Yukio Shimoda

The OFF-pathway dominance of P2X2-purinoceptors is formed without visual experience

Visual input in the critical period is an important determinant of the functions of the visual system, affecting for example the formation of the ocular dominance column in the visual cortex. The final map of columnar organization is usually determined by plastic changes in the critical period, but organization is distorted without adequate visual input. Here, we examined whether formation of the OFF-pathway dominance of P2X(2)-purinoceptor signaling in the mouse retina is the result of visual experience. The P2X(2)-purinoceptor signaling pathway developed during the critical period. However, visual experience in this period produced no plastic change in the formation of the OFF-pathway dominance of P2X(2)-purinoceptor signaling. Our findings suggest that the OFF-pathway dominance of P2X(2)-signaling in the mouse retina is intrinsically programmed.

EVALUATION OF SLEEP BY DETRENDED FLUCTUATION ANALYSIS OF THE HEARTBEAT

There are already‐established methods for investigating biological signals such as rhythmic heartbeats. We used detrended fluctuation analysis (DFA), originally developed by Peng et al. (1995) to check power‐law characteristics, because the method can quantify the heart condition numerically. In this article, we studied the heartbeat of sleeping subjects. Our purpose was to test whether DFA is useful to evaluate the subject’s wellness of both during being awake and sleeping. This is a challenge to measure sleep without complex/expensive machine, an electro encephalography (EEG). We conducted electrophysiological recording to measure heartbeats during sleep using electrocardiograph with three‐leads, one ground electrode and two active electrodes attached to chest. For good recording, a stable baseline must be maintained even when subjects move their body. We needed a tool to ensure long‐term steady recording. We thus invented a new electric‐circuit designed to produce this desired result. This gadget allow...

Low Scaling Exponent during Arrhythmia: Detrended Fluctuation Analysis is a Beneficial Biomedical Computation Tool

Cardiovascular disease is one of the major social health problems. Heart attacks, in particular, are a major social concern because of the unpredictable and silent way they develop. Recently, it was reported that the incidence of myocardial infarction has decreased significantly (Yeh et al., 2010). However, some unlucky patients are unaware that they are at risk for the life threatening disease. We must acknowledge that while the default setting is good health, there is always an onset to a disease and never to a return to good health. This onset results in “silent“ angina, and finally a “silent“ attack can happen. In fact, Dutch researchers estimated that 43% of heart attacks went unrecognized (de Torbal et al., 2006). Our ultimate aim was to predict a heart attack, or at least to quantitatively analyze the heart condition, based on the belief that it is possible to predict a heart attack by observing fluctuations in heartbeat intervals. Fluctuation analysis first appeared in the physical literature a long time ago (Peng et al., 1995). However, strong empirical evidence of its accuracy and usefulness must still be collected. Traditionally, cardiac studies have employed heart rate variability (HRV) to detect the onset of cardiac problems, including disorders of the autonomic nervous system. Problems arise, however, when patients are previously assumed to be healthy before the appearance of symptoms associated with HRV. An earlier marker is necessary because the early identification of symptoms aids in the prevention of the onset of chronic diseases. Detrended fluctuation analysis (DFA) (Peng et al., 1995) was proposed as a potentially useful method for detecting the signs of cardiovascular disease (See Stanley et al., 1999); although DFA has not yet been developed as a practical medical tool, such as the electrocardiogram (EKG). (We prefer the abbreviation “EKG” to “ECG,” with due respect to the inventor, Dutch physiologist, Nobel laureate, Willem Einthoven.) We recently tested the practical usefulness of DFA by using the heart of crustacean-animal models. In the test, we successfully showed that DFA could distinguish between intact and isolated hearts (Yazawa et al., 2004). In that study, we found out that the scaling exponent of the isolated hearts shifted and approached to 0.5 without exception. In turn, the scaling exponent of the intact hearts showed a value of about 1.0 without exception. As a result, we realized that DFA was reliable and useful because DFA was likely able to accurately reflect

Detrended Fluctuation Analysis: An Experiment About the Neural-Regulation of the Heart and Motor Vibration

