Cardiac activity during sleep onset

Rhythmicity in heart rate and its surges usher a special period of sleep, a likely home for PGO waves

High amplitude electroencephalogram (EEG) events, like unitary K-complex (KC), are used to partition sleep into stages and hence define the hypnogram, a key instrument of sleep medicine. Throughout sleep the heart rate (HR) changes, often as a steady HR increase leading to a peak, what is known as a heart rate surge (HRS). The hypnogram is often unavailable when most needed, when sleep is disturbed and the graphoelements lose their identity. The hypnogram is also difficult to define during normal sleep, particularly at the start of sleep and the periods that precede and follow rapid eye movement (REM) sleep. Here, we use objective quantitative criteria that group together periods that cannot be assigned to a conventional sleep stage into what we call REM0 periods, with the presence of a HRS one of their defining properties. Extended REM0 periods are characterized by highly regular sequences of HRS that generate an infra-low oscillation around 0.05 Hz. During these regular sequence of HRS, and just before each HRS event, we find avalanches of high amplitude events for each one of the mass electrophysiological signals, i.e. related to eye movement, the motor system and the general neural activity. The most prominent features of long REM0 periods are sequences of three to five KCs which we label multiple K-complexes (KCm). Regarding HRS, a clear dissociation is demonstrated between the presence or absence of high gamma band spectral power (55-95 Hz) of the two types of KCm events: KCm events with strong high frequencies (KCmWSHF) cluster just before the peak of HRS, while KCm between HRS show no increase in high gamma band (KCmNOHF). Tomographic estimates of activity from magnetoencephalography (MEG) in pre-KC periods (single and multiple) showed common increases in the cholinergic Nucleus Basalis of Meynert in the alpha band. The direct contrast of KCmWSHF with KCmNOHF showed increases in all subjects in the high sigma band in the base of the pons and in three subjects in both the delta and high gamma bands in the medial Pontine Reticular Formation (mPRF), the putative Long Lead Initial pulse (LLIP) for Ponto-Geniculo-Occipital (PGO) waves.

Multi-Night at-Home Evaluation of Improved Sleep Detection and Classification with a Memory-Enhanced Consumer Sleep Tracker

PURPOSE

To evaluate the benefits of applying an improved sleep detection and staging algorithm on minimally processed multi-sensor wearable data collected from older generation hardware.

PATIENTS AND METHODS

58 healthy, East Asian adults aged 23-69 years (M = 37.10, SD = 13.03, 32 males), each underwent 3 nights of PSG at home, wearing 2^nd Generation Oura Rings equipped with additional memory to store raw data from accelerometer, infra-red photoplethysmography and temperature sensors. 2-stage and 4-stage sleep classifications using a new machine-learning algorithm (Gen3) trained on a diverse and independent dataset were compared to the existing consumer algorithm (Gen2) for whole-night and epoch-by-epoch metrics.

RESULTS

Gen 3 outperformed its predecessor with a mean (SD) accuracy of 92.6% (0.04), sensitivity of 94.9% (0.03), and specificity of 78.5% (0.11); corresponding to a 3%, 2.8% and 6.2% improvement from Gen2 across the three nights, with Cohen's d values >0.39, t values >2.69, and p values <0.01. Notably, Gen 3 showed robust performance comparable to PSG in its assessment of sleep latency, light sleep, rapid eye movement (REM), and wake after sleep onset (WASO) duration. Participants <40 years of age benefited more from the upgrade with less measurement bias for total sleep time (TST), WASO, light sleep and sleep efficiency compared to those ≥40 years. Males showed greater improvements on TST and REM sleep measurement bias compared to females, while females benefitted more for deep sleep measures compared to males.

CONCLUSION

These results affirm the benefits of applying machine learning and a diverse training dataset to improve sleep measurement of a consumer wearable device. Importantly, collecting raw data with appropriate hardware allows for future advancements in algorithm development or sleep physiology to be retrospectively applied to enhance the value of longitudinal sleep studies.

