Alpha activity and cardiac correlates: three types of relationships during nocturnal sleep

The relationship between alpha power and heart rate variability commonly seen in various mental states

The extensive exploration of the correlation between electroencephalogram (EEG) and heart rate variability (HRV) has yielded inconsistent outcomes, largely attributable to variations in the tasks employed in the studies. The direct relationship between EEG and HRV is further complicated by alpha power, which is susceptible to influences such as mental fatigue and sleepiness. This research endeavors to examine the brain-heart interplay typically observed during periods of music listening and rest. In an effort to mitigate the indirect effects of mental states on alpha power, subjective fatigue and sleepiness were measured during rest, while emotional valence and arousal were evaluated during music listening. Partial correlation analyses unveiled positive associations between occipital alpha2 power (10-12 Hz) and nHF, an indicator of parasympathetic activity, under both music and rest conditions. These findings underscore brain-heart interactions that persist even after the effects of other variables have been accounted for.

Alpha-wave Characteristics in Psychophysiological Insomnia

Individuals with psychophysiological insomnia (Psych-Insomnia) would show raised cortical arousal through their initiating sleep. Frequent changes in the alpha activity can be indicative of visual cortical activation, even without visual stimulation or retinal input. Therefore, we aimed to investigate alpha-wave characteristics in Psych-Insomnia before and after sleep onset. In a case–control study, 11 individuals with Psych-Insomnia (age: 44.00 ± 13.27) and 11 age-, sex-, and body mass index-matched healthy individuals (age: 41.64 ± 15.89) were recruited for this study. An overnight polysomnography monitoring was performed. Alpha characteristics were calculated from wake before sleep onsets (WBSOs), wake after sleep onset, rapid eye movement, and nonrapid eye movement in the both groups. They include the alpha power and alpha frequency and their variability in the central region. In the WBSO, alpha activity and variability were higher in the Psych-Insomnia individuals compared to healthy individuals. In both groups, alpha frequency variability was observed at approximately 1 Hz. Alpha-wave synchronization in Psych-Insomnia individuals was higher than the group with normal sleep. Individuals with Psych-Insomnia have a lot of imagination in the wake before sleep, which can be caused by stress, everyday concerns, and daily concerns.

Eye movement desensitization and reprocessing for post-traumatic stress disorder from the perspective of three-dimensional model of the experiential selfhood

Eye Movement Desensitization and Reprocessing (EMDR) therapy is included in many international trauma treatment guidelines and is also shortlisted as an evidence-based practice for the treatment of psychological trauma and Post-Traumatic Stress Disorder (PTSD). However, its neurobiological mechanisms have not yet been fully understood. In this brief article we propose a hypothesis that a recently introduced neurophysiologically based three-dimensional construct model for experiential selfhood may help to fill this gap by providing the necessary neurobiological rationale of EMDR. In support of this proposal we briefly overview the neurophysiology of eye movements and the triad selfhood components, as well as EMDR therapy neuroimaging studies.

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.

Predictability decomposition detects the impairment of brain-heart dynamical networks during sleep disorders and their recovery with treatment

This work introduces a framework to study the network formed by the autonomic component of heart rate variability (cardiac processη) and the amplitude of the different electroencephalographic waves (brain processes δ, θ, α, σ, β) during sleep. The framework exploits multivariate linear models to decompose the predictability of any given target process into measures of self-, causal and interaction predictability reflecting respectively the information retained in the process and related to its physiological complexity, the information transferred from the other source processes, and the information modified during the transfer according to redundant or synergistic interaction between the sources. The framework is here applied to theη,δ,θ,α,σ,βtime series measured from the sleep recordings of eight severe sleep apnoea-hypopnoea syndrome (SAHS) patients studied before and after long-term treatment with continuous positive airway pressure (CPAP) therapy, and 14 healthy controls. Results show that the full and self-predictability of η, δ and θ decreased significantly in SAHS compared with controls, and were restored with CPAP forδandθbut not forη The causal predictability of η and δ occurred through significantly redundant source interaction during healthy sleep, which was lost in SAHS and recovered after CPAP. These results indicate that predictability analysis is a viable tool to assess the modifications of complexity and causality of the cerebral and cardiac processes induced by sleep disorders, and to monitor the restoration of the neuroautonomic control of these processes during long-term treatment.

