Cyclic alternating pattern and spectral analysis

of heart rate variability during normal sleep

RAFFAELE FERR I 1 , 2 , L I BOR IO PARR INO 3 , AR IANNA SMER IER I 3 ,

MAR IO G . TERZANO 3 , MAUR IZ IO EL IA 2 , S EBAST IANO A . MUSUMEC I 2

and SALVATORE PETT INATO 1

1Sleep Research Center, 2Department of Neurology, Oasi Institute for Research on Mental Retardation and Brain Aging (IRCCS), Troina,3Sleep Disorders Center, Department of Neurology, University of Parma, Parma, Italy

Accepted in revised form 24 October 1999; received 23 December 1998

INTRODUCTION

The natural electroencephalographic (EEG) arousal rhythm of

non-rapid eye movement (NREM) sleep is known as the cyclic

alternating pattern (CAP) (Terzano et al. 1985, 1988). CAP

consists of arousal-related phasic events (Phase A) that

interrupt, at intervals of 20±40 s, the tonic theta/delta activities

of NREM sleep (Phase B). Functionally, CAP translates a

condition of sustained arousal instability while the comple-

mentary EEG pattern, i.e. non-CAP (NCAP), characterized by

a rhythmic background activity with few, randomly distributed

SUMMARY The natural arousal rhythm of non-rapid eye movement (NREM) sleep is

known as the cyclic alternating pattern (CAP), which consists of arousal-

related phasic events (Phase A) that periodically interrupt the tonic theta/

delta activities of NREM sleep (Phase B). The complementary condition,

i.e. non-CAP (NCAP), consists of a rhythmic electroencephalogram

background with few, randomly distributed arousal-related phasic events.

Recently, some relation between CAP and autonomic function has been

preliminarily reported during sleep in young adults by means of spectral

analysis of heart rate variability (HRV). The present study was aimed at

analysing the e�ects of CAP on HRV in a group of normal children and

adolescents. Six normal children and adolescents (age range 10.0±17.5 y)

were included in this study. All-night polygraphic recordings were

performed after adaptation to the sleep laboratory. Six 5-min epochs were

selected from sleep Stage 2 and six from Stages 3 and 4 (slow-wave sleep),

both in CAP and NCAP conditions. From such epochs, a series of

parameters describing HRV was then calculated, in both time and

frequency domains, on the electrocardiographic R±R intervals. Statistical

comparison between CAP and NCAP epochs revealed a signi®cant

di�erence for most of the frequency domain parameters (increase of the

low-frequency band, increase of the low-frequency/high-frequency ratio

and decrease in the high-frequency band during CAP) both in Stage 2 and

in slow-wave sleep. Our results demonstrate that the physiological

¯uctuations of arousal during sleep described as CAP are accompanied

by subtle, but signi®cant, changes in balance between the sympathetic and

vagal components of the autonomic system.

KEYWORDS autonomic function, cyclic alternating pattern, heart rate

variability, sleep, spectral analysis

Correspondence: Dr R. Ferri, Sleep Research Center, Oasi Institute,

Via Conte Ruggero 73, 94018 Troina, Italy. Tel.: +39 935 936 111;

fax: +39 935 653 327; e-mail: rferri@oasi.en.it.

J. Sleep Res. (2000) 9, 13±18

Ó 2000 European Sleep Research Society 13

arousal-related phasic events, re¯ects a condition of stable

arousal.

The CAP sequences, formed by the regular succession of

Phases A and B, constitute the microstructural component of

sleep that accompanies the dynamic shifts between the NREM

stages and seems to play a role in the transition from NREM

to REM sleep (Terzano et al. 1985). Instead, NCAP is the

EEG expression of consolidated sleep within the NREM

stages. The physiological balance between CAP and NCAP

varies across the life span (Parrino et al. 1998) and has been

found to be altered in a number of sleep-disturbed conditions,

such as insomnia (Terzano and Parrino 1993), epilepsy

(Terzano et al. 1989, 1992), parasomnias (Zucconi et al.

