ABSTRACT. Sleep staging has been conventionally performed using neurophysiologic and behavioral criteria. However, these criteria may not always be available. Since it is known that cardiorespiratory variables in rapid eye movement (REM) sleep are different from those in quiet sleep, we asked whether such variables can be used for the determination of sleep state. We studied nine normal fullterm infants at 1 and 4 months of life. Ventilation was measured using barometric plethysmography and the RR interval using a high accuracy R wave detector. Electroencephalogram, electrooculogram, and postural muscle electromyogram were recorded using surface electrodes and behavioral criteria applied. Means of RR interval, respiratory cycle time and tidal volume, and coefficients of variation of the same variables, were obtained for 30-s intervals throughout each sleep study. The KolmogorovSmirnov distances between REM and quiet sleep were larger for the coefficients of variation than for the means at both ages for all variables. Moreover, coefficient of variation of respiratory cycle time was found to provide the largest separation between REM and quiet sleep. In view of this result, we developed a statistical decision rule using coefficient of variation of respiratory cycle time for the classification of REM and quiet sleep in blocks of 5-min periods. Each study was divided into 5-min epochs and this rule was applied to each epoch. Of 85 epochs staged as quiet sleep by neurophysiologic and behavioral criteria, 79 epochs (or 93%) were classified correctly as quiet sleep using our decision rule. Of 85 epochs staged as REM sleep, 84 were classified as REM sleep and only one misclassified as quiet sleep. Five additional infants, whose results did not enter into the formulation of the decision rule, were used as a subsequent example to test the rule. The results of these five infants were similar to those of the previous nine others. We conclude that in young infants 1) the variability of cardiorespiratory parameters can separate quiet from nonquiet sleep better than the mean values and 2) sleep staging using a decision rule based on coefficient of variation of respiratory cycle time can be performed with high degree of accuracy. In the past 1-2 decades, monitoring heart rate and respiration in the fetus or in early postnatal life has increased substantially for clinical or research purposes in humans and animals (1-14). Furthermore, technical advances involving computerized techniques have made it possible not only to record or analyze cardiorespiratory variables but to do so over prolonged periods of time. For instance, studies during gestation, labor, or in early postnatal life have been performed over several hours or even days (5-8, 13).One major concern in such studies is that during long periods of time, the state of consciousness of the subject can change. For example, the subject can change from, say, REM to quiet sleep, REM sleep to wakefulness, and so forth. Since the state of consciousness has long been recognized a...

We studied the short-term oscillations in the R-R interval in five puppies at 4 wk of age and five adult dogs during sleep and wakefulness. The R-R interval was measured using an R-R preprocessor, and respiration was recorded using barometric plethysmography. Puppies showed much smaller fluctuations in the R-R interval (SD between 6 and 40 ms) than adult dogs (SD between 124 and 367 ms) in both rapid eye movement (REM) and quiet sleep. Spectral analysis demonstrated that these oscillations were primarily of low frequencies, and the contribution of respiratory sinus arrythmia (RSA) to total power was low. In contrast, in adult dogs during sleep, the spectral distributions were peaked in frequency bands corresponding to mean respiratory rate, and the percent contribution of low frequencies to power was small. Furthermore, the mean R-R interval was considerably larger during expiration than during inspiration in adult dogs (showing 20-140% increase), but not in puppies (showing only -0.4 to 4.4% increase). We conclude that 1) the mechanisms responsible for RSA mature postnatally in the dog; 2) the magnitude of RSA depends on the state of consciousness in the adult dog, being greater in sleep than during wakefulness; and 3) low-frequency oscillations, not related to breathing and independent of sleep state, characterize the variations in the R-R interval in early life but are insignificant in the adult dog.