EEG beta power and heart rate variability describe the association between cortical and autonomic arousals across sleep

Cortical and autonomic arousals have been found to be closely associated. As arousal events are not evenly dispersed across sleep, we hypothesized the relationship between high frequency electroencephalogram (EEG) power and autonomic arousal indices differ between non-rapid eye movement (NREM) and rapid eye movement (REM) sleep. One night of polysomnographic recording was performed on a group of 18 subjects using a portable recorder. The EEG was collected from C3/Fz. Sleep stages and cortical arousals were visually scored. Cardiac autonomic modulation was assessed from heart rate variability, where the high frequency power (HF) indicates parasympathetic modulation, and the low frequency to high frequency power ratio (LF/HF) represents sympathetic modulation. During NREM sleep, EEG beta power was significantly correlated with LF/HF (r=0.40 ± 0.06), and the relationships were more positive than during REM sleep (LF/HF: r=0.20 ± 0.08; EOG power: r=-0.13 ± 0.05). The relationship of beta power with LF/HF was associated with the incidence of cortical arousal, particularly during NREM sleep. With respect to alpha power, it was only marginally related to HF or LF/HF. In addition, the coefficients of determination were lower for alpha power than for beta power in terms of the relationships to HF, LF/HF and EOG power. This study shows a higher relationship between cortical and autonomic activation during NREM sleep, and the association is better described by beta power. This finding suggests NREM sleep may be of greater therapeutic potential in view of reducing cardiovascular disease associated with sleep fragmentation, and beta power may provide a better index to evaluate the effect.

The circadian regulation of sleep: impact of a functional ADA-polymorphism and its association to working memory improvements

Sleep is regulated in a time-of-day dependent manner and profits working memory. However, the impact of the circadian timing system as well as contributions of specific sleep properties to this beneficial effect remains largely unexplored. Moreover, it is unclear to which extent inter-individual differences in sleep-wake regulation depend on circadian phase and modulate the association between sleep and working memory. Here, sleep electroencephalography (EEG) was recorded during a 40-h multiple nap protocol, and working memory performance was assessed by the n-back task 10 times before and after each scheduled nap sleep episode. Twenty-four participants were genotyped regarding a functional polymorphism in adenosine deaminase (rs73598374, 12 G/A-, 12 G/G-allele carriers), previously associated with differences in sleep-wake regulation. Our results indicate that genotype-driven differences in sleep depend on circadian phase: heterozygous participants were awake longer and slept less at the end of the biological day, while they exhibited longer non rapid eye movement (NREM) sleep and slow wave sleep concomitant with reduced power between 8-16 Hz at the end of the biological night. Slow wave sleep and NREM sleep delta EEG activity covaried positively with overall working memory performance, independent of circadian phase and genotype. Moreover, REM sleep duration benefitted working memory particularly when occurring in the early morning hours and specifically in heterozygous individuals. Even though based on a small sample size and thus requiring replication, our results suggest genotype-dependent differences in circadian sleep regulation. They further indicate that REM sleep, being under strong circadian control, boosts working memory performance according to genotype in a time-of-day dependent manner. Finally, our data provide first evidence that slow wave sleep and NREM sleep delta activity, majorly regulated by sleep homeostatic mechanisms, is linked to working memory independent of the timing of the sleep episode within the 24-h cycle.

Functional connectivity between parietal cortex and the cardiac autonomic system in uremics