1995) and mood disorders (Parrino et al. 1994).

CAP and NCAP not only constitute the dynamic sca�olds

for the microstructural organization of sleep, but also have

repercussions for motor and vegetative activities, which

¯uctuate during CAP and remain quiescent during NCAP.

Recently, some relation between CAP/NCAP and autonomic

function has been preliminarily reported in young adults

(Ferini-Strambi et al. 1997) by means of spectral analysis of

heart rate variability (HRV) during sleep. Heart rate is under

the control of e�erent sympathetic and vagal activities directed

to the sinus node, which are modulated by central brainstem

and peripheral oscillators (Malliani et al. 1991). Spectral

analysis of HRV is a quantitative, reliable method for

analysing the modulatory e�ects of neural mechanisms on

the sinus node (Task Force of the European Society of

Cardiology and the North American Society of Pacing and

Electrophysiology 1996) and two main components are

currently considered, high-frequency (HF) and low-frequency

(LF). The vagal activity is the major contributor to the HF

component, while the LF component is considered by some

authors to be a marker of sympathetic modulation and by

others to be a parameter including both vagal and sympathetic

in¯uences.

The aim of this study was to analyse the e�ects of the CAP

and NCAP conditions on HRV during NREM sleep in a

group of normal children and adolescents.

METHODS

Subjects

Ten subjects (mean age 13.4 y, range 10.0±17.5 y) were

admitted to this study. The protocol was approved by our

ethical review committee and informed consent was obtained

from the families of all subjects. All individuals were carefully

evaluated from the neurological, otorrhino-laryngoiatric and

cardiovascular points of view and failed to show signi®cant

abnormalities.

Recordings

All subjects slept in the laboratory for two consecutive nights.

The data were analysed during the second night. To determine

sleep stages, EEG (six channels), electro-oculogram (EOG)

and mental electromyogram were recorded by means of an

Oxford Medilog 9000-II recorder. Other physiological vari-

ables, such as electrocardiogram (CM4 derivation: anode in

position V4 and cathode attached to the manubrium of the

sternum), peripheral oxygen saturation, chest wall movement

by thoracic impedance and oro-nasal air¯ow with thermistors,

were recorded using an Oxford MPA-II recorder. All signals

were sampled at a rate of 128 Hz and were also reproduced on

paper by means of a Siemens Mingograf EEG 21 polygraph.

Sleep and HRV analysis

Sleep staging (macrostructure of sleep) was accomplished on

paper recordings, following standard criteria (Rechtscha�en

and Kales 1968). In particular, sleep staging was carried out by

visually analysing the EEG (C3-right earlobe derivation), EOG

(left and right outer canthi referred to the left earlobe) and

electromyogram (submentalis muscle). Body position was also

controlled by means of a video-camera; during all epochs

chosen for HRV analysis patients rested in a supine position.

In order to study sleep-stage-related HRV, a series of

5-min epochs was chosen from quiet wakefulness (W) and

the following stages during the ®rst two sleep cycles: sleep

Stage 1 comprising the preceding 2 min of quiet wakefulness

(W + S1), sleep Stage 2 (S2), sleep Stages 3 and/or 4 (slow-

wave sleep, SWS) and REM sleep. This ®rst-step selection

was carried out regardless of the ongoing microstructural

condition. Subsequently, CAP and NCAP sequences were

detected in each recording, during S2 and SWS, according to

the rules de®ned by Terzano et al. (1985, 1988). Therefore,

HRV was additionally studied on the recording night in

three di�erent 5-min epochs from CAP and in three di�erent

epochs from NCAP periods during both S2 and SWS. For

each subject, 12 epochs were selected (three from S2-CAP,

three from S2-NCAP, three from SWS-CAP and three from

SWS-NCAP).

