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

Effects of Aging on Cortical Neural Dynamics and Local Sleep Homeostasis in Mice

Healthy aging is associated with marked effects on sleep, including its daily amount and architecture, as well as the specific EEG oscillations. Neither the neurophysiological underpinnings nor the biological significance of these changes are understood, and crucially the question remains whether aging is associated with reduced sleep need or a diminished capacity to generate sufficient sleep. Here we tested the hypothesis that aging may affect local cortical networks, disrupting the capacity to generate and sustain sleep oscillations, and with it the local homeostatic response to sleep loss. We performed chronic recordings of cortical neural activity and local field potentials from the motor cortex in young and older male C57BL/6J mice, during spontaneous waking and sleep, as well as during sleep after sleep deprivation. In older animals, we observed an increase in the incidence of non-rapid eye movement sleep local field potential slow waves and their associated neuronal silent (OFF) periods, whereas the overall pattern of state-dependent cortical neuronal firing was generally similar between ages. Furthermore, we observed that the response to sleep deprivation at the level of local cortical network activity was not affected by aging. Our data thus suggest that the local cortical neural dynamics and local sleep homeostatic mechanisms, at least in the motor cortex, are not impaired during healthy senescence in mice. This indicates that powerful protective or compensatory mechanisms may exist to maintain neuronal function stable across the life span, counteracting global changes in sleep amount and architecture.

SIGNIFICANCE STATEMENT The biological significance of age-dependent changes in sleep is unknown but may reflect either a diminished sleep need or a reduced capacity to generate deep sleep stages. As aging has been linked to profound disruptions in cortical sleep oscillations and because sleep need is reflected in specific patterns of cortical activity, we performed chronic electrophysiological recordings of cortical neural activity during waking, sleep, and after sleep deprivation from young and older mice. We found that all main hallmarks of cortical activity during spontaneous sleep and recovery sleep after sleep deprivation were largely intact in older mice, suggesting that the well-described age-related changes in global sleep are unlikely to arise from a disruption of local network dynamics within the neocortex.

Anti-correlated cortical networks arise from spontaneous neuronal dynamics at slow timescales

In the highly interconnected architectures of the cerebral cortex, recurrent intracortical loops disproportionately outnumber thalamo-cortical inputs. These networks are also capable of generating neuronal activity without feedforward sensory drive. It is unknown, however, what spatiotemporal patterns may be solely attributed to intrinsic connections of the local cortical network. Using high-density microelectrode arrays, here we show that in the isolated, primary somatosensory cortex of mice, neuronal firing fluctuates on timescales from milliseconds to tens of seconds. Slower firing fluctuations reveal two spatially distinct neuronal ensembles, which correspond to superficial and deeper layers. These ensembles are anti-correlated: when one fires more, the other fires less and vice versa. This interplay is clearest at timescales of several seconds and is therefore consistent with shifts between active sensing and anticipatory behavioral states in mice.

Network Properties in Transitions of Consciousness during Propofol-induced Sedation

Reliable electroencephalography (EEG) signatures of transitions between consciousness and unconsciousness under anaesthesia have not yet been identified. Herein we examined network changes using graph theoretical analysis of high-density EEG during patient-titrated propofol-induced sedation. Responsiveness was used as a surrogate for consciousness. We divided the data into five states: baseline, transition into unresponsiveness, unresponsiveness, transition into responsiveness, and recovery. Power spectral analysis showed that delta power increased from responsiveness to unresponsiveness. In unresponsiveness, delta waves propagated from frontal to parietal regions as a traveling wave. Local increases in delta connectivity were evident in parietal but not frontal regions. Graph theory analysis showed that increased local efficiency could differentiate the levels of responsiveness. Interestingly, during transitions of responsive states, increased beta connectivity was noted relative to consciousness and unconsciousness, again with increased local efficiency. Abrupt network changes are evident in the transitions in responsiveness, with increased beta band power/connectivity marking transitions between responsive states, while the delta power/connectivity changes were consistent with the fading of consciousness using its surrogate responsiveness. These results provide novel insights into the neural correlates of these behavioural transitions and EEG signatures for monitoring the levels of consciousness under sedation.

