Interplay between spontaneous and induced brain activity during human non-rapid eye movement sleep

Humans are less responsive to the surrounding environment during sleep. However, the extent to which the human brain responds to external stimuli during sleep is uncertain. We used simultaneous EEG and functional MRI to characterize brain responses to tones during wakefulness and non-rapid eye movement (NREM) sleep. Sounds during wakefulness elicited responses in the thalamus and primary auditory cortex. These responses persisted in NREM sleep, except throughout spindles, during which they became less consistent. When sounds induced a K complex, activity in the auditory cortex was enhanced and responses in distant frontal areas were elicited, similar to the stereotypical pattern associated with slow oscillations. These data show that sound processing during NREM sleep is constrained by fundamental brain oscillatory modes (slow oscillations and spindles), which result in a complex interplay between spontaneous and induced brain activity. The distortion of sensory information at the thalamic level, especially during spindles, functionally isolates the cortex from the environment and might provide unique conditions favorable for off-line memory processing.     

Coupling between slow waves and sharp-wave ripples engages distributed neural activity during sleep in humans

Hippocampal-dependent memory consolidation during sleep is hypothesized to depend on the synchronization of distributed neuronal ensembles, organized by the hippocampal sharp-wave ripples (SWRs, 80 to 150 Hz), subcortical/cortical slow-wave activity (SWA, 0.5 to 4 Hz), and sleep spindles (SP, 7 to 15 Hz). However, the precise role of these interactions in synchronizing subcortical/cortical neuronal activity is unclear. Here, we leverage intracranial electrophysiological recordings from the human hippocampus, amygdala, and temporal and frontal cortices to examine activity modulation and cross-regional coordination during SWRs. Hippocampal SWRs are associated with widespread modulation of high-frequency activity (HFA, 70 to 200 Hz), a measure of local neuronal activation. This peri-SWR HFA modulation is predicted by the coupling between hippocampal SWRs and local subcortical/cortical SWA or SP. Finally, local cortical SWA phase offsets and SWR amplitudes predicted functional connectivity between the frontal and temporal cortex during individual SWRs. These findings suggest a selection mechanism wherein hippocampal SWR and cortical slow-wave synchronization governs the transient engagement of distributed neuronal populations supporting hippocampal-dependent memory consolidation.