In order to avoid gross e�ects on HRV, only CAP sequences

and NCAP periods without transient activation phases

(Schieber et al. 1971) or arousal (American Sleep Disorders

Association 1992) were selected. Moreover, because of the age

range of our subjects, children and adolescents, low amounts

of arousal were expected; in fact, the number of arousal events

shows a linear increase with age (Mathur and Douglas 1995;

Boselli et al. 1998). Within the structure of sleep, most of the

CAP sequences selected were identi®ed during the transition

from light to deep NREM sleep, in which the A phases are

basically composed of K-complexes or delta bursts (Ferrillo

et al. 1997), which are accompanied by less evident heart rate

changes. Finally, the eventual presence of apneas and hypop-

neas was also carefully controlled so that the epochs selected

for analysis were free of respiratory events.

In each 5-min epoch, ECG signals were analysed for

automatic detection of R waves using a self-made program

utilizing a simple threshold plus ®rst and second derivative

algorithms; however, careful visual inspection for possible

14 R. Ferri et al.

Ó 2000 European Sleep Research Society, J. Sleep Res., 9, 13±18

errors was performed on all epochs. In order to overcome the

problem of the low sampling rate of our recorders (128 Hz),

which might have caused a bias in the estimation of the

R-wave ®ducial point (Task Force of the European Society of

Cardiology and the North American Society of Pacing and

Electrophysiology 1996) and a consequent alteration of the

spectrum, a parabolic interpolation was used to re®ne its

evaluation (Merri et al. 1990; Bianchi et al. 1993). A series of

time domain measures was calculated: mean R±R-value,

standard deviation of all R±R intervals (SDNN), the square

root of the mean of the sum of the squares of di�erences

between adjacent R±R intervals (RMSSD), number of pairs of

adjacent R±R intervals di�ering by more than 50 ms in the

entire epoch (NN50) and percentage of NN50 among the total

R±R intervals (pNN50). The ®rst 256 R±R intervals from each

epoch were utilized for all subsequent analysis steps. The R±R

interval tachograms were processed by means of a FFT

algorithm and the following spectral parameters were

obtained: power in very low-frequency range, < 0.04 Hz

(VLF), power in low-frequency range, 0.04±0.15 Hz (LF),

power in high-frequency range, 0.15±0.4 Hz (HF), total power

(VLF + LF + HF), LF power in normalized units: LF/(total

power-VLF) ´ 100 (LF%), HF power in normalized units:

HF/(total power-VLF) ´ 100 (HF%), ratio of LF to HF (LF/

HF), frequency of highest peak in the VLF range (VLF peak),

frequency of highest peak in the LF range (LF peak) and

frequency of highest peak in the HF range (HF peak).

Statistical analysis

The comparison between HRV parameters obtained from

CAP and NCAP epochs, during each sleep stage considered in

this study, was performed by means of the Wilcoxon test for

paired data sets.

RESULTS

On average, the subjects included in this study slept for 8 h,

their sleep e�ciency index (total sleep time/time in bed) was

good (0.892) and the number of awakenings/h was very low

(0.770). A normal sleep macrostructure was observed in all

cases. The mean length of the CAP cycle during CAP

sequences was 25.2 s (Phase A 8.4 s and Phase B 16.8 s).

Figure 1 illustrates the stage-related changes in R±R interval

and HRV. R±R interval increased (therefore, heart rate

decreased) throughout sleep without relevant di�erences

between the sleep stages. LF% and LF/HF showed a common

trend towards a decrease with increasing sleep depth, from

wakefulness to SWS; during REM sleep, LF% and LF/HF

values approximated those of wakefulness. HF% underwent

Figure 1. Sleep stage associated changes in R±R interval and HRV spectral components.

Heart rate variability during normal sleep 15

Ó 2000 European Sleep Research Society, J. Sleep Res., 9, 13±18

complementary variations in wakefulness and in the di�erent

sleep stages.

The results of the comparison between HRV during CAP

and NCAP epochs in S2 and SWS, in the absence of sleep

apnea or arousal, are shown in Tables 1 and 2.