To investigate the role of opioids in regulating cardiovascular function, we administered delta-opioid receptor agonists D-Ala-D-Leu enkephalin (DADLE) and D-Ala-Met enkephalinamide (DAME), and mu-opioid receptor agonist, a morphiceptin analogue (MA), intracisternally in 13 unanesthetized, chronically instrumented adult dogs in 2 doses (25 and 125 micrograms/kg). After an initial transient drop, the R-R interval increased (peak approximately 25-60 min) postadministration of opioids. The time course and the magnitude of the change in R-R interval depended on the agonist: delta-agonists induced a more prolonged and marked change in R-R interval than mu-agonists at both doses. Mean arterial blood pressure (MAP) increased initially but dropped toward or even below base line 30 min after opioids administration. Atropine, given intravenously or intra-arterially at peak action of agonist in relatively low doses (0.02 mg/kg), induced an AV block followed by a marked decrease in R-R interval. There was also an increase in MAP after atropine. Naloxone, given intracisternally, reversed both delta- and mu-opioid effects but did not induce changes in the R-R interval without prior administration of opioids. We conclude that in unanesthetized adult dogs 1) both mu- and delta-receptor opioid agonists prolong the R-R interval, and this depends on the type of receptor stimulated; 2) opioids induce slowing in heart rate, possibly by increasing parasympathetic activity to the heart; 3) enkephalin and morphiceptin analogues induce a biphasic response in MAP; and 4) endorphins do not modulate cardiovascular function tonically; we speculate that they can alter the R-R interval and MAP in the presence of stimuli.

De [~ur~mrrztt c~/'Pm/rutrrc~.c (Pulrnonury Dirr.cion) I tot, total respiratory max(RR), maximum R R interval within a respiratory cycle min(RR), minimum R R interval within a respiratory cycle range(RR), difference between min(RR) and max(RR) NTS, nucleus tractus solitarius N A , nucleus ambiguus V M N , vagal motoneuronsnumber of years (3). We have demonstrated previously that HRV is abnormal in certain groups of infants who are at risk of sudden death (4, 5) and more recently, it as been shown that HRV can be used to estimate cardiac age in adult humans (ti. 7).We (8) and others (9-12) have previously examined the relation between breathing and heart rate and found that HRV is closely tied to breathing in mature subjects. However, HRV is not determined only by breathing, especially in early life (8. 12). For instance, during apnea or lack of breathing, heart rate varies, albeit much less than during breathing. These heart rate changes during respiratory pauses have not been studied in detail. For example, we d o not know the time course of the change in RR interval during pauses in early life and how these changes compare with those in the mature subject. In order to understand further the mechanisms that control heart rate and HRV, we examined herein the time course and the change in heart rate during respiratory pauses and compared them to those during breathing. Since the ANS is not mature early in life (8,(12)(13)(14) and since the ANS plays a major role in HRV (10). we studied the heart rate response to a respiratory pause in early life (puppies) and in an adult mature animal (dog). METHODS

To investigate the changes in diaphragm electromyogram (EMG) during the course of severe loaded breathing, we subjected five conscious adult sheep to inspiratory flow resistive breathing (resistance greater than 150 cmH2O X l-1 X s) for up to 2-3 h and studied the total EMG power per breath (iEMG) and the EMG power per unit time after dividing the duration of EMG activity within each breath into three equal parts (iEMG1, iEMG2, and iEMG3). Both total breath iEMG and transdiaphragmatic pressure (Pdi) increased, remained at a high level for a certain period of time, and then started to fall. A change in the pattern of iEMG within a breath was observed during loaded breathing. The increase in total-breath iEMG was associated mostly with an increase in iEMG3, or the last part of the EMG power within each inspiration. Similarly, the decrease in total breath iEMG was primarily due to a decrease in iEMG3. We conclude that, in sheep subjected to severe IFR loads for prolonged periods the marked increase in total-breath iEMG at the beginning of loaded breathing and the marked decrease in this iEMG at the time of decrease in Pdi are largely due to changes in iEMG that occur during the latter third of each breath. We speculate that during loaded breathing the recruitment pattern of diaphragmatic muscle fibers changes during the course of an inspiratory effort.