Memory consolidation involves the transformation of newly encoded representations into long-term memory (1–3). During non-rapid eye movement (NREM) sleep, hippocampal representations of recent experiences are reactivated (4, 5), along with transient synchronization of distributed subcortical and cortical neuronal populations (6, 7). It is hypothesized that the oscillatory synchrony facilitates connections between the neuronal ensembles, stabilizing memory representations (8). The selection and synchronization of distant neuronal populations that participate in hippocampal-dependent memory consolidation are proposed to depend on the interaction between hippocampal sharp-wave ripples (SWRs, 80 to 150 Hz), traveling subcortical/cortical slow-wave activity (SWA, 0.5 to 4 Hz), and sleep spindles (SP, 7 to 15Hz), but the underlying mechanisms subserving this network engagement are unclear. Here, we investigated how hippocampal SWRs and subcortical/cortical slow waves and spindles coordinate distributed neuronal populations during memory consolidation in NREM sleep.Hippocampal SWRs are transient local field potential oscillations (20 to 100 ms; 80 to 150 Hz in humans) implicated in planning, memory retrieval, and memory consolidation (9). Several lines of evidence highlight the role of SWRs in sleep-dependent memory consolidation. First, memory reactivation in the hippocampus, cortical, and subcortical structures peaks during SWRs (4–7, 10, 11). Second, hippocampal–subcortical/cortical functional connectivity, the prerequisite for binding of anatomically distributed reactivated memory traces is enhanced around SWRs (7, 12–15). Finally, SWR suppression interferes with, while prolongation of SWR duration improves hippocampal-dependent memory consolidation (16, 17).While research converges on the notion that SWR output modulates neuronal activity across brain regions during NREM sleep, SWR events are temporally biased by phases of SWA and SWA-nested SP (18–20). SWA and SP are present in cortical and subcortical structures (21, 22), originate in frontal areas, and traverse in an orderly succession to temporal lobes and subcortical structures, including the hippocampus (18, 22–24). Indeed, SWA synchrony increases following learning, and the reduction of SWA synchrony is correlated with memory impairment (25). Finally, although SWA is ubiquitous, individual SWA trajectories are usually limited to a subset of cortical/subcortical areas, with ∼80% of these events detected in less than half of recorded locations in humans (22). Therefore, each SWR-associated SWA event could recruit and index a unique sequence of cortical and subcortical populations.In this study, we used the broadband high-frequency activity (HFA, 70 to 200 Hz) recorded from human intracranial electrodes as a metric of subcortical/cortical activity. HFA is an indirect measure of multiunit spiking from the population surrounding the electrode contact (26), estimated in the range of several hundred thousand neurons. Consistent with the hypothesized role of SWR in synchronizing distributed memory traces, we found HFA power modulation during hippocampal SWR events in ∼30% of extrahippocampal recording sites. Given the critical role of SWA in facilitating hippocampal-dependent memory consolidation (13) and their confinement to local regions (22), we hypothesize that interplay between SWA and SWRs organizes hippocampal–cortical and cortical–cortical interactions during SWR events. Indeed, we found a strong association between SWR phase locking to extrahippocampal SWA or SP and HFA modulation in the same recording site. Interestingly, while the SWR–SWA phase locking was present bilaterally, the SWR–SP phase locking was limited to the hemisphere of SWR origin. These findings suggest that coupling between the hippocampal SWRs and extrahippocampal SWA/SP drives the selection of cortical populations to participate in hippocampal–cortical communication. In addition, theoretical constructs of memory consolidation predict transient synchronization of neuronal populations in distant cortical regions during hippocampal SWRs. Based on the widespread presence of SWA during NREM sleep, SWA–SWR temporal coupling, and ability of SWA to synchronize large cortical areas, we hypothesized that the pairwise phase relation between the SWA in different cortical locations could predict the functional coupling between the local cortical populations during SWR windows. In support of the cooperative role of SWR and SWA in orchestrating cortical–cortical communication, we found that SWA phase alignments between two distant cortical sites predicted their neuronal population synchronization during individual SWR windows, manifested by temporal HFA power correlations. The amplitude of individual SWRs was another strong predictor of cortico–cortical coupling, while the combination of SWA phase difference and SWR amplitude outperformed the predictive accuracy of the phase difference or SWA amplitude individually. These results imply a recruitment mechanism by which interplay of SWA and SWRs provides communication windows for long-range interactions between distributed neuronal populations, critical for hippocampal-dependent memory consolidation.     

Source modeling sleep slow waves

Slow waves are the most prominent electroencephalographic (EEG) feature of sleep. These waves arise from the synchronization of slow oscillations in the membrane potentials of millions of neurons. Scalp-level studies have indicated that slow waves are not instantaneous events, but rather they travel across the brain. Previous studies of EEG slow waves were limited by the poor spatial resolution of EEGs and by the difficulty of relating scalp potentials to the activity of the underlying cortex. Here we use high-density EEG (hd-EEG) source modeling to show that individual spontaneous slow waves have distinct cortical origins, propagate uniquely across the cortex, and involve unique subsets of cortical structures. However, when the waves are examined en masse, we find that there are diffuse hot spots of slow wave origins centered on the lateral sulci. Furthermore, slow wave propagation along the anterior−posterior axis of the brain is largely mediated by a cingulate highway. As a group, slow waves are associated with large currents in the medial frontal gyrus, the middle frontal gyrus, the inferior frontal gyrus, the anterior cingulate, the precuneus, and the posterior cingulate. These areas overlap with the major connectional backbone of the cortex and with many parts of the default network.     

儿童癫痫伴慢波睡眠期持续棘慢波综合征临床特征及预后

目的 加强对癫痫伴慢波睡眠期持续棘慢波(CSWS)临床、脑电图特征的认识,强调早期诊断及治疗的重要性.方法 回顾性分析5例CSWS患者临床、脑电图特征及治疗情况,并对患者进行6个月～1.5a随访.结果 5例患者,男3例、女2例,癫痫起病年龄1岁1个月～7岁8个月.2例存在脑部静止性病变,3例头影像学未见异常.4例患者以夜间发作首发,1例以清醒期全面强直阵挛发作起病,逐渐出现全面性脑功能减退,脑电图具备特征性慢波睡眠期持续性放电.4例在激素治疗3个月后临床症状及脑电图明显改善,1例激素治疗6个月后复发.结论 CSWS早期表现不典型,早期诊断及激素治疗可改善患者认知.     