The Roles of Cortical Slow Waves in Synaptic Plasticity and Memory Consolidation

Sleep plays important roles in sensory and motor memory consolidation. Sleep oscillations, reflecting neural population activity, involve the reactivation of learning-related neurons and regulate synaptic strength and, thereby affect memory consolidation. Among sleep oscillations, slow waves (0.5–4 Hz) are closely associated with memory consolidation. For example, slow-wave power is regulated in an experience-dependent manner and correlates with acquired memory. Furthermore, manipulating slow waves can enhance or impair memory consolidation. During slow wave sleep, inter-areal interactions between the cortex and hippocampus (HC) have been proposed to consolidate declarative memory; however, interactions for non-declarative (HC-independent) memory remain largely uninvestigated. We recently showed that the directional influence in a slow-wave range through a top-down cortical long-range circuit is involved in the consolidation of non-declarative memory. At the synaptic level, the average cortical synaptic strength is known to be potentiated during wakefulness and depressed during sleep. Moreover, learning causes plasticity in a subset of synapses, allocating memory to them. Sleep may help to differentiate synaptic strength between allocated and non-allocated synapses (i.e., improving the signal-to-noise ratio, which may facilitate memory consolidation). Herein, we offer perspectives on inter-areal interactions and synaptic plasticity for memory consolidation during sleep.

Electrophysiological Evidence That the Retrosplenial Cortex Displays a Strong and Specific Activation Phased with Hippocampal Theta during Paradoxical (REM) Sleep

It is widely accepted that cortical neurons are similarly more activated during waking and paradoxical sleep (PS; aka REM) than during slow-wave sleep (SWS). However, we recently reported using Fos labeling that only a few limbic cortical structures including the retrosplenial cortex (RSC) and anterior cingulate cortex (ACA) contain a large number of neurons activated during PS hypersomnia. Our aim in the present study was to record local field potentials and unit activity from these two structures across all vigilance states in freely moving male rats to determine whether the RSC and the ACA are electrophysiologically specifically active during basal PS episodes. We found that theta power was significantly higher during PS than during active waking (aWK) similarly in the RSC and hippocampus (HPC) but not in ACA. Phase-amplitude coupling between HPC theta and gamma oscillations strongly and specifically increased in RSC during PS compared with aWK. It did not occur in ACA. Further, 68% and 43% of the units recorded in the RSC and ACA were significantly more active during PS than during aWK and SWS, respectively. In addition, neuronal discharge of RSC but not of ACA neurons increased just after the peak of hippocampal theta wave. Our results show for the first time that RSC neurons display enhanced spiking in synchrony with theta specifically during PS. We propose that activation of RSC neurons specifically during PS may play a role in the offline consolidation of spatial memories, and in the generation of vivid perceptual scenery during dreaming.SIGNIFICANCE STATEMENT Fifty years ago, Michel Jouvet used the term paradoxical to define REM sleep because of the simultaneous occurrence of a cortical activation similar to waking accompanied by muscle atonia. However, we recently demonstrated using functional neuroanatomy that only a few limbic structures including the retrosplenial cortex (RSC) and anterior cingulate cortex (ACA) are activated during PS. In the present study, we show for the first time that the RSC and ACA contain neurons firing more during PS than in any other state. Further, RSC neurons are firing in phase with the hippocampal theta rhythm. These data indicate that the RSC is very active during PS and could play a key role in memory consolidation taking place during this state.

Role of Somatostatin-Positive Cortical Interneurons in the Generation of Sleep Slow Waves

During non-rapid eye-movement (NREM) sleep, cortical and thalamic neurons oscillate every second or so between ON periods, characterized by membrane depolarization and wake-like tonic firing, and OFF periods, characterized by membrane hyperpolarization and neuronal silence. Cortical slow waves, the hallmark of NREM sleep, reflect near-synchronous OFF periods in cortical neurons. However, the mechanisms triggering such OFF periods are unclear, as there is little evidence for somatic inhibition. We studied cortical inhibitory interneurons that express somatostatin (SOM), because ∼70% of them are Martinotti cells that target diffusely layer I and can block excitatory transmission presynaptically, at glutamatergic terminals, and postsynaptically, at apical dendrites, without inhibiting the soma. In freely moving male mice, we show that SOM+ cells can fire immediately before slow waves and their optogenetic stimulation during ON periods of NREM sleep triggers long OFF periods. Next, we show that chemogenetic activation of SOM+ cells increases slow-wave activity (SWA), slope of individual slow waves, and NREM sleep duration; whereas their chemogenetic inhibition decreases SWA and slow-wave incidence without changing time spent in NREM sleep. By contrast, activation of parvalbumin+ (PV+) cells, the most numerous population of cortical inhibitory neurons, greatly decreases SWA and cortical firing, triggers short OFF periods in NREM sleep, and increases NREM sleep duration. Thus SOM+ cells, but not PV+ cells, are involved in the generation of sleep slow waves. Whether Martinotti cells are solely responsible for this effect, or are complemented by other classes of inhibitory neurons, remains to be investigated.SIGNIFICANCE STATEMENT Cortical slow waves are a defining feature of non-rapid eye-movement (NREM) sleep and are thought to be important for many of its restorative benefits. Yet, the mechanism by which cortical neurons abruptly and synchronously cease firing, the neuronal basis of the slow wave, remains unknown. Using chemogenetic and optogenetic approaches, we provide the first evidence that links a specific class of inhibitory interneurons-somatostatin-positive cells-to the generation of slow waves during NREM sleep in freely moving mice.