Although the central autonomic network (CAN) has been well researched in animal models, the CAN in humans is still unclear, especially for cardiovascular control. This study aimed to investigate which areas of the cerebral cortices are associated with the peripheral cardiac autonomic control involved in the CAN in uremic patients with autonomic dysfunction and normal controls. The central and peripheral autonomic network in 19 uremic patients with significant autonomic dysfunction and 24 age- and sex-matched controls [mean age ± standard deviation (SD), 55.16 ± 10.45 years and 55.42 ± 5.42 years, respectively] were evaluated by simultaneous spectral analysis of electroencephalography (EEG) and electrocardiography recording (ECG), along with serial autonomic tests [autonomic questionnaire and orthostatic blood pressure (BP) change]. Only frequency-domain heart rate variability (f-HRV) during the deep-breathing stage could differentiate the two groups. Although there is no significant difference in f-HRV during the quiet-breathing stage, different patterns of central oscillation and their correlation with peripheral cardiac autonomic indices could be found for the two groups. Although the power of specific EEG bands under electrode T3 and T6 correlated significantly with the power of peripheral HRV indices in the control group, those under electrodes P3 and Pz had significant correlations in the uremic group suggesting a role of functional connectivity between them. In addition, sympathetic activity is correlated with slow wave EEG (theta/delta) power whereas parasympathetic activity is correlated with fast wave EEG (beta) power. In conclusion, there is functional connectivity between the parietal cortex and the peripheral cardiac autonomic system (PAN) in uremics and the pattern of central autonomic connectivity differs between uremic patients with autonomic dysfunction and normal controls.

Heart rate variability in sleep-related migraine without aura

OBJECTIVES

This is an observational study aimed to investigate the activity of autonomic nervous system during sleep in patients with sleep-related migraine.

METHODS

Eight consecutive migraineurs without aura were enrolled (6 women and 2 men), aged 30 to 62 years (mean 48.1 ± 9.3 years). Inclusion criteria were: high frequency of attacks (> 5 per month) and occurrence of more than 75% of the attacks during sleep causing an awakening. Patients were compared with a control group of 55 healthy subjects (23 men and 32 women, mean age 54.2 ± 13.0 years), and with a further control group of 8 age- and gender-matched healthy controls. Patient and controls underwent polysomnography and heart rate variability analysis.

RESULTS

A significant reduction of the LF/HF ratio during N2 and N3 sleep stages was observed in migraineurs compared with controls. No differences in sleep macrostructure were observed; cyclic alternating pattern (CAP) time and CAP rate were lower in migraineurs than in controls.

CONCLUSIONS

These findings indicate a peculiar modification of the autonomic balance during sleep in sleep-related migraine. The reduction of LF/HF ratio in NREM sleep was observed in controls, but it was quantitatively much more evident in migraineurs. Changes in LF/HF could be consequent to an autonomic unbalance which could manifest selectively (or alternatively become more evident) during sleep. These findings, together with the reduction in CAP rate, could be an expression of reduced arousability during sleep in patients with sleep-related migraine. The simultaneous involvement of the autonomic, arousal, and pain systems might suggest involvement of the hypothalamic pathways.

Cross-correlation of EEG frequency bands and heart rate variability for sleep apnoea classification

Sleep apnoea is a sleep breathing disorder which causes changes in cardiac and neuronal activity and discontinuities in sleep pattern when observed via electrocardiogram (ECG) and electroencephalogram (EEG). Using both statistical analysis and Gaussian discriminative modelling approaches, this paper presents a pilot study of assessing the cross-correlation between EEG frequency bands and heart rate variability (HRV) in normal and sleep apnoea clinical patients. For the study we used EEG (delta, theta, alpha, sigma and beta) and HRV (LF(nu), HF(nu) and LF/HF) features from the spectral analysis. The statistical analysis in different sleep stages highlighted that in sleep apnoea patients, the EEG delta, sigma and beta bands exhibited a strong correlation with HRV features. Then the correlation between EEG frequency bands and HRV features were examined for sleep apnoea classification using univariate and multivariate Gaussian models (UGs and MGs). The MG outperformed the UG in the classification. When EEG and HRV features were combined and modelled with MG, we achieved 64% correct classification accuracy, which is 2 or 8% improvement with respect to using only EEG or ECG features. When delta and acceleration coefficients of the EEG features were incorporated, then the overall accuracy improved to 71%.

THE RELATIONSHIP OF HRV TO SLEEP EEG AND SLEEP RHYTHM

Previous studies have shown that there exists a cycle of NREM (non-rapid eye movement)-REM (rapid eye movement) during normal human sleep, and heart rate variability (HRV) has a close relationship to sleep stages and sleep cycle. This article reports the relationship between the electroencephalographic activity and the HRV spectral power in several specific frequency bands. The authors discovered that relationships do exist between HRV and electroencephalogram (EEG) during sleep. In particular, it was found that, prior to the changes of EEG, the changes of HRV usually indicate the shift of sleep stages. HRV frequency analysis indicates that the very-low-frequency components of HRV are closely related to sleep EEG. Results show that the rhythm of the spectral power oscillations in some specific frequency bands of HRV is almost the same as the sleep cycle, which reflects the rhythm of sleep to a certain extent.