The mean R±R-values were very similar in both CAP and

NCAP conditions, with a limited interindividual variability.

During both S2 (Table 1) and SWS (Table 2) a signi®cant

di�erence between CAP and NCAP conditions emerged for

LF% and LF/HF ratio (higher in CAP than in NCAP) and for

HF% (lower in CAP than in NCAP); in SWS also VLF

showed values signi®cantly higher during CAP than during

NCAP states.

None of the time-domain parameters describing HRV

considered in this study (SDNN, RMSSD, NN50, pNN50)

showed any signi®cant di�erence between CAP and NCAP

epochs.

DISCUSSION

In the second century, Galen observed that sleep is accompan-

ied by a slowing in heart rate (Furley and Wilkie 1984);

however, it was necessary to wait for almost 2000 years in

order to achieve further insight into the sleep-related changes

of heart rate with the report by MacWilliam (1923) of increases

in heart rate and blood pressure with dreaming. Entering the

EEG and ECG era, sleep-stage-related changes in heart rate

started to be described in detail (Baust and Bonhert 1969;

Malpas and Purdie 1990; Cajochen et al. 1994; Pivik et al.

1996). More recently, spectral analysis of HRV has been used

to study ¯uctuations in the activity of the autonomic nervous

system during sleep. Using this technique, it has been reported

that LF shows a decrease during sleep, reaching minimal

values during SWS; in contrast, REM sleep is accompanied by

elevated LF values, similar to those of wakefulness, both in

children (Baharav et al. 1995) and young adults (Vaughn et al.

1995). In children, the opposite is true for HF, which increases

with sleep onset and reaches its highest values during SWS

(Baharav et al. 1995); in young adults HF has been reported to

be maximal during sleep Stage 2 (Vaughn et al. 1995). The

ratio between these two components of HRV (LF/HF) shows

changes similar to those of LF (Baharav et al. 1995).

Thus, spectral analysis of HRV has been considered to be a

reliable noninvasive method of quantifying changes in the

sustained tonic autonomic in¯uences on the heart during sleep.

The results obtained from the present analysis of sleep-stage

in¯uences on heart rate show good agreement with the ®ndings

of previous reports (Baharav et al. 1995; Vaughn et al. 1995).

Moreover, it must be emphasized that time-domain param-

eters were unable to disclose signi®cant CAP-related changes

in HRV, being less sensitive to subtle modi®cations of the

autonomic control of heart rate during sleep.

It must be noted that the age of the subjects included in this

study ranged over a period of life in which signi®cant changes

in sleep structure are to be expected. In particular, teenagers

show higher percentages of SWS and lower amounts of arousal

than older controls (Boselli et al. 1998; Parrino et al. 1998).

However, in this study we did not aim to evaluate develop-

mental aspects of HRV.