Respiratory, cardiac, EEG, BOLD signals and functional connectivity over multiple microsleep episodes

Falling asleep is common in fMRI studies. By using long eyelid closures to detect microsleep onset, we showed that the onset and termination of short sleep episodes invokes a systematic sequence of BOLD signal changes that are large, widespread, and consistent across different microsleep durations. The signal changes are intimately intertwined with shifts in respiration and heart rate, indicating that autonomic contributions are integral to the brain physiology evaluated using fMRI and cannot be simply treated as nuisance signals. Additionally, resting state functional connectivity (RSFC) was altered in accord with the frequency of falling asleep and in a manner that global signal regression does not eliminate. Our findings point to the need to develop a consensus among neuroscientists using fMRI on how to deal with microsleep intrusions. SIGNIFICANCE STATEMENT: Sleep, breathing and cardiac action are influenced by common brainstem nuclei. We show that falling asleep and awakening are associated with a sequence of BOLD signal changes that are large, widespread and consistent across varied durations of sleep onset and awakening. These signal changes follow closely those associated with deceleration and acceleration of respiration and heart rate, calling into question the separation of the latter signals as 'noise' when the frequency of falling asleep, which is commonplace in RSFC studies, correlates with the extent of RSFC perturbation. Autonomic and central nervous system contributions to BOLD signal have to be jointly considered when interpreting fMRI and RSFC studies.

Lying Awake at Night: Cardiac Autonomic Activity in Relation to Sleep Onset and Maintenance

Insomnia, i.e., difficulties initiating and/or maintaining sleep, is one of the most common sleep disorders. To study underlying mechanisms for insomnia, we studied autonomic activity changes around sleep onset in participants without clinical insomnia but with varying problems with initiating or maintaining sleep quantified as increased sleep onset latency (SOL) and wake after sleep onset (WASO), respectively. Polysomnography and electrocardiography were simultaneously recorded in 176 participants during a single night. Cardiac autonomic activity was assessed using frequency domain analysis of RR intervals and results show that the normalized spectral power in the low frequency band (LF_nu) after sleep onset was significantly higher in participants with long SOL compared to participants with short SOL. Furthermore, the normalized spectral power in the high frequency band (HF_nu) was significantly lower in participants with long SOL as compared to participants with short SOL over 3 time periods (first 10 min in bed intending to sleep, 10 min before, and 10 min after sleep onset). These results suggest that participants with long SOL are more aroused in all three examined time periods when compared to participants with short SOL, especially for young adults (20–40 years). As there is no clear consensus on the cutoff for an increased WASO, we used a data-driven approach to explore different cutoffs to define short WASO and long WASO groups. LF_nu, HF_nu, and LF/HF differed between the long and the short WASO groups. A higher LF_nu and LF/HF and a lower HF_nu was observed in participants with long WASO for most cutoffs. The highest effect size was found using the cutoff of 66 min. Our findings suggest that autonomic cardiac activity has predictive value with respect to sleep characteristics pertaining to sleep onset and maintenance.

Phosphocreatine Levels in the Left Thalamus Decline during Wakefulness and Increase after a Nap

Scientists have hypothesized that the availability of phosphocreatine (PCr) and its ratio to inorganic phosphate (Pi) in cerebral tissue form a substrate of wakefulness. It follows then, according to this hypothesis, that the exhaustion of PCr and the decline in the ratio of PCr to Pi form a substrate of fatigue. We used 31P-magnetic resonance spectroscopy (31P-MRS) to investigate quantitative levels of PCr, the γ-signal of ATP, and Pi in 30 healthy humans (18 female) in the morning, in the afternoon, and while napping (n = 15) versus awake controls (n = 10). Levels of PCr (2.40 mM at 9 A.M.) decreased by 7.0 ± 0.8% (p = 7.1 × 10-6, t = -5.5) in the left thalamus between 9 A.M. and 5 P.M. Inversely, Pi (0.74 mM at 9 A.M.) increased by 17.1 ± 5% (p = 0.005, t = 3.1) and pH levels dropped by 0.14 ± 0.07 (p = 0.002; t = 3.6). Following a 20 min nap after 5 P.M., local PCr, Pi, and pH were restored to morning levels. We did not find respective significant changes in the contralateral thalamus or in other investigated brain regions. Left hemispheric PCr was signficantly lower than right hemispheric PCr only at 5 P.M. in the thalamus and at all conditions in the temporal region. Thus, cerebral daytime-related and sleep-related molecular changes are accessible in vivo Prominent changes were identified in the thalamus. This region is heavily relied on for a series of energy-consuming tasks, such as the relay of sensory information to the cortex. Furthermore, our data confirm that lateralization of brain function is regionally dynamic and includes PCr.SIGNIFICANCE STATEMENT The metabolites phosphocreatine (PCr) and inorganic phosphate (Pi) are assumed to inversely reflect the cellular energy load. This study detected a diurnal decrease of intracellular PCr and a nap-associated reincrease in the left thalamus. Pi behaved inversely. This outcome corroborates the role of the thalamus as a region of high energy consumption in agreement with its function as a gateway that relays and modulates information flow. Conversely to the dynamic lateralization of thalamic PCr, a constantly significant lateralization was observed in other regions. Increasing fatigue over the course of the day may also be a matter of cerebral energy supply. Comparatively fast restoration of that supply may be part of the biological basis for the recreational value of "power napping."