Molecular Mechanisms of Sleep Homeostasis in Flies and Mammals

Sleep is homeostatically regulated with sleep pressure accumulating with the increasing duration of prior wakefulness. Yet, a clear understanding of the molecular components of the homeostat, as well as the molecular and cellular processes they sense and control to regulate sleep intensity and duration, remain a mystery. Here, we will discuss the cellular and molecular basis of sleep homeostasis, first focusing on the best homeostatic sleep marker in vertebrates, slow wave activity; second, moving to the molecular genetic analysis of sleep homeostasis in the fruit fly Drosophila; and, finally, discussing more systemic aspects of sleep homeostasis.

Neural Markers of Responsiveness to the Environment in Human Sleep

Sleep is characterized by a loss of behavioral responsiveness. However, recent research has shown that the sleeping brain is not completely disconnected from its environment. How neural activity constrains the ability to process sensory information while asleep is yet unclear. Here, we instructed human volunteers to classify words with lateralized hand responses while falling asleep. Using an electroencephalographic (EEG) marker of motor preparation, we show how responsiveness is modulated across sleep. These modulations are tracked using classic event-related potential analyses complemented by Lempel-Ziv complexity (LZc), a measure shown to track arousal in sleep and anesthesia. Neural activity related to the semantic content of stimuli was conserved in light non-rapid eye movement (NREM) sleep. However, these processes were suppressed in deep NREM sleep and, importantly, also in REM sleep, despite the recovery of wake-like neural activity in the latter. In NREM sleep, sensory activations were counterbalanced by evoked down states, which, when present, blocked further processing of external information. In addition, responsiveness markers correlated positively with baseline complexity, which could be related to modulation in sleep depth. In REM sleep, however, this relationship was reversed. We therefore propose that, in REM sleep, endogenously generated processes compete with the processing of external input. Sleep can thus be seen as a self-regulated process in which external information can be processed in lighter stages but suppressed in deeper stages. Last, our results suggest drastically different gating mechanisms in NREM and REM sleep.

SIGNIFICANCE STATEMENT

Previous research has tempered the notion that sleepers are isolated from their environment. Here, we pushed this idea forward and examined, across all sleep stages, the brain's ability to flexibly process sensory information, up to the decision level. We extracted an EEG marker of motor preparation to determine the completion of the sensory processing chain and explored how it is constrained by baseline and evoked neural activity. In NREM sleep, slow waves elicited by stimuli appeared to block response preparation. We also used a novel analytic approach (Lempel-Ziv complexity) and showed that the ability to process external information correlates with neural complexity. A reversal of the correlation between complexity and motor indices in REM sleep suggests drastically different gating mechanisms across sleep stages.

The Phenomenal Contents and Neural Correlates of Spontaneous Thoughts across Wakefulness, NREM Sleep, and REM Sleep

Thoughts occur during wake as well as during dreaming sleep. Using experience sampling combined with high-density EEG, we investigated the phenomenal qualities and neural correlates of spontaneously occurring thoughts across wakefulness, non-rapid eye movement (NREM) sleep, and REM sleep. Across all states, thoughts were associated with activation of a region of the midcingulate cortex. Thoughts during wakefulness additionally involved a medial prefrontal region, which was associated with metacognitive thoughts during wake. Phenomenologically, waking thoughts had more metacognitive content than thoughts during both NREM and REM sleep, whereas thoughts during REM sleep had a more social content. Together, these results point to a core neural substrate for thoughts, regardless of behavioral state, within the midcingulate cortex, and suggest that medial prefrontal regions may contribute to metacognitive content in waking thoughts.

