated for standard frequency bands for all channels, averaged across the NREM periods of the first 3 sleep cycles. To quantify topographic changes with age, maps were generated of the Pearson’s coefficient of the correlation between power and age at each electrode. Significant correlations were determined by statistical non-parametric mapping. Absolute slow wave power declined significantly with increasing age across the entire scalp, whereas declines in theta and sigma power were significant only in frontal regions. Power in fast spindle frequencies declined significantly with increasing age frontally, whereas absolute power of slow spindle frequencies showed no significant change with age. When EEG power was normalized across the scalp, a left centro-parietal region showed significantly less age-related decline in power than the rest of the scalp. This partial preservation was particularly significant in the slow wave and sigma bands. The effect of age on sleep EEG varies substantially by region and frequency band. This non-uniformity should inform the design of future investigations of aging and sleep. This study provides normative data on the effect of age on sleep EEG topography, and provides a basis from which to explore the mechanisms of normal aging as well as neurodegenerative disorders for which age is a risk factor.

Precaution for volume conduction in rodent cortical electroencephalography using high-density polyimide-based microelectrode arrays on the skull

In humans, significant progress has been made to link spatial changes in electroencephalographic (EEG) spectral density, connectivity strength, and phase-amplitude modulation to neurological, physiological, and psychological correlates. In contrast, standard rodent EEG techniques employ only few electrodes, which results in poor spatial resolution. Recently, a technique was developed to overcome this limitation in mice. This technique was based on a polyimide-based microelectrode (PBM) array applied on the mouse skull, maintaining a significant number of electrodes with consistent contact, electrode impedance, and mechanical stability. The present study built on this technique by extending it to rats. Therefore, a similar PBM array, but adapted to rats, was designed and fabricated. In addition, this array was connected to a wireless EEG headstage, allowing recording in untethered, freely moving rats. The advantage of a high-density array relies on the assumption that the signal recorded from the different electrodes is generated from distinct sources, i.e., not volume-conducted. Therefore, the utility and validity of the array were evaluated by determining the level of synchrony between channels due to true synchrony or volume conduction during basal vigilance states and following a subanesthetic dose of ketamine. Although the PBM array allowed recording with high signal quality, under both drug and drug-free conditions, high synchronization existed due to volume conduction between the electrodes even in the higher spectral frequency range. Discrimination existed only between frontally and centrally/distally grouped electrode pairs. Therefore, caution should be used in interpreting spatial data obtained from high-density PBM arrays in rodents.

Slow sleep spindle and procedural memory consolidation in patients with major depressive disorder

INTRODUCTION

Evidence has accumulated, which indicates that, in healthy individuals, sleep enhances procedural memory consolidation, and that sleep spindle activity modulates this process. However, whether sleep-dependent procedural memory consolidation occurs in patients medicated for major depressive disorder remains unclear, as are the pharmacological and physiological mechanisms that underlie this process.

METHODS

Healthy control participants (n=17) and patients medicated for major depressive disorder (n=11) were recruited and subjected to a finger-tapping motor sequence test (MST; nondominant hand) paradigm to compare the averaged scores of different learning phases (presleep, postsleep, and overnight improvement). Participants' brain activity was recorded during sleep with 16 electroencephalography channels (between MSTs). Sleep scoring and frequency analyses were performed on the electroencephalography data. Additionally, we evaluated sleep spindle activity, which divided the spindles into fast-frequency spindle activity (12.5-16 Hz) and slow-frequency spindle activity (10.5-12.5 Hz).

RESULT

Sleep-dependent motor memory consolidation in patients with depression was impaired in comparison with that in control participants. In patients with depression, age correlated negatively with overnight improvement. The duration of slow-wave sleep correlated with the magnitude of motor memory consolidation in patients with depression, but not in healthy controls. Slow-frequency spindle activity was associated with reduction in the magnitude of motor memory consolidation in both groups.

CONCLUSION

Because the changes in slow-frequency spindle activity affected the thalamocortical network dysfunction in patients medicated for depression, dysregulated spindle generation may impair sleep-dependent memory consolidation. Our findings may help to elucidate the cognitive deficits that occur in patients with major depression both in the waking state and during sleep.