Autonomic cardiac activity in adults with short and long sleep onset latency

Autonomic cardiac activity during sleep has been widely studied. Research has mostly focused on cardiac activity between different sleep stages and wakefulness as well as between normal and pathological sleep. This work investigates autonomic activity changes during sleep onset in healthy subjects with long and short sleep onset latency (SOL). Polysomnography (PSG) and electrocardiography (ECG) were simultaneously recorded in 186 healthy subjects during a single night. Autonomic activity was assessed based on frequency domain analysis of RR intervals and results show that the analysis of RR intervals differs significantly between the short SOL and the long SOL groups. We found that the spectral power in the low frequency band (LF) was significantly higher in the long SOL group compared to the short SOL group in the first 10 minutes in bed intended to sleep. There was no significant difference for LF and the spectral power in the high frequency band (HF) 10 minutes before and after sleep onset between the two groups. Only in the short SOL group there was a significant increase in HF from the first 10 minutes in bed intended to sleep to 10 minutes before SO, while LF decreased significantly in both groups. The effect of time (5.5-min bin) on the heart rate variability (HRV) features around sleep onset showed that both LF and HF differed significantly during the period surrounding sleep onset only in the short SOL group.

Dynamic coupling between the central and autonomic nervous systems during sleep: A review

Sleep is characterized by coordinated cortical and cardiac oscillations reflecting communication between the central (CNS) and autonomic (ANS) nervous systems. Here, we review fluctuations in ANS activity in association with CNS-defined sleep stages and cycles, and with phasic cortical events during sleep (e.g., arousals, K-complexes). Recent novel analytic methods reveal a dynamic organization of integrated physiological networks during sleep and indicate how multiple factors (e.g., sleep structure, age, sleep disorders) affect "CNS-ANS coupling". However, these data are mostly correlational and there is a lack of clarity of the underlying physiology, making it challenging to interpret causality and direction of coupling. Experimental manipulations (e.g., evoking K-complexes or arousals) provide information on the precise temporal sequence of cortical-cardiac activity, and are useful for investigating physiological pathways underlying CNS-ANS coupling. With the emergence of new analytical approaches and a renewed interest in ANS and CNS communication during sleep, future work may reveal novel insights into sleep and cardiovascular interactions during health and disease, in which coupling could be adversely impacted.

Regularity of cardiac rhythm as a marker of sleepiness in sleep disordered breathing

Aim

The present study aimed to analyse the autonomic nervous system activity using heart rate variability (HRV) to detect sleep disordered breathing (SDB) patients with and without excessive daytime sleepiness (EDS) before sleep onset.

Methods

Two groups of 20 patients with different levels of daytime sleepiness -sleepy group, SG; alert group, AG- were selected consecutively from a Maintenance of Wakefulness Test (MWT) and Multiple Sleep Latency Test (MSLT) research protocol. The first waking 3-min window of RR signal at the beginning of each nap test was considered for the analysis. HRV was measured with traditional linear measures and with time-frequency representations. Non-linear measures -correntropy, CORR; auto-mutual-information function, AMIF- were used to describe the regularity of the RR rhythm. Statistical analysis was performed with non-parametric tests.

Results

Non-linear dynamic of the RR rhythm was more regular in the SG than in the AG during the first wakefulness period of MSLT, but not during MWT. AMIF (in high-frequency and in Total band) and CORR (in Total band) yielded sensitivity > 70%, specificity >75% and an area under ROC curve > 0.80 in classifying SG and AG patients.

Conclusion

The regularity of the RR rhythm measured at the beginning of the MSLT could be used to detect SDB patients with and without EDS before the appearance of sleep onset.