Fast and slow Ca2+-dependent hyperpolarization mechanisms connect membrane potential and sleep homeostasis

Several lines of evidence indicate that the sleep-wake state of cortical neurons is regulated not only through neuronal projections from the lower brain, but also through the cortical neurons' intrinsic ability to initiate a slow firing pattern related to the slow-wave oscillation observed in electroencephalography of the sleeping brain. Theoretical modeling and experiments with genetic and pharmacological perturbation suggest that ion channels and kinases acting downstream of calcium signaling regulate the cortical-membrane potential and sleep duration. In this review, we introduce possible Ca²⁺-dependent hyperpolarization mechanisms in cortical neurons, in which Ca²⁺ signaling associated with neuronal excitation evokes kinase cascades, and the activated kinases modify ion channels or pumps to regulate the cortical sleep/wake firing mode.

Local aspects of sleep and wakefulness

Slow waves, the hallmark of NREM (Non Rapid Eye Movement) sleep, are not uniformly distributed across the cortical surface, but can occur locally and asynchronously across brain regions. Their regional distribution and amplitude is affected by brain maturation and by time spent awake, mediated in part by experience-dependent changes in synaptic strength. Recent studies have shown that local low-frequency oscillations (<10Hz) can also occur in REM sleep and during wakefulness, leading to region-specific cognitive errors. Local decreases and increases of slow wave activity in posterior brain regions have been linked to the occurrence of dreaming and to unconscious sleep, respectively. Finally, the coexistence of local sleep-like and wake-like patterns in different brain areas is characteristic of several sleep disorders and may offer insights into these conditions.

Ca2+-dependent hyperpolarization hypothesis for mammalian sleep

The detailed molecular mechanisms underlying the regulation of sleep/wake cycles in mammals are elusive. In this regulation, at least two mechanisms with fast and slow time scales are involved. In the faster time scale, a state of non-rapid-eye-movement (NREM) sleep can be microscopically characterized by the millisecond-to-second-order electrical behavior of neurons, namely slow-wave oscillations described by electrophysiology. In the slower time scale, the total duration of NREM sleep is homeostatically regulated by sleep pressure (the need for sleep), which is usually sustained for hours or even days and can be macroscopically described by electroencephalogram (EEG). The longer dynamics of sleep regulation are often explained by the accumulation of sleep-inducing substances (SISs). However, we still do not have a concrete model to connect fast, microscopic dynamics and slow, macroscopic dynamics. In this review, we introduce a recent Ca²⁺-dependent hyperpolarization hypothesis, in which the Ca²⁺-dependent hyperpolarization of cortical-membrane potential induces slow-wave oscillation. Slow dynamics of the Ca²⁺-dependent hyperpolarization pathway might be regulated by recently identified sleep-promoting kinases as well as classical SISs. Therefore, cortical Ca²⁺-dependent hyperpolarization may be a fundamental mechanism connecting fast neural activity to the slow dynamics of sleep pressure.

Promising techniques to illuminate neuromodulatory control of the cerebral cortex in sleeping and waking states

Sleep, a common event in daily life, has clear benefits for brain function, but what goes on in the brain when we sleep remains unclear. Sleep was long regarded as a silent state of the brain because the brain seemingly lacks interaction with the surroundings during sleep. Since the discovery of electrical activities in the brain at rest, electrophysiological methods have revealed novel concepts in sleep research. During sleep, the brain generates oscillatory activities that represent characteristic states of sleep. In addition to electrophysiology, opto/chemogenetics and two-photon Ca²⁺ imaging methods have clarified that the sleep/wake states organized by neuronal and glial ensembles in the cerebral cortex are transitioned by neuromodulators. Even with these methods, however, it is extremely difficult to elucidate how and when neuromodulators spread, accumulate, and disappear in the extracellular space of the cortex. Thus, real-time monitoring of neuromodulator dynamics at high spatiotemporal resolution is required for further understanding of sleep. Toward direct detection of neuromodulator behavior during sleep and wakefulness, in this review, we discuss developing imaging techniques based on the activation of G-protein-coupled receptors that allow for visualization of neuromodulator dynamics.

The neural correlates of dreaming

Consciousness never fades during wake. However, if awakened from sleep, sometimes we report dreams and sometimes no experiences. Traditionally, dreaming has been identified with REM sleep, characterized by a wake-like, globally ‘activated’, high-frequency EEG. However, dreaming also occurs in NREM sleep, characterized by prominent low-frequency activity. This challenges our understanding of the neural correlates of conscious experiences in sleep. Using high-density EEG, we contrasted the presence and absence of dreaming within NREM and REM sleep. In both NREM and REM sleep, reports of dream experience were associated with a local decrease in low-frequency activity in posterior cortical regions. High-frequency activity within these regions correlated with specific dream contents. Monitoring this posterior ‘hot zone’ predicted whether an individual reported dreaming or the absence of experiences during NREM sleep in real time, suggesting that it may constitute a core correlate of conscious experiences in sleep.