Sleep,Brain, and Cognition Special Feature: Understanding the roles of central and autonomic activity during sleep in the improvement of working memory and episodic memory

The last decade has seen significant progress in identifying sleep mechanisms that support cognition. Most of these studies focus on the link between electrophysiological events of the central nervous system during sleep and improvements in different cognitive domains, while the dynamic shifts of the autonomic nervous system across sleep have been largely overlooked. Recent studies, however, have identified significant contributions of autonomic inputs during sleep to cognition. Yet, there remain considerable gaps in understanding how central and autonomic systems work together during sleep to facilitate cognitive improvement. In this article we examine the evidence for the independent and interactive roles of central and autonomic activities during sleep and wake in cognitive processing. We specifically focus on the prefrontal–subcortical structures supporting working memory and mechanisms underlying the formation of hippocampal-dependent episodic memory. Our Slow Oscillation Switch Model identifies separate and competing underlying mechanisms supporting the two memory domains at the synaptic, systems, and behavioral levels. We propose that sleep is a competitive arena in which both memory domains vie for limited resources, experimentally demonstrated when boosting one system leads to a functional trade-off in electrophysiological and behavioral outcomes. As these findings inevitably lead to further questions, we suggest areas of future research to better understand how the brain and body interact to support a wide range of cognitive domains during a single sleep episode.     

Memory stabilization with targeted reactivation during human slow-wave sleep

It is believed that neural representations of recent experiences become reactivated during sleep, and that this process serves to stabilize associated memories in long-term memory. Here, we initiated this reactivation process for specific memories during slow-wave sleep. Participants studied 50 object-location associations with object-related sounds presented concurrently. For half of the associations, the related sounds were re-presented during subsequent slow-wave sleep while participants underwent functional MRI. Compared with control sounds, related sounds were associated with increased activation of right parahippocampal cortex. Postsleep memory accuracy was positively correlated with sound-related activation during sleep in various brain regions, including the thalamus, bilateral medial temporal lobe, and cerebellum. In addition, postsleep memory accuracy was also positively correlated with pre- to postsleep changes in parahippocampal-medial prefrontal connectivity during retrieval of reactivated associations. Our results suggest that the brain is differentially activated by studied and unstudied sounds during deep sleep and that the thalamus and medial temporal lobe are involved in establishing the mnemonic consequences of externally triggered reactivation of associative memories.     

Slow oscillation electrical brain stimulation during waking promotes EEG theta activity and memory encoding

The application of transcranial slow oscillation stimulation (tSOS; 0.75 Hz) was previously shown to enhance widespread endogenous EEG slow oscillatory activity when applied during a sleep period characterized by emerging endogenous slow oscillatory activity. Processes of memory consolidation typically occurring during this state of sleep were also enhanced. Here, we show that the same tSOS applied in the waking brain also induced an increase in endogenous EEG slow oscillations (0.4–1.2 Hz), although in a topographically restricted fashion. Applied during wakefulness tSOS, additionally, resulted in a marked and widespread increase in EEG theta (4–8 Hz) activity. During wake, tSOS did not enhance consolidation of memories when applied after learning, but improved encoding of hippocampus-dependent memories when applied during learning. We conclude that the EEG frequency and related memory processes induced by tSOS critically depend on brain state. In response to tSOS during wakefulness the brain transposes stimulation by responding preferentially with theta oscillations and facilitated encoding.     

Spontaneous local variations in ongoing neural activity bias perceptual decisions

Neural variability in responding to identical repeated stimuli has been related to trial-by-trial fluctuations in ongoing activity, yet the neural and perceptual consequences of these fluctuations remain poorly understood. Using functional neuroimaging, we recorded brain activity in subjects who reported perceptual decisions on an ambiguous figure, Rubin's vase-faces picture, which was briefly presented at variable intervals of ≥20 s. Prestimulus activity in the fusiform face area, a cortical region preferentially responding to faces, was higher when subjects subsequently perceived faces instead of the vase. This finding suggests that endogenous variations in prestimulus neuronal activity biased subsequent perceptual inference. Furnishing evidence that evoked sensory responses, we then went on to show that the pre- and poststimulus activity interact in a nonlinear way and the ensuing perceptual decisions depend upon the prestimulus context in which they occur.     