In addition to the correlation between depth of sleep and

variations of vegetative activity, there is also consolidated

evidence of transient changes in autonomic activity in

Table 1 Comparison between HR ®ndings during sleep Stage 2 CAP and NCAP epochs

S2±CAP S2±NCAPWilcoxon

Mean SD n Mean SD n P <

Mean R±R-value (s) 0.873 0.2368 10 0.902 0.2247 10 NS

SDNN 0.100 0.0585 10 0.090 0.0626 10 NS

RMSSD 0.089 0.0554 10 0.095 0.0929 10 NS

NN50 94.07 54.338 10 100.4 68.139 10 NS

pNN50 36.89 21.308 10 39.37 26.717 10 NS

VLF abs. (s2/beat) 2.699 3.4153 10 1.349 1.8085 10 NS

LF abs. (s2/beat) 1.001 1.0893 10 0.589 0.6959 10 NS

HF abs. (s2/beat) 1.224 1.2644 10 2.067 3.9133 10 NS

Total abs. (s2/beat) 4.925 5.3813 10 4.005 6.1430 10 NS

LF%* 41.67 5.6386 10 31.26 10.623 10 0.012

HF%* 58.33 5.6386 10 68.74 10.623 10 0.012

LF/HF 0.753 0.1945 10 0.513 0.2577 10 0.012

VLF peak (cycles/beat) 0.022 0.0088 10 0.016 0.0062 10 NS

LF peak (cycles/beat) 0.064 0.0177 10 0.071 0.0148 10 NS

HF peak (cycles/beat) 0.227 0.1797 10 0.220 0.0590 10 NS

SDNN, standard deviation of all R±R intervals, RMSSD, square root of the mean of the sum of the squares of differences between adjacent R±R

intervals, NN50, number of pairs of adjacent R±R intervals differing by more than 50 ms in the entire epoch, pNN50, NN50%, VLF, power in

very low-frequency range, <0.04 Hz, LF, power in low-frequency range, 0.04±0.15 Hz, HF, power in high-frequency range, 0.15±0.4 Hz, total

power, VLF + LF + HF, LF%, LF power in normalized units: LF/(total power-VLF) ´ 100, HF%, HF power in normalized units: HF/(total

power-VLF) ´ 100, LF/HF, ratio LF/HF, VLF peak, frequency of highest peak in the VLF range, LF peak, frequency of highest peak in the LF

range, HF peak, frequency of highest peak in the HF range. *Note that the value of SDs of LF% and HF% are identical because the sum

of these two parameters is always 100, in each subject.

16 R. Ferri et al.

Ó 2000 European Sleep Research Society, J. Sleep Res., 9, 13±18

association with spontaneous arousal-related phasic events.

Among such events, the most powerful e�ect on sympathetic

activity is exerted by arousal periods, which are actually

accompanied by robust increases in muscle sympathetic

activity, heart rate and blood pressure (Guilleminault and

Stoohs 1995). However, a less prominent, but still signi®cant,

acceleration of heart rate and rises in muscle sympathetic

activity and blood pressure are observed during NREM sleep

in the seconds that follow a K-complex (Hornyak et al. 1991)

or a delta burst (Church et al. 1978). In other words, all

arousal-related phasic events occurring during NREM sleep

are associated with short-lasting increases in sympathetic

activity and constitute a sort of continuum from weaker

(K-complexes and delta bursts) to powerful (arousal) EEG

features. In order to cast light exclusively on the impact of

the weaker events, in the present study, arousal periods were

excluded from the correlation between microstructural con-

ditions and HRV.

In a preliminary report, Ferini-Strambi et al. (1997) have

already shown that in young adults CAP and NCAP are

accompanied by signi®cant changes in HRV parameters.

However, these authors made no distinction between the

di�erent types of A phases included in their study and

probably also analysed epochs containing arousal or transient

activation phases. Our results indicate that such an e�ect is

also evident in children and adolescents, and that it reaches

statistical signi®cance even when the microanalysis of sleep is

cleansed of arousal. In particular, the increase in LF and LF/

HF ratio during S2±CAP and SWS±CAP (at the expense of a

complementary HF reduction) implies that during CAP the

sympatho-vagal balance is shifted towards sympathetic pre-

valence. Even if CAP-associated changes are of small ampli-

tude, they might be able to in¯uence the results of studies on

HRV during sleep in which they are not taken into account

due to the omitted scoring of CAP. No statistical comparison

was possible between epochs in which CAP was ignored and

only macrostructural analysis was accomplished, and those in

which CAP was evaluated. However, if we roughly compare

the HRV values expressed during the NREM sleep stages

(Fig. 1) and during the CAP/NCAP conditions (Tables 1 and

2), it can be seen that the CAP-related increase in sympathetic

activity is always higher than the mean value expressed by the

corresponding sleep stage as a whole. It is also interesting to

note that signi®cant autonomic di�erences between CAP and

NCAP were found both in Stage 2, which generally occupies

» 50% of the total sleep time in children and adolescents, and

in SWS, which generally occupies »25% of the total sleep time.