Correlation of sleep EEG frequency bands and Heart Rate Variability

Sleep apnoea is a sleep breathing disorder which causes changes in cardiac and neuronal activity and discontinuities in sleep pattern when observed via electrocardiogram (ECG) and electroencephalogram (EEG). This paper presents a pilot study result of assessing the correlation between EEG frequency bands and ECG Heart Rate Variability (HRV) in normal and sleep apnoea human clinical patients at different sleep stages. In sleep apnoea patients, the results have shown that EEG delta, sigma and beta bands exhibited a strong correlation with cardiac HRV parameters at different sleep stages.

A study of the brain's resting state based on alpha band power, heart rate and fMRI

Considering that there are several theoretical reasons why fMRI data is correlated to variations in heart rate, these correlations are explored using experimental resting state data. In particular, the possibility is discussed that the "default network", being a brain area that deactivates during non-specific general tasks, is a hemodynamic effect caused by heart rate variations. Of fifteen healthy controls ECG, EEG and fMRI were co-registered. Slice time dependent heart rate regressors were derived from the ECG data and correlated to fMRI using a linear correlation analysis where the impulse response is estimated from the data. It was found that in most subjects substantial correlations between heart rate variations and fMRI exist, both within the brain and at the ventricles. The brain areas with high correlation to heart rate are different from the "default network" and the response functions deviate from the canonical hemodynamic response function. Furthermore, a general negative correlation was found between heart beat intervals (reverse of heart rate) and alpha power. We interpret this finding by assuming that subject's state varies between drowsiness and wakefulness. Finally, given this large correlation, we re-examined the contribution of heart rate variations to earlier reported fMRI/alpha band correlations, by adding heart rate regressors as confounders. It was found that inclusion of these confounders most often had a negligible effect. From its strong correlation to alpha power, we conclude that the heart rate variations contain important physiological information about subject's resting state. However, it does not provide a full explanation of the behaviour of the "default network". Its application as confounder in fMRI experiments is a relatively small computational effort, but may have a substantial impact in paradigms where heart rate is controlled by the stimulus.

Heart beats brain: The problem of detecting alpha waves by neuronal current imaging in joint EEG–MRI experiments

It has been suggested recently that the influence of the neuro-magnetic field should make electrical brain activity directly detectable by MRI. To test this hypothesis, we performed combined EEG-MRI experiments which aim to localize the neuronal current sources of alpha waves (8-12 Hz), one of the most prominent EEG phenomena in humans. A detailed analysis of cross-spectral coherence between simultaneously recorded EEG and MRI time series revealed no sign of alpha waves. Instead the EEG-MRI approach was found to be hampered by artefacts due to cardiac pulsation, which extend into the frequency band of alpha waves. Separate brain displacement mapping experiments confirmed that not only the EEG but also the MRI signal is confounded by harmonics of the cardiac frequency even at 10 Hz and beyond. This well-known ballistocardiogram artefact cannot be avoided or eliminated entirely by available signal processing techniques. Therefore we must conclude that current EEG-MRI methodology based on correlation analysis lacks not only the sensitivity but also the specificity required for the reliable detection of alpha waves.

A prominent role for amygdaloid complexes in the Variability in Heart Rate (VHR) during Rapid Eye Movement (REM) sleep relative to wakefulness

Rapid eye movement sleep (REMS) is associated with intense neuronal activity, rapid eye movements, muscular atonia and dreaming. Another important feature in REMS is the instability in autonomic, especially in cardiovascular regulation. The neural mechanisms underpinning the variability in heart rate (VHR) during REMS are not known in detail, especially in humans. During wakefulness, the right insula has frequently been reported as involved in cardiovascular regulation but this might not be the case during REMS. We aimed at characterizing the neural correlates of VHR during REMS as compared to wakefulness and to slow wave sleep (SWS), the other main component of human sleep, in normal young adults, based on the statistical analysis of a set of H(2)(15)O positron emission tomography (PET) sleep data acquired during SWS, REMS and wakefulness. The results showed that VHR correlated more tightly during REMS than during wakefulness with the rCBF in the right amygdaloid complex. Moreover, we assessed whether functional relationships between amygdala and any brain area changed depending the state of vigilance. Only the activity within in the insula was found to covary with the amygdala, significantly more tightly during wakefulness than during REMS in relation to the VHR. The functional connectivity between the amygdala and the insular cortex, two brain areas involved in cardiovascular regulation, differs significantly in REMS as compared to wakefulness. This suggests a functional reorganization of central cardiovascular regulation during REMS.