Effect of slow wave and REM sleep on thyropharyngeus and stylopharyngeus activity during induced central apneas

The pharyngeal constrictors have been hypothesized to play an important role in the regulation of upper airway (UAW) patency in patients with sleep apnea. However, little research has focused on the activation and control of muscles that determine the lateral and posterior wall of the retropalatal airway dimensions. Our aim was to investigate the effects of slow wave sleep (SWS) and rapid eye movement (REM) sleep on the activation of pharyngeal constrictor (thyropharyngeus; TP) and dilator (stylopharyngeus; SP) muscles during eupneic breathing and induced central apneas. In nine goats, we found that eupneic TP and SP activity progressively decreased from awake to SWS (57 and 56%, respectively; P<0.01) and further in REM (25.6 and 19.9%, respectively; P<0.01). In contrast, diaphragm activity decreased equally during SWS and REM (89.3 and 87.7%, respectively; P<0.01) compared to awake. Following induced apneas while SP activity was eliminated in every state, maximal TP activity was highest in awake state (318.6% of control; P<0.02), less in SWS (157.6%; P<0.02), and nearly absent in REM (117.3%; P>0.02). During the recovery from an induced apnea when diaphragm activity was at 95% of its' control, awake TP activity remained significantly elevated and SP reduced (P>0.02) while TP activity during SWS was elevated and SP had returned to control level. During REM, TP and SP activity were not different from their reduced controls (P>0.02). The data supports our hypotheses that SWS and REM sleep causes a reduction in the eupneic TP and SP activity, as well as a reduction in TP response to induced apneas. However, the relative imbalance in TP vs SP activity during the recovery from an apnea (awake and SWS) suggest that an imbalance of active neuromuscular forces may contribute to upper airway narrowing in mixed apneas, but not in central apnea during sleep.     

From the Cover: A role for cortical nNOS/NK1 neurons in coupling homeostatic sleep drive to EEG slow wave activity

Although the neural circuitry underlying homeostatic sleep regulation is little understood, cortical neurons immunoreactive for neuronal nitric oxide synthase (nNOS) and the neurokinin-1 receptor (NK1) have been proposed to be involved in this physiological process. By systematically manipulating the durations of sleep deprivation and subsequent recovery sleep, we show that activation of cortical nNOS/NK1 neurons is directly related to non-rapid eye movement (NREM) sleep time, NREM bout duration, and EEG δ power during NREM sleep, an index of preexisting homeostatic sleep drive. Conversely, nNOS knockout mice show reduced NREM sleep time, shorter NREM bouts, and decreased power in the low δ range during NREM sleep, despite constitutively elevated sleep drive. Cortical NK1 neurons are still activated in response to sleep deprivation in these mice but, in the absence of nNOS, they are unable to up-regulate NREM δ power appropriately. These findings support the hypothesis that cortical nNOS/NK1 neurons translate homeostatic sleep drive into up-regulation of NREM δ power through an NO-dependent mechanism.The electrical activity of the cerebral cortex has been used to distinguish sleep vs. wakefulness since the earliest EEG studies of sleep (1). Several neural circuits have been implicated in the synchronization and desynchronization of cortical activity that distinguish non-rapid eye movement sleep (NREM) from wakefulness and rapid eye movement sleep (REM). Input from the basal forebrain (BF), likely from both cholinergic and noncholinergic neurons, is critical for the desynchronized EEG characteristic of wakefulness and REM (2, 3). Synchronization of the EEG during NREM depends on thalamic as well as intrinsic cortical oscillators (4).The firing rate of cortical neurons has generally been reported to be reduced during NREM relative to wakefulness and REM (5, 6). A few studies have reported cortical neurons with the opposite pattern. For example, 4 of 177 neurons in the monkey orbitofrontal cortex increased their firing rates during NREM (7). In the cat parietal cortex, 25% of neurons discharged in phase with NREM slow waves during up states but ceased firing during quiet wakefulness (8).Using Fos immunohistochemistry as a marker of cellular activity, we described a population of cortical GABAergic interneurons that are activated during sleep in three species (9, 10). These neurons express neuronal nitric oxide synthase (nNOS) and thus likely release nitric oxide (NO) as well as GABA (11). The percentage of activated cortical nNOS neurons was proportional to NREM δ energy (NRDE), the product of NREM time and NREM EEG δ power. Because NREM time and δ power increase in response to prolonged wakefulness through a regulated process referred to as sleep homeostasis, NRDE is an electrophysiological marker of homeostatic sleep “drive.” Consequently, activation of cortical nNOS neurons during sleep seems to be related to the sleep need that accrues during wakefulness.Cortical nNOS neurons receive cholinergic (12), monoaminergic (13), and peptidergic (14, 15) inputs. Sleep-active nNOS cells correspond to type I nNOS neurons, which are larger and less numerous than type II cells, express the neurokinin-1 receptor (NK1; 14, 15), and are likely projection neurons (16, 17). On the basis of these observations, we have proposed that cortical nNOS/NK1 neurons are fundamentally related to the homeostatic regulation of sleep and play a critical role in coordinating slow waves within the cortex, possibly through release of NO (18).To further test this hypothesis, we subjected rats to varying durations of sleep deprivation (SD) and recovery sleep opportunities (RS) and evaluated which sleep parameters were most closely correlated with cortical nNOS/NK1 neuron activation. We then asked whether those sleep parameters were altered in nNOS KO mice. Consistent with a role for cortical nNOS/NK1 neurons in sleep homeostasis, we find that these neurons are most active during consolidated NREM with increased δ power, that the absence of nNOS results in attenuation of NREM consolidation and NREM δ power, and that nNOS KO mice are unable to respond appropriately to challenges to the sleep homeostatic system.     