The influence of pre-sleep cognitive arousal on sleep onset processes

Cognitive hyperarousal, resulting in enhanced cognitive activation, has been cited as an important contributor to the development and preservation of insomnia. To further understand this process, our study examined the effects of acutely-induced pre-sleep cognitive hyperarousal on sleep onset processes in healthy volunteers. Following an adaptation night, 15 subjects slept two nights in our sleep laboratory: one reference night and another one with cognitive arousal induction, in a counterbalanced order. In the cognitive arousal condition, subjects worked through half an hour of cognitive tasks without interference of an emotional component prior to retiring to bed. Objective sleep onset latency was significantly prolonged in the cognitive arousal condition compared to the reference condition. Significantly more high frequency activity was recorded during the first and second deep-sleep period. Moreover, differences in heart rate and proximal temperature during and after sleep onset were observed in the nights after the cognitive induction. Pre-sleep cognitive activation successfully induced a significant cognitive load and activation in our subjects to influence subsequent sleep (onset) processes.

Acute changes in cardiovascular function during the onset period of daytime sleep: comparison to lying awake and standing

The siesta habit is associated with a 37% reduction in coronary mortality, possibly because of reduced cardiovascular stress associated with daytime sleep. Whether the most important behavior is the daytime nap itself, a supine posture, or the expectancy of a nap is unknown. We present the first detailed description on healthy individuals of the acute changes in cardiovascular function during defined phases of the daytime sleep-onset period. These responses were compared with lying awake and standing. Following a night of restricted (4 h) sleep, nine healthy participants (aged 34 ± 5 yr) were allowed to sleep at 1400 for up to 1 h. Polysomnography was used to calculate three phases of daytime sleep onset: phase 1, a baseline period of relaxed wakefulness before lights out; phase 2, the period between lights out and onset of stage 1 sleep; and phase 3, the period between onsets of stages 1 and 2 sleep. Differences (means ± SD) in blood pressure, heart rate, and forearm cutaneous vascular conductance (CVC) between phases were analyzed. During the 9.7 ± 13.8 min of phase 2, systolic and diastolic blood pressure was 4.7 ± 4.5 and 3.6 ± 2.8 mmHg lower than baseline, whereas CVC was 9.5 ± 4.3% higher than baseline ( P < 0.05). Subsequent changes in cardiovascular function during the sleep itself were trivial ( P > 0.05). The above changes were not observed when subjects stood or laid supine in relaxed wakefulness for 1 h ( P > 0.05). Our findings suggest that the period between lights out and sleep onset is associated with the largest acute reduction in blood pressure during one afternoon siesta.

Central sleep apnea: Pathophysiology and treatment

Central sleep apnea (CSA) is characterized by a lack of drive to breathe during sleep, resulting in repetitive periods of insufficient ventilation and compromised gas exchange. These nighttime breathing disturbances can lead to important comorbidity and increased risk of adverse cardiovascular outcomes. There are several manifestations of CSA, including high altitude-induced periodic breathing, idiopathic CSA, narcotic-induced central apnea, obesity hypoventilation syndrome, and Cheyne-Stokes breathing. While unstable ventilatory control during sleep is the hallmark of CSA, the pathophysiology and the prevalence of the various forms of CSA vary greatly. This brief review summarizes the underlying physiology and modulating components influencing ventilatory control in CSA, describes the etiology of each of the various forms of CSA, and examines the key factors that may exacerbate apnea severity. The clinical implications of improved CSA pathophysiology knowledge and the potential for novel therapeutic treatment approaches are also discussed.

Relationships between sleep, physical activity and human health

Although sleep and exercise may seem to be mediated by completely different physiological mechanisms, there is growing evidence for clinically important relationships between these two behaviors. It is known that passive body heating facilitates the nocturnal sleep of healthy elderly people with insomnia. This finding supports the hypothesis that changes in body temperature trigger somnogenic brain areas to initiate sleep. Nevertheless, little is known about how the core and distal thermoregulatory responses to exercise fit into this hypothesis. Such knowledge could also help in reducing sleep problems associated with nocturnal shiftwork. It is difficult to incorporate physical activity into a shiftworker's lifestyle, since it is already disrupted in terms of family commitments and eating habits. A multi-research strategy is needed to identify what the optimal amounts and timing of physical activity are for reducing shiftwork-related sleep problems. The relationships between sleep, exercise and diet are also important, given the recently reported associations between short sleep length and obesity. The cardiovascular safety of exercise timing should also be considered, since recent data suggest that the reactivity of blood pressure to a change in general physical activity is highest during the morning. This time is associated with an increased risk in general of a sudden cardiac event, but more research work is needed to separate the influences of light, posture and exercise per se on the haemodynamic responses to sleep and physical activity following sleep taken at night and during the day as a nap.