A study of the dynamic interactions between sleep EEG and heart rate variability in healthy young men

OBJECTIVE

We investigated the interactions between heart rate variability and sleep electroencephalogram power spectra.

METHODS

Heart rate and sleep electroencephalogram signals were recorded in 8 healthy young men. Spectral analysis was applied to electrocardiogram and electroencephalogram recordings. Spectral components of RR intervals were studied across sleep stages. The cross-spectrum maximum was determined as well as coherencies, gains and phase shifts between normalized high frequency of RR intervals and all electroencephalographic frequency bands, calculated over the first 3 NREM-REM cycles.

RESULTS

RR intervals increased from awake to NREM and decreased during REM. Normalized low frequency decreased from awake to NREM and increased during REM while normalized high frequency evolved conversely. Low to high frequency ratio developed in opposition to RR intervals. Coherencies between normalized high frequency and power spectra were high for all bands. The gain was highest for delta band. Phase shift between normalized high frequency and delta differed from zero and modifications in normalized high frequency preceded changes in delta by 41+/-14 degrees.

CONCLUSIONS

Our study demonstrates that: (1) all electroencephalographic power bands are linked to normalized high frequency; (2) modifications in cardiac vagal activity show predominantly parallel changes and precede changes in delta band by a phase shift corresponding to a lead of 12+/-5 min.

Acute stress affects heart rate variability during sleep

OBJECTIVE

Although stress can elicit profound and lasting effects on sleep, the pathways whereby stress affects sleep are not well understood. In this study, we used autoregressive spectral analysis of the electrocardiogram (EKG) interbeat interval sequence to characterize stress-related changes in heart rate variability during sleep in 59 healthy men and women.

METHODS

Participants (N = 59) were randomly assigned to a control or stress condition, in which a standard speech task paradigm was used to elicit acute stress in the immediate presleep period. EKG was collected throughout the night. The high frequency component (0.15-0.4 Hz Eq) was used to index parasympathetic modulation, and the ratio of low to high frequency power (0.04-0.15 Hz Eq/0.15-0.4 Hz Eq) of heart rate variability was used to index sympathovagal balance.

RESULTS

Acute psychophysiological stress was associated with decreased levels of parasympathetic modulation during nonrapid eye movement (NREM) and rapid eye movement sleep and increased levels of sympathovagal balance during NREM sleep. Parasympathetic modulation increased across successive NREM cycles in the control group; these increases were blunted in the stress group and remained essentially unchanged across successive NREM periods. Higher levels of sympathovagal balance during NREM sleep were associated with poorer sleep maintenance and lower delta activity.

CONCLUSIONS

Changes in heart rate variability associated with acute stress may represent one pathway to disturbed sleep. Stress-related changes in heart rate variability during sleep may also be important in association with chronic stressors, which are associated with significant morbidity and increased risk for mortality.

Estimating cardiac autonomic activity during sleep: impedance cardiography, spectral analysis, and Poincaré plots

OBJECTIVE

To compare noninvasive measures of cardiac autonomic activity during sleep.

METHODS

The absolute and normalized (n.u.) high and low frequency peaks from the spectral analysis of R-R intervals (HF, LF, HFn.u., LFn.u.), LF/HF ratio, pre-ejection period (PEP) from impedance cardiography, and the autocorrelation coefficient (rRR) as illustrated in Poincaré plots were measured during night-time sleep in 9 young healthy subjects. Heart rate and blood pressure were also recorded.