Widespread ripples synchronize human cortical activity during sleep,waking, and memory recall

Declarative memory encoding, consolidation, and retrieval require the integration of elements encoded in widespread cortical locations. The mechanism whereby such “binding” of different components of mental events into unified representations occurs is unknown. The “binding-by-synchrony” theory proposes that distributed encoding areas are bound by synchronous oscillations enabling enhanced communication. However, evidence for such oscillations is sparse. Brief high-frequency oscillations (“ripples”) occur in the hippocampus and cortex and help organize memory recall and consolidation. Here, using intracranial recordings in humans, we report that these ∼70-ms-duration, 90-Hz ripples often couple (within ±500 ms), co-occur (≥ 25-ms overlap), and, crucially, phase-lock (have consistent phase lags) between widely distributed focal cortical locations during both sleep and waking, even between hemispheres. Cortical ripple co-occurrence is facilitated through activation across multiple sites, and phase locking increases with more cortical sites corippling. Ripples in all cortical areas co-occur with hippocampal ripples but do not phase-lock with them, further suggesting that cortico-cortical synchrony is mediated by cortico-cortical connections. Ripple phase lags vary across sleep nights, consistent with participation in different networks. During waking, we show that hippocampo-cortical and cortico-cortical coripples increase preceding successful delayed memory recall, when binding between the cue and response is essential. Ripples increase and phase-modulate unit firing, and coripples increase high-frequency correlations between areas, suggesting synchronized unit spiking facilitating information exchange. co-occurrence, phase synchrony, and high-frequency correlation are maintained with little decrement over very long distances (25 cm). Hippocampo-cortico-cortical coripples appear to possess the essential properties necessary to support binding by synchrony during memory retrieval and perhaps generally in cognition.