Selective activation of a few limbic structures during paradoxical (REM) sleep by the claustrum and the supramammillary nucleus: evidence and function

We review here classical and recent knowledge on the state of the cortex during paradoxical (REM) sleep (PS). Recent data indicate that only a few limbic cortical structures including the anterior cingulate, retrosplenial and medial entorhinal cortices and the dentate gyrus are strongly activated during PS. In contrast, most of the other cortices including the somatosensory ones are rather deactivated during PS. Further, recent results suggest that tonic activation of limbic cortical neurons during PS is due to projections from glutamate neurons of the claustrum and GABA/glutamate neurons of the supramammillary nucleus while their pacing with theta is induced by projections from GABAergic neurons of the medial septum. The limbic structures activated during PS have all been implicated in spatial memory and it is therefore likely that such activation is crucial for memory consolidation.

Sleep & metabolism: The multitasking ability of lateral hypothalamic inhibitory circuitries

The anatomical and functional mapping of lateral hypothalamic circuits has been limited by the numerous cell types and complex, yet unclear, connectivity. Recent advances in functional dissection of input-output neurons in the lateral hypothalamus have identified subset of inhibitory cells as crucial modulators of both sleep-wake states and metabolism. Here, we summarize these recent studies and discuss the multi-tasking functions of hypothalamic circuitries in integrating sleep and metabolism in the mammalian brain.

Emotional arousal modulates oscillatory correlates of targeted memory reactivation during NREM, but not REM sleep

Rapid eye movement (REM) sleep is considered to preferentially reprocess emotionally arousing memories. We tested this hypothesis by cueing emotional vs. neutral memories during REM and NREM sleep and wakefulness by presenting associated verbal memory cues after learning. Here we show that cueing during NREM sleep significantly improved memory for emotional pictures, while no cueing benefit was observed during REM sleep. On the oscillatory level, successful memory cueing during NREM sleep resulted in significant increases in theta and spindle oscillations with stronger responses for emotional than neutral memories. In contrast during REM sleep, solely cueing of neutral (but not emotional) memories was associated with increases in theta activity. Our results do not support a preferential role of REM sleep for emotional memories, but rather suggest that emotional arousal modulates memory replay and consolidation processes and their oscillatory correlates during NREM sleep.

Quantitative electroencephalogram measures in adult obstructive sleep apnea - Potential biomarkers of neurobehavioural functioning

Obstructive sleep apnea (OSA) results in significantly impaired cognitive functioning and increased daytime sleepiness in some patients leading to increased risk of motor vehicle and workplace accidents and reduced productivity. Clinicians often face difficulty in identifying which patients are at risk of neurobehavioural dysfunction due to wide inter-individual variability, and disparity between symptoms and conventional metrics of disease severity such as the apnea hypopnea index. Quantitative electroencephalogram (EEG) measures are determinants of awake neurobehavioural function in healthy subjects. However, the potential value of quantitative EEG (qEEG) measurements as biomarkers of neurobehavioural function in patients with OSA has not been examined. This review summarises the existing literature examining qEEG in OSA patients including changes in brain activity during wake and sleep states, in relation to daytime sleepiness, cognitive impairment and OSA treatment. It will speculate on the mechanisms which may underlie changes in EEG activity and discuss the potential utility of qEEG as a clinically useful predictor of neurobehavioural function in OSA.

Scalp and Source Power Topography in Sleepwalking and Sleep Terrors: A High-Density EEG Study

STUDY OBJECTIVES

To examine scalp and source power topography in sleep arousals disorders (SADs) using high-density EEG (hdEEG).

METHODS

Fifteen adult subjects with sleep arousal disorders (SADs) and 15 age- and gender-matched good sleeping healthy controls were recorded in a sleep laboratory setting using a 256 channel EEG system.

RESULTS

Scalp EEG analysis of all night NREM sleep revealed a localized decrease in slow wave activity (SWA) power (1-4 Hz) over centro-parietal regions relative to the rest of the brain in SADs compared to good sleeping healthy controls. Source modelling analysis of 5-minute segments taken from N3 during the first half of the night revealed that the local decrease in SWA power was prominent at the level of the cingulate, motor, and sensori-motor associative cortices. Similar patterns were also evident during REM sleep and wake. These differences in local sleep were present in the absence of any detectable clinical or electrophysiological sign of arousal.