In other words, we are dealing with a microstructural

phenomenon that may have extensive HRV repercussions

throughout sleep. Therefore, the presence or absence of CAP

should be veri®ed, whenever possible, when studying HRV

during sleep.

As a constituent manifestation of NREM sleep, CAP occurs

even in the absence of sleep-perturbing factors (e.g. noise, pain,

myoclonic jerks, respiratory events). Basically, internal and

environmental disturbances vary the physiological amount of

CAP, but have limited e�ects on the 20±40-s alternating

rhythm of Phases A and B. Previous investigation has

ascertained that this periodicity is involved in the modulation

of a number of repetitive phenomena, such as periodic limb

movements during sleep (Parrino et al. 1996), sleep bruxism

(Macaluso et al. 1998) and sleep-related respiratory events

(Terzano et al. 1996). With respect to the present study, it can

be suggested that the same cerebral mechanisms underlying the

Table 2 Comparison between HR ®ndings during slow-wave sleep CAP and NCAP epochs

SWS±CAP SWS±NCAPWilcoxon

Mean SD n Mean SD n P <

Mean R±R-value (s) 0.879 0.2320 10 0.895 0.2268 10 NS

SDNN 0.078 0.0602 10 0.069 0.0554 10 NS

RMSSD 0.082 0.0871 10 0.088 0.0824 10 NS

NN50 83.63 64.146 10 99.38 68.119 10 NS

pNN50 32.79 25.153 10 37.79 26.705 10 NS

VLF abs. (s2/beat) 0.840 1.2892 10 0.116 0.0582 10 0.04

LF abs. (s2/beat) 0.445 0.7289 10 0.274 0.3877 10 NS

HF abs. (s2/beat) 1.590 3.5618 10 1.798 3.5829 10 NS

Total abs. (s2/beat) 2.874 5.0441 10 2.189 4.0020 10 NS

LF% 32.84 12.855 10 22.95 14.721 10 0.008

HF% 67.16 12.855 10 77.05 14.721 10 0.008

LF/HF 0.567 0.3569 10 0.365 0.3735 10 0.008

VLF peak (cycles/beat) 0.022 0.0084 10 0.018 0.0078 10 NS

LF peak (cycles/beat) 0.067 0.0176 10 0.084 0.0376 10 NS

HF peak (cycles/beat) 0.236 0.0603 10 0.240 0.0577 10 NS

SDNN, standard deviation of all R±R intervals, RMSSD, square root of the mean of the sum of the squares of differences between adjacent R±R

intervals, NN50, number of pairs of adjacent R±R intervals differing by more than 50 ms in the entire epoch, pNN50, NN50%, VLF, power in

very low-frequency range, <0.04 Hz, LF, power in low-frequency range, 0.04±0.15 Hz, HF, power in high-frequency range, 0.15±0.4 Hz, total

power, VLF + LF + HF, LF%, LF power in normalized units: LF/(total power-VLF) ´ 100, HF%, HF power in normalized units: HF/(total

power-VLF) ´ 100, LF/HF, ratio LF/HF, VLF peak, frequency of highest peak in the VLF range, LF peak, frequency of highest peak in the LF

range, HF peak, frequency of highest peak in the HF range.

Heart rate variability during normal sleep 17

Ó 2000 European Sleep Research Society, J. Sleep Res., 9, 13±18

regulation of arousal instability might be involved in the

genesis and enhancement of the sympathetic activity, since the

two phenomena (CAP and LF) operate within a common

20±40-s scale.

In conclusion, our data are in tune with the idea that

CAP modulates not only EEG activities, but also a series of

other sleep-related phenomena including autonomic ¯uctua-

tions (Terzano and Parrino 1993; Terzano et al. 1996).

Further studies are needed to clarify the vegetative impact of

both spontaneous and evoked CAP sequences, including

those containing arousal, and to investigate the role of

CAP-related autonomic changes in di�erent pathological

conditions.

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