Acceleratory and inhibitory cardio-regulator nerves innervate the heart of a living creature. The two nerves discharge concurrently to maintain an equilibrium state of the heart. The nerves change their frequency of discharge in a reflexive manner to meet the demand from the periphery, such as augmentation of oxygen supply or vice versa. Consequently, the heart exhibits a dynamic change in rate of pumping and force of contraction. If the control system fails, the heart exhibits an unhealthy state. However, an assessment of a healthy/unhealthy status is uneasy, because we are not able to monitor the nerve activities by non-invasive methods. Therefore, we challenged to detect a state of the heart without nerve-recordings. We used the Detrended Fluctuation Analysis (DFA) by applying it to a heartbeat interval time series because the DFA is believed that it can quantify the state of heart. The objective of this research was to determine whether the DFA technology could function as a useful method for the evaluation of the subject’s quality of a cardiovascular-related illness. We performed DFA on the EKGs (Electrocardiograms) from living organisms and a running motor as well. We conclude that scaling exponents could determine whether the subjects are under sick or healthy conditions.

Quantification of Athlete’s Heart Condition: A Detrended Fluctuation Analysis

Detrended fluctuation analysis (DFA) technology was used to check the heartbeats of athletes in the Indonesian olympic training center. We report results of time series analysis of heartbeat on subjects who underwent ergometer exercise. The objective of this research was to determine whether DFA could function as a useful computation method for the evaluation of the subject’s quality of cardiovascular system. Since there are no 2 individuals that are identical physiologically, we present case studies but novel findings regarding how wellness of subjects can be evaluated by the electrocardiography. Even from the case studies, we can propose a general conclusion that DFA is a new, useful numerical method for quantifying the degree of wellness through the heartbeat recording.

Neurodynamical Control of the Heart of Freely Moving Animals Including Humans

Two kinds of nerves, acceleratory and inhibitory cardio-regulator nerves, innervate the heart. They are known to discharge concurrently to maintain an equilibrium state of the body. The nerves are also known to change their frequency of discharge in a reflexive manner to meet the demand from the periphery; such as augmentation of oxygen supply or vice versa. Consequently, the heart exhibits dynamic change in its pumping rate and force of contraction. If the control system fails, the heart exhibits unhealthy state. However, assessment of healthy/unhealthy status is uneasy because we are not able to monitor the nerve activities by non-invasive methods. Therefore, we challenged to detect state of the heart without nerve-recordings. We used the detrended fluctuation analysis (DFA) applying to heartbeat interval time series because DFA has been believed that it can quantify the state of heart. We performed DFA on the EKGs (electrocardiograms) from various living organisms including humans. The objective of this research was to determine whether the analytical technology, DFA, could function as a useful method for the evaluation of the subject’s quality of cardiovascular-related illness and transition to and from a normal healthy state. We found that DFA could describe brain-heart interaction quantitatively: the scaling exponents of (1) healthy, (2) sick-type (such as stressful or arrhythmic states), and (3) unpredictable-death type (such as ischemic heart disease) were corresponded to individuals who exhibited, (1) nearly one, (2) less than one, and (3) greater than one, respectively. We conclude that scaling exponents could determine whether the subjects are under sick or healthy conditions on the basis of cardiac physiology.Copyright

Detrended Fluctuation Analysis of Arrhythmia: Scaling Exponent as an Index of Heart Wellness

Well-established technologies to analyze biological signals including rhythmic heartbeat are available and accessible to scholars. However, stronger empirical evidence is required to justify the use of these technologies as practical tools in the field of biomedicine. Here we conducted analyses of heartbeat interval time series using an analytical technology developed across three decades—detrended fluctuation analysis (DFA)—to verify the power-law/scaling characteristics of signals that fluctuate in a regular, irregular, or erratic manner. We believe that DFA is a useful tool because it can quantify the heart condition by a scaling exponent, with a value of one (1) set as the default for a healthy state. This baseline value can be compared to a clinical thermometer, where the baseline is 37 °C for a physiologically healthy condition. Our study aimed to ascertain and confirm the utility of DFA in evaluating heart wellness, specifically in the context of studying arrhythmic heartbeat. We present case studies to confirm that DFA is a beneficial tool that quantifies the scaling exponent of a heart’s condition as “nonstationarily” beating and dynamically controlled. From an engineering perspective, we show that the heart condition can be classified into two typical categories: a healthy rhythm with a scaling exponent of one (1.0), and arrhythmia with a lower scaling exponent (0.7 or less).Copyright