Autonomic changes during wake-sleep transition: a heart rate variability based approach

Autonomic function during sleep and wakefulness has been extensively investigated, however information concerning autonomic changes during the wake to sleep transition is scarce. The objective of the present study was to non-invasively characterize autonomic function and additional physiologic changes during sleep onset in normal and abnormal sleep. The estimation of autonomic function was based on time-frequency analysis of the RR interval series, using the power components in the very-low-frequency range (0.005-0.04 Hz), low-frequency (0.04-0.15 Hz), and high-frequency range (0.15-0.5 Hz). The ratio of low to high frequency power represented the sympathovagal balance. Thirty-four subjects who underwent whole night polysomnography were divided into 3 groups according to their complaints and study results: normal subjects, apneic patients (OSAS), and subjects with various sleep disorders (VSD). The results indicated a significant increase in RR interval during sleep onset, although its variability decreased; respiratory rate did not change, yet respiration became more stable; EMG amplitude and its variability decreased with sleep onset. Very-low-frequency power started to decrease significantly 2 min before sleep onset in all groups; low-frequency power decreased and high-frequency power did not change significantly in all groups, accordingly their ratio decreased and reflected a shift towards parasympathetic predominance. Although autonomic function displayed similar behavior in all subjects, OSAS and VSD patients presented a higher sympathovagal balance reflecting enhanced sympathetic predominance in those groups compared to normal subjects, both before and after sleep onset. All parameters reached a nadir at a defined time point during the process of falling asleep. We conclude that the wake-sleep transition period represents a transitional process between two physiologically different states; this transition starts with a decrease in the very slow oscillations in heart rate that anticipates a step-change resetting of autonomic function, followed by a decrease in sympathovagal balance towards the end of the process.

Control of cerebral blood flow during sleep and the effects of hypoxia

During wakefulness, cerebral blood flow (CBF) is closely coupled to regional cerebral metabolism; however CBF is also strongly modulated by breathing, increasing in response to both hypercapnia and hypoxia. During stage III/IV non-rapid eye (NREM) sleep, cerebral metabolism and CBF decrease whilst the partial pressure of arterial CO2 increases due to a reduction in alveolar ventilation. The reduction in CBF during NREM sleep therefore occurs despite a relative state of hypercapnia. We have used transcranial Doppler ultrasound to determine middle cerebral artery velocity, as an index of CBF, and have determined that NREM sleep is associated with a reduction in the cerebrovascular response to hypercapnia. This reduction in reactivity would, at least in part, allow the observed reductions in CBF in this state. Similarly, we have observed that the CBF response to hypoxia is absent during stage III/IV NREM sleep. Nocturnal hypoxia and hypercapnia are major pathogenic factor associated with cardio-respiratory diseases. These marked changes in cerebrovascular control that occur during sleep suggest that the cerebral circulation may be particularly vulnerable to cardio-respiratory insults during this period.

Cerebral blood flow changes associated with fluctuations in alpha and theta rhythm during sleep onset in humans

Cerebral blood flow (CBF) is typically reduced during stable non-rapid eye movement (non-REM) sleep compared with the waking level. It is not known when in the sleep cycle these changes occur. However, spontaneous fluctuations in alpha and theta rhythm during sleep onset are associated with marked changes in cardio-respiratory control. The aim of this study was to test the hypothesis that changes in CBF would occur during sleep onset and would be related to changes in cortical activity. Middle cerebral artery velocity (MCAV) was measured using transcranial Doppler ultrasound, as an index of CBF, in 10 healthy subjects. Sleep state, ventilation, end tidal carbon dioxide (PET,CO2), arterial oxygen saturation (SaO2), mean arterial blood pressure (MABP) and cardiac R-R interval (RR) were monitored simultaneously. Immediately following the transition from alpha to theta rhythm (the transition from wake to sleep), ventilation decreased by 13.4% and tidal volume (VT) by 12.2% (P<0.01); PET,CO2 increased by 1.9% (P<0.01); respiratory frequency (fR) and SaO2 did not change significantly. MCAV increased by 9.7% (P<0.01); MABP decreased by 3.2% (P<0.01) but RR did not change significantly. Immediately following the transition from theta to alpha rhythm (spontaneous awakening), increased by 13.3% (P<0.01); VT increased by 11.4% (P<0.01); PET,CO2 decreased by 1.9% (P<0.01); MCAV decreased by 11.1% (P<0.01) and MABP decreased by 7.5%; fR, SaO2 and RR did not change significantly. These changes in MCAV during sleep onset cannot be attributed to changes in ventilation or MABP. We speculate that the changes in cerebral vascular tone during sleep onset are mediated neurally, by regulatory mechanisms linked to the changes in cortical state, and that these mechanisms are different from those regulating the longer-term reduction in CBF associated with stable non-REM sleep.