CONCLUSIONS

Overall, results suggest the presence of local sleep differences in the brain of SADs patients during nights without clinical episodes. The persistence of similar topographical changes in local EEG power during REM sleep and wakefulness points to trait-like functional changes that cross the boundaries of NREM sleep. The regions identified by source imaging are consistent with the current neurophysiological understanding of SADs as a disorder caused by local arousals in motor and cingulate cortices. Persistent localized changes in neuronal excitability may predispose affected subjects to clinical episodes.

Diagnostic Value of Combining Tumor and Inflammatory Markers in Lung Cancer

BACKGROUND

Despite major advances in lung cancer treatment, early detection remains the most promising way of improving outcomes. To detect lung cancer in earlier stages, many serum biomarkers have been tested. Unfortunately, no single biomarker can reliably detect lung cancer. We combined a set of 2 tumor markers and 4 inflammatory or metabolic markers and tried to validate the diagnostic performance in lung cancer.

METHODS

We collected serum samples from 355 lung cancer patients and 590 control subjects and divided them into training and validation datasets. After measuring serum levels of 6 biomarkers (human epididymis secretory protein 4 [HE4], carcinoembryonic antigen [CEA], regulated on activation, normal T cell expressed and secreted [RANTES], apolipoprotein A2 [ApoA2], transthyretin [TTR], and secretory vascular cell adhesion molecule-1 [sVCAM-1]), we tested various sets of biomarkers for their diagnostic performance in lung cancer.

RESULTS

In a training dataset, the area under the curve (AUC) values were 0.821 for HE4, 0.753 for CEA, 0.858 for RANTES, 0.867 for ApoA2, 0.830 for TTR, and 0.552 for sVCAM-1. A model using all 6 biomarkers and age yielded an AUC value of 0.986 and sensitivity of 93.2% (cutoff at specificity 94%). Applying this model to the validation dataset showed similar results. The AUC value of the model was 0.988, with sensitivity of 93.33% and specificity of 92.00% at the same cutoff point used in the validation dataset. Analyses by stages and histologic subtypes all yielded similar results.

CONCLUSIONS

Combining multiple tumor and systemic inflammatory markers proved to be a valid strategy in the diagnosis of lung cancer.

Integrated Information and State Differentiation

Integrated information (Φ) is a measure of the cause-effect power of a physical system. This paper investigates the relationship between Φ as defined in Integrated Information Theory and state differentiation (D), the number of, and difference between potential system states. Here we provide theoretical justification of the relationship between Φ and D, then validate the results using a simulation study. First, we show that a physical system in a state with high Φ necessarily has many elements and specifies many causal relationships. Furthermore, if the average value of integrated information across all states is high, the system must also have high differentiation. Next, we explore the use of D as a proxy for Φ using artificial networks, evolved to have integrated structures. The results show a positive linear relationship between Φ and D for multiple network sizes and connectivity patterns. Finally we investigate the differentiation evoked by sensory inputs and show that, under certain conditions, it is possible to estimate integrated information without a direct perturbation of its internal elements. In concluding, we discuss the need for further validation on larger networks and explore the potential applications of this work to the empirical study of consciousness, especially concerning the practical estimation of Φ from neuroimaging data.

The Case of the Disappearing Spindle Burst

Sleep spindles are brief cortical oscillations at 10–15 Hz that occur predominantly during non-REM (quiet) sleep in adult mammals and are thought to contribute to learning and memory. Spindle bursts are phenomenologically similar to sleep spindles, but they occur predominantly in early infancy and are triggered by peripheral sensory activity (e.g., by retinal waves); accordingly, spindle bursts are thought to organize neural networks in the developing brain and establish functional links with the sensory periphery. Whereas the spontaneous retinal waves that trigger spindle bursts in visual cortex are a transient feature of early development, the myoclonic twitches that drive spindle bursts in sensorimotor cortex persist into adulthood. Moreover, twitches—and their associated spindle bursts—occur exclusively during REM (active) sleep. Curiously, despite the persistence of twitching into adulthood, twitch-related spindle bursts have not been reported in adult sensorimotor cortex. This raises the question of whether such spindle burst activity does not occur in adulthood or, alternatively, occurs but has yet to be discovered. If twitch-related spindle bursts do occur in adults, they could contribute to the calibration, maintenance, and repair of sensorimotor systems.