RESULTS

Heart rate was significantly associated with cardiac sympathetic activity (PEP, average r=-0.46), but not with cardiac parasympathetic activity (HF, average r=-0.17). rRR was significantly associated with heart rate (average r=0.41), and LF/HF (average r=0.69), but not with PEP or HF. From NREM to REM sleep, heart rate, LFn.u., LF and rRR significantly increased, HFn.u. significantly decreased, LF/HF showed an increasing trend (P=0.07) and PEP showed a decreasing trend (P=0.06). Blood pressure and HF were highly variable without significant changes from NREM to REM sleep.

CONCLUSIONS

Cardiac parasympathetic activity (HF) does not vary greatly between sleep stages. Cardiac sympathetic activity (PEP) decreases linearly during sleep. rRR and LF/HF can track sympathovagal changes during sleep, but cannot differentiate between changes in cardiac parasympathetic and sympathetic activity. The relative advantages and disadvantages of the different measures are discussed.

Effect of cognitive behavioral therapy on heart rate variability during REM sleep in female rape victims with PTSD

Six female rape victims with posttraumatic stress disorder (PTSD) were assessed for sleep disturbances. Five responded to cognitive-behavioral therapy (CBT) and one did not complete treatment. Sympatho-vagal balance was measured using heart rate variability (HRV) during rapid eye movement (REM) sleep. The treatment responders significantly decreased on HRV while the noncompleter increased. The responders also significantly decreased on sleep disturbances. The noncompleter remained unchanged. Thus a remission in PTSD symptoms following CBT accompanied a reduction in the HRV indicator of sympathetic predominance in REM sleep.

Correlation between electroencephalography and heart rate variability during sleep

It is known that autonomic nervous activities change in correspondence with sleep stages. However, the characteristics of continuous fluctuations in nocturnal autonomic nerve tone have not been clarified in detail. The study aimed to determine the possible correlation between the electroencephalogram (EEG) and autonomic nervous activities, and to clarify in detail the nocturnal fluctuations in autonomic nerve activities. Overnight EEGs and electrocardiograms of seven healthy males were obtained. These EEGs were analyzed by fast Fourier transformation algorithm to extract delta, sigma and beta power. Heart rate and heart rate variability (HRV) were calculated in consecutive 5-min epochs. The HRV indices of low frequency (LF), high frequency (HF) and LF/HF ratio were calculated from the spectral analysis of R-R intervals. The sleep stages were manually scored according to Rechtschaffen and Kales' criteria. Low frequency and LF/HF were significantly lower during non-rapid eye movement (NREM) than REM, and were lower in stages 3 and 4 than in stages 1 and 2. Furthermore, delta EEG showed inverse correlations with LF (r = - 0.44, P < 0.001) and LF/HF (r = - 0.41, P < 0.001). In contrast, HF differed neither between REM and NREM nor among NREM sleep stages. Detailed analysis revealed that correlation was evident from the first to third NREM, but not in the fourth and fifth NREM. Delta EEG power showed negative correlations with LF and LF/HF, suggesting that sympathetic nervous activities continuously fluctuate in accordance with sleep deepening and lightening.

Inverse coupling between ultradian oscillations in delta wave activity and heart rate variability during sleep

OBJECTIVE

We investigate the relationship between changes in heart rate variability and electroencephalographic (EEG) activity during sleep.

METHOD

Nine male subjects with regular non-rapid-eye movement-rapid-eye movement (NREM-REM) sleep cycles were included in the study. They underwent EEG and cardiac recordings during one experimental night. Heart rate variability was determined over 5-min periods by the ratio of low frequency to low frequency plus high frequency power [LF/(LF+HF)] calculated using spectral analysis of R-R intervals. EEG spectra were analyzed using a fast Fourier transform algorithm.

RESULTS

We found an ultradian 80-120 min rhythm in the LF/(LF+HF) ratio, with high levels during rapid eye movement (REM) sleep and low levels during slow wave sleep (SWS). During sleep stage 2 there was a progressive decrease in the transition from REM sleep to SWS, and an abrupt increase from SWS to REM sleep. These oscillations were significantly coupled in a 'mirror-image' to the overnight oscillations in delta wave activity, which reflect sleep deepening and lightening. Cardiac changes preceded EEG changes by about 5 min.

CONCLUSIONS

These findings demonstrate the existence of an inverse coupling between oscillations in delta wave activity and heart rate variability. They indicate a non-uniformity in sleep stage 2 that underlies ultradian sleep regulation.