Mitsuyuki Nakao

A Novel Extraction Method of Fetal Electrocardiogram From the Composite Abdominal Signal

In contrast to the ultrasonic measurement of fetal heart motion, the fetal electrocardiogram (ECG) provides clinically significant information concerning the electrophysiological state of a fetus. In this paper, a novel method for extracting the fetal ECG from abdominal composite signals is proposed. This method consists of the cancellation of the mothers ECG and blind source separation with the reference signal (BSSR). The cancellation of the mothers ECG component was performed by subtracting the linear combination of mutually orthogonal projections of the heart vector. The BSSR is a fixed-point algorithm, the Lagrange function of which includes the higher order cross-correlation between the extracted signal and the reference signal as the cost term rather than a constraint. This realizes the convexity of the Lagrange function in a simple form, which guarantees the convergence of the algorithm. By practical application, the proposed method has been shown to be able to extract the P and T waves in addition to the R wave. The reliability and accuracy of the proposed method was confirmed by comparing the extracted signals with the directly recorded ECG at the second stage of labor. The gestational age-dependency of the physiological parameters of the extracted fetal ECG also coincided well with that of the magnetocardiogram, which proves the clinical applicability of the proposed method

Period and Phase Adjustments of Human Circadian Rhythms in the Real World

Entrainment of the circadian rhythm has 2 aspects, period and phase adjustments, which are established simultaneously in most nonhuman circadian systems. The human circadian system is unique in its functional structure in which 2 different subsystems are involved; one is the circadian pacemaker analogous to that located in the suprachiasmatic nucleus, and the other is the oscillatory system of unknown nature that drives the rest-activity cycle. The human circadian system shows the endogenous period very close to 24 h under entrainment and less sensitive to photic stimuli than under free running, which may explain stable entrainment in the real word where natural sun lights are unpredictable in terms of the intensity and time of appearance. On the other hand, nonphotic entrainment seems to play a significant role in phase adjustment of the human circadian system. Nonphotic zeitgebers initially directed to the rest-activity cycle may affect the circadian pacemaker through feedback and/or associated LD cycles.

Theta wave amplitude and frequency are differentially correlated with pontine waves and rapid eye movements during REM sleep in rats.

The present study examined the correlations between the dynamics of hippocampal theta waves and pontine waves (P waves) and rapid eye movements (REMs) densities during REM sleep. Theta wave peak frequency and theta amplitude were estimated as the parameters of theta wave dynamics in each 3s segment. The peak frequency and theta amplitude were positively correlated with P wave and REMs densities, however their detailed correlation properties were distinct from each other. Dependency of peak frequency on P wave/REMs density did not change significantly from that on REMs/P wave density. On the other hand, dependency of the theta amplitude on P wave/REMs density significantly increased with an increased REMs/P wave density. Because hippocampal theta waves and P waves are involved in learning and memory functions during REM sleep, the correlation between theta parameters and P wave density might help to clarify these functions.

An interpretation of 1/f fluctuations in neuronal spike trains during dream sleep

The mesencephalic reticular formation (MRF) neurons are regarded as contributing to the activation of the cerebral cortex. We have investigated the statistical characteristics of the single neuronal activity in the MRF of cat during two activated states: paradoxical sleep (PS) and state in which the animal is watching birds (BW). 1/f-like spectra are observed for both PS and BW states, being more pronounced for PS state. For the interpretation of these findings, we have applied the clustering Poisson process, which not only gives rise to a 1/f spectrum but also suggests a generation mechanism. The MRF neuronal activities in PS and BW are closely fitted by the clustering Poisson process, both in terms of power spectral density and counting statistics. These results strongly suggest that the activities of MRF neurons in PS and BW can be interpreted as the superpositions of randomly occurring clusters which consist of various number of impulses.

Spectral distortion properties of the integral pulse frequency modulation model

The integral pulse frequency modulation (IPFM) model has been used for the following two purposes. First, it has been utilized to verify the correspondence between the spectral structure of autonomic input and the estimated spectrum of heart rate variability (HRV), relying mainly on the theoretical work of Bayly (1968). Second, the IPFM model provides a framework for evaluating how precisely the proposed method of HRV analysis could estimate the input spectral structure. However, the appropriateness of the IPFM model for both purposes has not been examined sufficiently in realistic situations. Here, the spectral structure of the pulse train generated by the IPFM model is theoretically derived for an input signal containing multiple frequency components. This is a more general condition than the single sinusoidal input signal used earlier. In accordance with the theoretical results, the magnitude of the spectral distortion is computed for a pair of varied frequencies, considering the corresponding coefficient of variation of interpulse intervals. Results show that the distortion could be nonnegligible under practical values of the coefficient of variation. Such distortion may well affect the spectral structure in the wide frequency range. This study suggests that the spectral structure of HRV should be interpreted carefully, taking the above distortion properties into account, even though the IPFM model appears to be established as a mechanism mediating between autonomic input and heart rate variability.