Local Slow Waves in Superficial Layers of Primary Cortical Areas during REM Sleep

Sleep is traditionally constituted of two global behavioral states, non-rapid eye movement (NREM) and rapid eye movement (REM), characterized by quiescence and reduced responsiveness to sensory stimuli [1]. NREM sleep is distinguished by slow waves and spindles throughout the cerebral cortex and REM sleep by an "activated," low-voltage fast electroencephalogram (EEG) paradoxically similar to that of wake, accompanied by rapid eye movements and muscle atonia. However, recent evidence has shown that cortical activity patterns during wake and NREM sleep are not as global as previously thought. Local slow waves can appear in various cortical regions in both awake humans [2] and rodents [3-5]. Intracranial recordings in humans [6] and rodents [4, 7] have shown that NREM sleep slow waves most often involve only a subset of brain regions that varies from wave to wave rather than occurring near synchronously across all cortical areas. Moreover, some cortical areas can transiently "wake up" [8] in an otherwise sleeping brain. Yet until now, cortical activity during REM sleep was thought to be homogenously wake-like. We show here, using local laminar recordings in freely moving mice, that slow waves occur regularly during REM sleep, but only in primary sensory and motor areas and mostly in layer 4, the main target of relay thalamic inputs, and layer 3. This finding may help explain why, during REM sleep, we remain disconnected from the environment even though the bulk of the cortex shows wake-like, paradoxical activation.

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 as a biological problem: an overview of frontiers in sleep research

Sleep is a physiological process not only for the rest of the body but also for several brain functions such as mood, memory, and consciousness. Nevertheless, the nature and functions of sleep remain largely unknown due to its extremely complicated nature and lack of optimized technology for the experiments. Here we review the recent progress in the biology of the mammalian sleep, which covers a wide range of research areas: the basic knowledge about sleep, the physiology of cerebral cortex in sleeping animals, the detailed morphological features of thalamocortical networks, the mechanisms underlying fluctuating activity of autonomic nervous systems during rapid eye movement sleep, the cutting-edge technology of tissue clearing for visualization of the whole brain, the ketogenesis-mediated homeostatic regulation of sleep, and the forward genetic approach for identification of novel genes involved in sleep. We hope this multifaceted review will be helpful for researchers who are interested in the biology of sleep.

Coupling of Thalamocortical Sleep Oscillations Are Important for Memory Consolidation in Humans

Sleep, specifically non-rapid eye movement (NREM) sleep, is thought to play a critical role in the consolidation of recent memories. Two main oscillatory activities observed during NREM, cortical slow oscillations (SO, 0.5–1.0Hz) and thalamic spindles (12–15Hz), have been shown to independently correlate with memory improvement. Yet, it is not known how these thalamocortical events interact, or the significance of this interaction, during the consolidation process. Here, we found that systemic administration of the GABAergic drug (zolpidem) increased both the phase-amplitude coupling between SO and spindles, and verbal memory improvement in humans. These results suggest that thalamic spindles that occur during transitions to the cortical SO Up state are optimal for memory consolidation. Our study predicts that the timely interactions between cortical and thalamic events during consolidation, contribute to memory improvement and is mediated by the level of inhibitory neurotransmission.

Propagated infra-slow intrinsic brain activity reorganizes across wake and slow wave sleep

Propagation of slow intrinsic brain activity has been widely observed in electrophysiogical studies of slow wave sleep (SWS). However, in human resting state fMRI (rs-fMRI), intrinsic activity has been understood predominantly in terms of zero-lag temporal synchrony (functional connectivity) within systems known as resting state networks (RSNs). Prior rs-fMRI studies have found that RSNs are generally preserved across wake and sleep. Here, we use a recently developed analysis technique to study propagation of infra-slow intrinsic blood oxygen level dependent (BOLD) signals in normal adults during wake and SWS. This analysis reveals marked changes in propagation patterns in SWS vs. wake. Broadly, ordered propagation is preserved within traditionally defined RSNs but lost between RSNs. Additionally, propagation between cerebral cortex and subcortical structures reverses directions, and intra-cortical propagation becomes reorganized, especially in visual and sensorimotor cortices. These findings show that propagated rs-fMRI activity informs theoretical accounts of the neural functions of sleep.

Spatial patterns of neuronal activity in rat cerebral cortex during non-rapid eye movement sleep

It is commonly assumed that cortical activity in non-rapid eye movement sleep (NREMS) is spatially homogeneous on the mesoscopic scale. This is partly due to the limited observational scope of common metabolic or imaging methods in sleep. We used the recently developed technique of thallium-autometallography (TlAMG) to visualize mesoscopic patterns of activity in the sleeping cortex with single-cell resolution. We intravenously injected rats with the lipophilic chelate complex thallium diethyldithiocarbamate (TlDDC) during spontaneously occurring periods of NREMS and mapped the patterns of neuronal uptake of the potassium (K+) probe thallium (Tl+). Using this method, we show that cortical activity patterns are not spatially homogeneous during discrete 5-min episodes of NREMS in unrestrained rats-rather, they are complex and spatially diverse. Along with a relative predominance of infragranular layer activation, we find pronounced differences in metabolic activity of neighboring neuronal assemblies, an observation which lends support to the emerging paradigm that sleep is a distributed process with regulation on the local scale.