Changes in cardiovascular function during the sleep onset period in young adults

Blood pressure (BP) and heart rate (HR) are influenced by the sleep-wake cycle, with relatively abrupt falls occurring in association with sleep onset (SO). However, the pattern and rate of fall in BP and HR during SO and the processes that contribute to the fall in these variables have not been fully identified. Continuous BP and HR recordings were collected beginning 1 h before lights out (LO) until the end of the first non-rapid eye movement sleep period in 21 young, healthy participants maintained in a supine position. Five consecutive phases were defined: 1) the 30 min of wakefulness before LO; 2) LO to stage 1 sleep; 3) stage 1 to stage 2 sleep; 4) stage 2 sleep to the last microarousal before stable sleep; and 5) the first 30 min of undisturbed stable sleep. The data were analyzed on a beat-by-beat basis and reported as 2-min periods for phases 1 and 5 and 10% epochs for phases 2, 3, and 4 (as participants had variable time periods in these phases). The level of baroreflex (BR) activity was assessed by the sequence technique and an autoregressive multivariate model. Furthermore, during phases 3 and 4, the BP and HR responses to arousal from sleep were determined. There were substantial falls in BP and HR after LO before the initial onset of θ-activity (phase 3) and again after the onset of stable sleep after the cessation of spontaneous arousals. During phases 3 and 4 when there were repeated arousals from sleep, the fall in both variables was retarded. Furthermore, both the rate and magnitude of the fall in BP were negatively associated with the number of arousals during phases 3 and 4. There was a small increase in the sensitivity of the BR and indirect evidence of a substantial fall in its set point.

State transitions between wake and sleep, and within the ultradian cycle, with focus on the link to neuronal activity

The structure of sleep across the night as expressed by the hypnogram, is characterised by repeated transitions between the different states of vigilance: wake, light and deep non-rapid eye movement (NREM) sleep, and rapid eye movement (REM) sleep. This review is concerned with current knowledge on these state transitions, focusing primarily on those findings that allow the integration of data at cellular level with spectral time-course data at the encephalographic (EEG) level. At the cellular level it has been proposed that, under the influence of circadian and homeostatic factors, transitions between wake and sleep may be determined by mutually inhibitory interaction between sleep-active neurons in the hypothalamic preoptic area and wake-active neurons in multiple arousal centres. These two fundamentally different behavioural states are separated by the sleep onset and the sleep inertia periods each characterised by gradual changes in which neither true wake nor true sleep patterns are present. The results of sequential spectral analysis of EEG data on moves towards and away from deep sleep are related to findings at the cellular level on the generating mechanisms giving rise to the various NREM oscillatory modes under the neuromodulatory control of brainstem-thalamic activating systems. And there is substantial evidence at cellular level that transition to and from REM sleep is governed by the reciprocal interaction between cholinergic REM-on neurons and aminergic REM-off neurons located in the brainstem. Similarity between the time-course of the REM-on neuronal activity and that of EEG power in the high beta range (approximately 18-30 Hz) allows a tentative parallelism to be drawn between the two. This review emphasises the importance of the thalamically projecting brainstem activating systems in the orchestration of the transitions that give rise to state progression across the sleep-wake cycle.

A cardiovascular-respiratory control system model including state delay with application to congestive heart failure in humans

This paper considers a model of the human cardiovascular-respiratory control system with one and two transport delays in the state equations describing the respiratory system. The effectiveness of the control of the ventilation rate is influenced by such transport delays because blood gases must be transported a physical distance from the lungs to the sensory sites where these gases are measured. The short term cardiovascular control system does not involve such transport delays although delays do arise in other contexts such as the baroreflex loop (see [46]) for example. This baroreflex delay is not considered here. The interaction between heart rate, blood pressure, cardiac output, and blood vessel resistance is quite complex and given the limited knowledge available of this interaction, we will model the cardiovascular control mechanism via an optimal control derived from control theory. This control will be stabilizing and is a reasonable approach based on mathematical considerations as well as being further motivated by the observation that many physiologists cite optimization as a potential influence in the evolution of biological systems (see, e.g., Kenner [29] or Swan [62]). In this paper we adapt a model, previously considered (Timischl [63] and Timischl et al. [64]), to include the effects of one and two transport delays. We will first implement an optimal control for the combined cardiovascular-respiratory model with one state space delay. We will then consider the effects of a second delay in the state space by modeling the respiratory control via an empirical formula with delay while the the complex relationships in the cardiovascular control will still be modeled by optimal control. This second transport delay associated with the sensory system of the respiratory control plays an important role in respiratory stability. As an application of this model we will consider congestive heart failure where this transport delay is larger than normal and the transition from the quiet awake state to stage 4 (NREM) sleep. The model can be used to study the interaction between cardiovascular and respiratory function in various situations as well as to consider the influence of optimal function in physiological control system performance.