Ripples are brief high-frequency oscillations that have been well-studied in the rodent hippocampus during non-rapid eye movement sleep (NREM), when they mark the replay of events from the previous waking period, and are critical for memory consolidation in the cortex (1–4). Recently, ripples were found in rat association cortex but not primary sensory or motor cortices during sleep, with increased coupling to hippocampal ripples in sleep following learning (5). An earlier study reported ripples in waking and sleeping cat cortex, especially NREM (6). In humans, cortical ripples have recently been identified during waking and were more frequently found in lateral temporal than in rolandic cortex. Hippocampal sharpwave-ripple occurrence and ripple coupling between parahippocampal gyrus and temporal association cortex increase preceding memory recall in humans (7, 8), possibly facilitating replay of cortical neuron firing sequences established during encoding (9). In rats, ripples co-occur between hippocampus and ∼1 mm² of parietal cortex in sleep following learning (5), in mice, ripples propagate from the hippocampus to retrosplenial cortex (10), and in cats, ripple co-occurrence is reportedly limited to short distances (6).We recently reported, using human intracranial recordings, that ∼70-ms-long, ∼90-Hz ripples are ubiquitous in all regions of the cortex during NREM as well as waking (11). During waking, cortical ripples occur on local high-frequency activity peaks. During sleep, cortical ripples typically occur on the cortical down-to-upstate transition, often with 10- to 16-Hz cortical sleep spindles, and local unit firing patterns consistent with generation by pyramidal-interneuron feedback. We found that cortical ripples group cofiring within the window of spike-timing-dependent plasticity. These findings are consistent with cortical ripples contributing to memory consolidation during NREM in humans.While there is thus an emerging appreciation that hippocampal and cortical ripples have an important role in human and rodent memory, nothing is known of the network properties of cortical ripples. Specifically, it is not known if ripples co-occur or phase-synchronize between cortical sites and, if so, whether this is affected by distance or correlated with the reconstruction of declarative memories. These would be critical properties for cortical ripples to participate in the binding of different elements of memories that are represented in disparate cortical areas, the essence of hippocampus-dependent memory (12).The binding of disparate elements of a memory is a specific case of a more general problem of how the various contents of a mental event are united into a single experience. Most often addressed is how different visual qualities of an object (e.g., color, shape, location, and texture) are associated with each other (13), but the “binding problem” generalizes to how the contents of awareness are unified in a single stream of consciousness (14). Modern accounts often rely on hierarchical and multimodal convergence. However, cortical processing is distributed, and it would be difficult to represent the combinatorial possibilities contained in all potential experiences with convergence, leading to the suggestion that temporal synchrony binds cortical areas (15). This hypothesis was first supported by phase-locked unit firing and local field potentials (LFPs) at 40 to 60 Hz evoked by simple visual stimuli in the anesthetized cat primary visual cortex at distances <7 mm (16). Although some further studies found similar results in other cortical areas, behaviors, and species, as would be expected under the binding-by-synchrony hypothesis (17, 18), others have been less successful (19). Synchronous high-gamma oscillations have also been criticized as providing no mechanism for neuronal interaction beyond generic activation (19, 20).Here, using human intracranial stereoelectroencephalography (SEEG) recordings, we find that ripples co-occur and, remarkably, phase-synchronize across all lobes and between both hemispheres, with little decrement, even at long distances. Furthermore, ripple co-occurrence is enhanced between cortical sites as well as between the cortex and hippocampus preceding successful delayed recall. Corippling was progressively above that expected as it involved a larger proportion of sites, and this led to progressively stronger phase locking. Single-unit firing increased during, and phase-locked to, cortical ripples, providing a basic requirement for ripples to enhance communication via gain modulation and coincidence detection. Enhanced communication was supported by our finding of increased high-frequency correlation between even distant corippling regions. These characteristics suggest that distributed, phase-locked cortical ripples possess the properties that may allow them to help integrate different components of a memory. More generally, ripples may help to “bind” different aspects of a mental event encoded in widespread cortical areas into a coherent representation.     

Rhythmic alternating patterns of brain activity distinguish rapid eye movement sleep from other states of consciousness

Rapid eye movement (REM) sleep constitutes a distinct “third state” of consciousness, during which levels of brain activity are commensurate with wakefulness, but conscious awareness is radically transformed. To characterize the temporal and spatial features of this paradoxical state, we examined functional interactions between brain regions using fMRI resting-state connectivity methods. Supporting the view that the functional integrity of the default mode network (DMN) reflects “level of consciousness,” we observed functional uncoupling of the DMN during deep sleep and recoupling during REM sleep (similar to wakefulness). However, unlike either deep sleep or wakefulness, REM was characterized by a more widespread, temporally dynamic interaction between two major brain systems: unimodal sensorimotor areas and the higher-order association cortices (including the DMN), which normally regulate their activity. During REM, these two systems become anticorrelated and fluctuate rhythmically, in reciprocally alternating multisecond epochs with a frequency ranging from 0.1 to 0.01 Hz. This unique spatiotemporal pattern suggests a model for REM sleep that may be consistent with its role in dream formation and memory consolidation.     

Learning increases human electroencephalographic coherence during subsequent slow sleep oscillations

Learning is assumed to induce specific changes in neuronal activity during sleep that serve the consolidation of newly acquired memories. To specify such changes, we measured electroencephalographic (EEG) coherence during performance on a declarative learning task (word pair associations) and subsequent sleep. Compared with a nonlearning control condition, learning performance was accompanied with a strong increase in coherence in several EEG frequency bands. During subsequent non-rapid eye movement sleep, coherence only marginally increased in a global analysis of EEG recordings. However, a striking and robust increase in learning-dependent coherence was found when analyses were performed time-locked to the occurrence of slow oscillations (<1 Hz). Specifically, the surface-positive half-waves of the slow oscillation resulting from widespread cortical depolarization were associated with distinctly enhanced coherence after learning in the slow-oscillatory, delta, slow-spindle, and gamma bands. The findings identify the depolarizing phase of the slow oscillations in humans as a time period particularly relevant for a reprocessing of memories in sleep.     