Altered frequency-dependent characteristics of the cardiac baroreflex in essential hypertension

Blood pressure (BP) oscillations contain rhythmic components of low-, mid-, and high-frequency bands (0.02-0.06, 0.07-0.14, 0.15-0.40 Hz, respectively). Baroreceptors may sense each BP oscillation and induce a buffer reaction. To clarify the frequency-dependent baroreflex response and its possible alteration in patients with high BP, both BP (Finapres) and the RR interval (electrocardiogram) were continuously monitored in untreated patients with essential hypertension (EH) (n = 52) and normotensive subjects (NT) (n = 43). The magnitude and phase response of cardiac beats to BP oscillations were examined by transfer function analysis. Spontaneous baroreflex sensitivity was assessed by linear regression analysis of the BP and RR oscillations. The heart rate responded linearly to BP oscillations in more subjects at mid- and high-frequency bands (83% or more) than at the low-frequency band (60% or less). The phase was approximately zero at the high-frequency band and was consistently negative at the mid- and low-frequency bands. In general, all frequency gains were significantly and positively correlated with spontaneous baroreflex sensitivity. Each frequency gain was smaller in EH patients than in NT subjects, the high-frequency gain more so than the gains at the lower frequencies. In seven young EH patients, treatment with a beta 1-adrenoceptor selective blocker normalized the high-frequency gain and tended to increase the gains at the lower frequencies. These results suggest that the spontaneous baroreflex modulates RR oscillations over a broad frequency range from 0.02 to 0.40 Hz; the effect was most marked at frequencies higher than 0.07 Hz. Furthermore the frequency-dependent characteristics of the cardiac baroreflex were altered in essential hypertension partly because of an increased beta-adrenergic activity.

Instantaneous acceleration and amplification of hippocampal theta wave coincident with phasic pontine activities during REM sleep

Rapid eye movement (REM) sleep is characterized by hippocampal theta waves and phasic spike-like waves originating from the pons, termed ponto-geniculo-occipital (PGO) waves in cats and pontine (P) waves in rats. While the theta wave and PGO/P wave have been suggested to participate in higher-order brain functions, their generation mechanisms and roles in brain functions have been studied independently. Therefore, the present study investigated instantaneous aspects of the relationship between theta waves and PGO/P waves in both cats and rats. Theta wave was instantaneously accelerated several hundred milliseconds before the negative peak of the PGO/P wave in both animals, and was also amplified just before PGO/P wave occurrence. Considering the integrated knowledge provided by studies of both animals, these results suggest that PGO/P wave-related activities in the pons are delivered to the theta wave generator. The activations of the theta wave coincident with PGO/P wave might facilitate cooperative contribution to higher-order brain functions in REM sleep.

Phase-locking of spontaneous and elicited ponto-geniculo-occipital waves is associated with acceleration of hippocampal theta waves during rapid eye movement sleep in cats.

We investigated the temporal relationship between hippocampal theta waves and ponto-geniculo-occipital waves (PGO) during rapid eye movement sleep (REM sleep) in cats. In addition, we analyzed the relationship between hippocampal theta waves and PGO as elicited by tone stimulus (PGO(E)) in order to quantitively characterize the PGO wave generator mechanism. The results showed that a spontaneous PGO tended to be phase-locked to the theta wave, which was more clearly observed in the single PGO than in the cluster. However, cluster PGO(E) tended to be phase-locked as well as single PGO(E). It was therefore suggested that the generator of PGO is activated in relation to the hippocampal theta wave. An acceleration of the theta wave associated with PGO occurrence was found, and was more markedly observed than with the cluster PGO. Although the magnitude of it was less than in the spontaneous case, an acceleration around the PGO(E) was also observed. These results suggest that the generators of theta and PGO receive some common activations, especially when a cluster PGO is generated. The interaction between PGO and hippocampal theta waves is expected to be involved in the possible functions of REM sleep.

Further study on 1/f fluctuations observed in central single neurons during REM sleep

Recently, 1/f fluctuations have been discovered in the single-unit activity of mesencephalic reticular formation (MRF) neurons during REM sleep. In a previous paper, such behavior could satisfyingly be interpreted on the basis of the clustering Poisson process. The question of applicability of this model to other MRF neurons remained unanswered. The present paper reports on 1/f fluctuations in 12 MRF neurons all of which can satisfyingly be modeled by the clustering Poisson process.

Simulation study on dynamics transition in neuronal activity during sleep cycle by using asynchronous and symmetry neural network model

We have found that single neuronal activities in different regions in the brain commonly exhibit the distinct dynamics transition during sleep-waking cycle in cats. Especially, power spectral densities of single neuronal activities change their profiles from the white to the 1/f along with sleep cycle from slow wave sleep (SWS) to paradoxical sleep (PS). Each region has different neural network structure and physiological function. This suggests a globally working mechanism may be underlying the dynamics transition we concern. Pharmacological studies have shown that a change in a wide-spread serotonergic input to these regions possibly causes the neuronal dynamics transition during sleep cycle. In this paper, based on these experimental results, an asynchronous and symmetry neural network model including inhibitory input, which represents the role of the serotonergic system, is utilized to examine the reality of our idea that the inhibitory input level varying during sleep cycle induce that transition. Simulation results show that the globally applied inhibitory input can control the dynamics of single neuronal state evolution in the artificial neural network: 1/f-like power spectral density profiles result under weak inhibition, which possibly corresponds to PS, and white profiles under strong inhibition, which possibly corresponds to SWS. An asynchronous neural network is known to change its state according to its energy function. The geometrical structure of network energy function is thought to vary along with the change in inhibitory level, which is expected to cause the dynamics transition of neuronal state evolution in the network model. These simulation results support the possibility that the serotonergic system is essential for the dynamics transition of single neuronal activities during sleep cycle.