Large-scale ensemble averaging of ambulatory impedance cardiograms

Impedance cardiography has been used increasingly to measure human physiological responses to emotional and mentally engaging stimuli. The validity of large-scale ensemble averaging of ambulatory impedance cardiograms was evaluated for preejection period (PEP), interbeat interval, and dZ/dt(min) amplitude. We tested whether the average of "classical" 60-sec ensemble averages across periods with fixed activity, posture, physical load, social situation, and location could be accurately estimated from a single large-scale ensemble average spanning these entire periods. Impedance and electrocardiograms were recorded for about 24-h from 21 subjects. Recordings were scored by seven raters, using both methods for each subject. Good agreement (average intraclass correlation coefficient was .91) between both ensemble averaging methods was found for all three cardiac function measures. The results indicate that for unambiguous ambulatory impedance cardiograms, large-scale ensemble averaging is valid, which makes measuring prolonged changes in cardiac sympathetic activity by measuring ambulatory PEP feasible even in large epidemiological samples.

The influence of sleep onset on the diurnal variation in cardiac activity and cardiac control

Heart rate (HR), blood pressure (BP) and autonomic nervous system (ANS) activity vary diurnally, with a reduction in HR and BP, and a shift to vagal dominance during the dark phase. However, the cause of these changes, particularly the relative influence of sleep and circadian mechanisms, remains uncertain. The present study assessed the effect of sleep onset on HR, BP, high frequency (HF) component of heart rate variability (HRV), low frequency/high frequency (LF/HF) ratio and pre-ejection period (PEP). Sleep onset was dissociated from circadian influences by having subjects go to sleep at two different circadian phases, their normal time of sleep onset (normal sleep onset, NSO), and after a delay of 3 h (delayed sleep onset, DSO). The assumption was that changes caused by sleep onset would occur in association with sleep onset, irrespective of its timing, while circadian effects would have a consistent circadian phase and be independent of when sleep onset occurred. Thirteen and 17 subjects were run in the NSO and DSO conditions, respectively. Following a 1-h adaptation period, data collection began 2 h before subjects' normal time of sleep onset and continued until morning awakening. The lights were turned out after 2 h in the NSO condition and 5 h in the DSO condition. Subjects were required to maintain a supine position throughout the experimental sessions. The night-time decrease in HR was found to be due to both sleep onset and a circadian influence, with the circadian component being more prominent. In contrast, the fall in BP was largely due to a sleep onset effect. Increased vagal activity, as reflected in the HF component and a shift to vagal dominance in the LF/HF ratio, appeared to be primarily a function of the sleep system, while sympathetic activity, as assessed by PEP, reflected a circadian influence.

The boundary between wakefulness and sleep: quantitative electroencephalographic changes during the sleep onset period

Microstructural electroencephalographic changes during the wakefulness-sleep transition have been investigated by comparing two definitions of sleep onset: the first occurrence of stage 1 and of stage 2. Power values were calculated across a 1-28-Hz frequency range in a 1-Hz bin resolution in the sleep recordings of 26 normal subjects. Quantitative changes were assessed after averaging individual time series, aligned with respect to the first occurrence of stage 1 or of stage 2. The time course of the single-Hz activity revealed a linear increase of power in the 1-6-Hz range and a linear decrease in the 9-12- and 16-28-Hz ranges during the stage 1 transition. During the stage 2 transition, electroencephalogram power linearly increased in the 1-7- and 14-15-Hz ranges and decreased in the 18-28-Hz range, while the 8-12-Hz range fitted a second-order polynomial curve. The two 'switch' points were also compared in their ability to differentiate Hz by Hz wakefulness from sleep: a lower mean power was found after stage 1 onset in the 9-11-Hz and 20-28-Hz bins and a higher one in the 1-5-Hz bins, while a higher power was found in the 1-8-Hz and 12-16-Hz bins and a lower one in 18-28-Hz bins after stage 2 onset. The time course of three electroencephalographic frequency ranges [delta/theta/sigma (1-7 and 12-16 Hz); beta (17-28 Hz); alpha (8-11 Hz)], grouped on the basis of a principal component analysis, fitted a first-order polynomial curve for the first two ranges, and a second-order polynomial curve for the last, with a progressive decrease during wakefulness, a minimum point during stage 1, and a subsequent increase during stage 2. The uniformly increasing electroencephalographic power across the 1-16-Hz frequency range during stage 2 and the shift of functional meaning for the alpha power during stage 1 point to the start of stage 2 as a more reliable boundary between wakefulness and sleep.