Rapid eye movement and slow-wave sleep rebound after one night of continuous positive airway pressure for obstructive sleep apnoea

Background and objective: Rebound of slow‐wave sleep (SWS) and rapid eye movement (REM) sleep is observed in patients who are on continuous positive airway pressure (CPAP) therapy for obstructive sleep apnoea (OSA); but, neither have been objectively defined. The pressure titration study often represents the first recovery sleep period for patients with OSA. Our aim was to objectively define and identify predictors of SWS and REM sleep rebound following CPAP titration. Methods: Paired diagnostic polysomnography and pressure titration studies from 335 patients were reviewed. Results: The mean apnoea‐hypopnoea index was 40.7 ± 26.1, and minimum oxygen saturation was 76 ± 14.4%. Comparing eight incremental thresholds, a rebound of 20% in REM sleep and a 40% increase in SWS allowed the best separation of prediction models. A 20% rebound in REM sleep was predicted by REM sleep %, non‐REM arousal index (ArI) and total sleep time during diagnostic polysomnography, and male gender (R² = 35.3%). A 40% rebound in SWS was predicted by SWS %, total ArI and REM sleep % during diagnostic polysomnography, and body mass index (R² = 45.4%). Conclusions: A 40% rebound in SWS, but only a 20% rebound in REM sleep on the pressure titration study, is predicted by abnormal sleep architecture and sleep fragmentation prior to the commencement of treatment.     

An assembled electrogastrographic device to examine the meal effect on gastric slow wave

We have assembled an electrogastrographic device based on the main components of amplifiers, a band-pass filter, an analogue/digital converter, low band-pass digital filters and a personal computer. The analysis software uses autoregressive moving average modelling to compute the frequency of slow waves and uses fast Fourier transformation for power spectral computation. Twenty healthy young male volunteers were enrolled in the study to test meal-elicited responses of the slow wave. Subjects underwent a 15 min recording while fasting and then a standard breakfast, which included 250 mL milk and a cake with a total of 1.45 kj, was ingested within 5 min. The post-prandial 15 min recording was immediately resumed after the meal. A slight but significant increase in the frequency of slow waves was seen in post-prandial measurements (mean ± s.d., 0.0506±0.0005 vs 0.0497±0.0005 Hz; P<0.0001). Moreover, a significant enhancement of the power of slow waves was elicited following the meal (36.0±3.1 vs 27.6±3.1 dB; P<0.0001). We conclude that this assembled electrogastrographic device is a reliable means of monitoring gastric myoelectrical activity because the phenomenon of post-prandial responses of slow waves in either frequency or power is well demonstrated.     

������˯�ߺ�����ͣ�ۺ����������������

阻塞性睡眠呼吸暂停综合征(OSAS)是以睡眠时上呼吸道反复塌陷为特征的疾病,常伴日间嗜睡和心脑血管疾病。虽然上气道解剖异常可能与这一疾病的发生有关,但其发生机制尚不完全清楚。最近的一些研究显示,OSAS的发生与呼吸中枢驱动异常有关。文章将介绍呼吸中枢驱动评价方法包括用多导食管电极记录膈肌肌电。研究显示,OSAS事件发生时呼吸中枢驱动事实上是下降而不是增高。     

快速眼动睡眠期的阻塞型呼吸暂停与高血压

快速眼动(REM)睡眠期阻塞型睡眠呼吸暂停(OSA)是指发生在REM期的阻塞型睡眠呼吸暂停综合征,由于REM期交感神经活性异常增高,因此发生在此期的OSA可以使交感神经活性更高,心血管功能更不稳定。目前认为REM-OSA很可能是OSA相关高血压发生的主要原因,并且也可能是目前OSA相关高血压用持续正压通气(CPAP)治疗效果不明显的重要原因。临床工作中应重视对REM-OSA的诊断和治疗,这对OSA相关高血压的防治具有重要意义。