DFA, a Biomedical Checking Tool for the Heart Control System

We made our own detrended fluctuation analysis (DFA) program. We applied it to the cardio-vascular system for checking characteristics of the heartbeat of various individuals. Healthy subjects showed a normal scaling exponent, which is near 1.0. This is in agreement with the original report by Peng et al. published in 1990s. We found that the healthy exponents span from 0.9 to 1.19 in our temporary guideline based on our own experiments. In the present study, we investigated the persons who have an extra-systole heartbeat, so called as premature ventricular contractions (PVCs), and revealed that their arrhythmic heartbeat exhibited a low scaling exponent approaching to 0.7 with no exceptions. In addition, alternans, which is the heartbeats in period-2 rhythms, and which is also called as the harbinger of death, exhibited a low scaling exponent like the PVCs. We may conclude that if it would be possible to make a device that equips a DFA program, it might be useful to check the heart condition, and contribute not only in statistical physics but also in biomedical engineering and clinical practice fields; especially for health check. The device is applicable for people who are spending an ordinary life, before they get seriously heart sick.

Two different pathways for choline transport in the mouse retina

Mammalian visual system exhibits significant experience-induced plasticity during a restricted period of early postnatal life. Expression of the plasticity is retarded in animals raised in darkness, suggesting the necessity of visual experience in cortical development. Growing evidences suggest a role of endocannnabinoid system in the plasticity of central nervous system. To explore a possible role of endocannnabinoid system in the developmental plasticity of visual cortex, we examined the developmental regulation of the expression of Type 1 cannabinoid receptor (CB1) and diacylglycerol lipase(DGL), which synthesizes a major endocannabinoid 2-arachidonoylglycerol, in the primary visual cortex (V1) of mice at various ages and those raised in darkness, using immunohistochemistry and western blot analysis. CB1 immunoreactivity was rather faint and mainly existed in layer VI of V1 at postnatal days (P)10. In animals from P20 to P100, intense CB1 immunoreactivity was observed in layer II/III and VI of V1. The CB1 signal was mainly colocalized with inhibitory nerve terminals containing vesicular GABA transporter rather than with the terminals containing vesicular glutamate transporters. Relative amount of CB1 protein in V1 did not change significantly from P10 to P100. On the other hand, DGL, which is assumed to localize at post synaptic sites, distributed at lower part of layer II/III and layer IV from P30 to P100. DGLprotein level in V1 significantly increased during development from P10 to P40 and then decreased to P100 in V1. Mice rearing in the dark from birth to P30 exhibited similar layer distribution of CB1 and DGLimmunoreactivity to those in normal animal at P30. Therefore, the postnatal maturation of laminar distribution of CB1 and DGLwould not require sensory experience.

Evaluation of Wellness by Detrended Fluctuation Analysis of Heartbeats

We used detrended fluctuation analysis (DFA), which was originally developed by Peng et al. (1995) to check power-law characteristics, to study the heartbeats of various subjects. Our purpose was to determine whether DFA is a useful method for the evaluation of a subject’s quality of recovery from cardiovascular-related illness and transition to a normal healthy state. Here, we report on subjects who underwent rehabilitation thermal therapy, subjects who developed premature ventricular contractions, and other subjects, including healthy subjects. The perceived level of wellness varies among subjects because the physiology of no 2 individuals is identical. However, several case studies have shown how wellness of subjects can be evaluated using heartbeat recordings. We conclude that DFA is a new, useful numerical method for quantifying the degree of wellness and the transition from sickness to wellness.Copyright