Cardiac and respiratory activity at arousal from sleep under controlled ventilation conditions

Arousal from sleep is associated with elevated cardiac and respiratory activity. It is unclear whether this occurs because of homeostatic mechanisms or a reflex activation response associated with arousal. Cardiorespiratory activity was measured during spontaneous arousals from sleep in subjects breathing passively on a ventilator. Under such conditions, homeostatic mechanisms are eliminated. Ventilation, end-tidal PCO2, mask pressure, diaphragmatic electromyograph, heart rate, and blood pressure were measured in four normal subjects under two conditions: assisted ventilation and a normal ventilation control condition. In the control condition, there was a normal, sleep-related fall in ventilation and rise in end-tidal PCO2. Subsequently, at an arousal, there was an increase in respiratory and cardiac activity. In the ventilator condition, a vigorous cardiorespiratory response to a spontaneous arousal from sleep remained. These results indicate that sleep-related respiratory stimuli are not necessary for the occurrence of elevated cardiorespiratory activity at an arousal from sleep and are consistent with the hypothesis that such activity is at least in part due to a reflex activation response.

Slow eye movements and EEG power spectra during wake-sleep transition

OBJECTIVE

The aim of the present study was to assess the relationship between slow eye movements (SEMs) and quantitative EEG measures during the wake-sleep transition.

METHODS

Individual distributions were aligned with respect to the onset of stage 2 to provide an unequivocal hallmark of the beginning of sleep and to reduce the sources of variability in this transition. The relationship between EEG spectral powers and EOG changes was assessed by means of product-moment correlations and bootstrap analyses for individual time series, and by means of a multiple regression analysis for the entire sample.

RESULTS

Results on the individual distributions as well as on averaged data showed a tight relationship between SEMs and EEG changes, negative across the 1-14 Hz frequency range and positive across the 15-30 Hz one. Spectral power in the sigma EEG band, that corresponds to the frequency at the phasic sleep spindles, resulted as the best predictor of SEM variations, being negatively correlated to the EOG changes. With respect to the other EEG frequency bands, the split half of the distributions with respect to stage 2 onset indicated a positive correlation of delta power with the increase of SEM activity before sleep onset, and of beta power with the decrease of SEMs after sleep onset.

CONCLUSIONS

These results seem to suggest that sleep spindles could trigger the reduction and the final disappearance of slow eye movements in the late part of the wake-sleep transition.

Cardiac autonomic nervous system activity during presleep wakefulness and stage 2 NREM sleep

Previous research has found that cardiac parasympathetic nervous system (PNS) activity increases and cardiac sympathetic nervous system (SNS) activity decreases during night-time sleep. This study aimed to examine in greater detail the time course of these changes in cardiac autonomic nervous system (ANS) activity. In the week prior to the experimental night, nine subjects maintained a constant sleep-wake schedule and experienced an adaptation night. Each subject's experimental night consisted of 2 h of presleep wakefulness, followed by a night of sleep, commencing at each subject's normal sleep onset time. One hundred and twenty beat blocks of presleep wakefulness and stable Stage 2 non-rapid eye movement (NREM) sleep across the night were selected. SNS activity was assessed using pre-ejection period, the amplitude of the T-wave in the ECG and the 0.1 Hz peak from the spectral analysis of the ECG. PNS activity was assessed using respiratory sinus arrhythmia (spectral analysis). Heart rate and respiratory rate were also measured. The results indicated a progressive decrease in SNS activity throughout sleep and a rise in PNS activity during the first half of the normal sleep period. The changes in PNS activity were similar, while the changes in SNS activity were altered, compared with a previous study in which stage of sleep was not controlled. This indicates a likely sleep stage influence on SNS activity, but not on cardiac PNS activity. These results are consistent with the concept of a primarily circadian, but not sleep, influence on PNS activity, and primarily a sleep, but not circadian, influence on SNS activity.