Fine temporal structure of cardiorespiratory synchronization.

نویسندگان

  • Sungwoo Ahn
  • Jessica Solfest
  • Leonid L Rubchinsky
چکیده

Cardiac and respiratory rhythms are known to exhibit a modest degree of phase synchronization, which is affected by age, diseases, and other factors. We study the fine temporal structure of this synchrony in healthy young, healthy elderly, and elderly subjects with coronary artery disease. We employ novel time-series analysis to explore how phases of oscillations go in and out of the phase-locked state at each cycle of oscillations. For the first time we show that cardiorespiratory system is engaged in weakly synchronized dynamics with a very specific temporal pattern of synchrony: the oscillations go out of synchrony frequently, but return to the synchronous state very quickly (usually within just 1 cycle of oscillations). Properties of synchrony depended on the age and disease status. Healthy subjects exhibited more synchrony at the higher (1:4) frequency-locking ratio between respiratory and cardiac rhythms, whereas subjects with coronary artery disease exhibited relatively more 1:2 synchrony. However, multiple short desynchronization episodes prevailed regardless of the age and disease status. The same average synchrony level could be alternatively achieved with few long desynchronizations, but this was not observed in the data. This implies functional importance of short desynchronization dynamics. These dynamics suggest that a synchronous state is easy to create if needed but is also easy to break. Short desynchronization dynamics may facilitate the mutual coordination of cardiac and respiratory rhythms by creating intermittent synchronous episodes. It may be an efficient background dynamics to promote adaptation of cardiorespiratory coordination to various external and internal factors.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

معرفی شبکه های عصبی پیمانه ای عمیق با ساختار فضایی-زمانی دوگانه جهت بهبود بازشناسی گفتار پیوسته فارسی

In this article, growable deep modular neural networks for continuous speech recognition are introduced. These networks can be grown to implement the spatio-temporal information of the frame sequences at their input layer as well as their labels at the output layer at the same time. The trained neural network with such double spatio-temporal association structure can learn the phonetic sequence...

متن کامل

Model for cardiorespiratory synchronization in humans.

Recent experimental studies suggest that there is evidence for a synchronization between human heartbeat and respiration. We develop a physiologically plausible model for this cardiorespiratory synchronization, and numerically show that the model can exhibit stable synchronization against given perturbations. In our model, in addition to the well-known influence of respiration on heartbeat, the...

متن کامل

Cardiorespiratory Synchronization: is it a Real Phenomenon?

In this work we present a quantitative approach to the analysis of cardiorespiratory synchronization, which is a newly discovered phenomenon. The primary aim of this stu+ is to determine whether cardiorespiratory synchronization is a real phenomenon or a random one. We utilized the surrogate data analysis approach. A surrogate data set was constructed ji-om recordings of ECG and respiration obt...

متن کامل

Fine temporal structure of beta oscillations synchronization 1 in subthalamic nucleus in Parkinson ’ s disease

Fine temporal structure of beta oscillations synchronization 1 in subthalamic nucleus in Parkinson’s disease 2 3 4 Choongseok Park, Robert M Worth, Leonid L Rubchinsky 5 6 1 Department of Mathematical Sciences and Center for Mathematical Biosciences, Indiana 7 University Purdue University Indianapolis, Indianapolis, IN 46202 8 2 Department of Neurosurgery, Indiana University School of Medicine,...

متن کامل

Empirical mode decomposition and synchrogram approach to cardiorespiratory synchronization.

We use the empirical mode decomposition method to decompose experimental respiratory signals into a set of intrinsic mode functions (IMFs), and consider one of these IMFs as a respiratory rhythm. We then use the Hilbert spectral analysis to calculate the instantaneous phase of the IMF. Heartbeat data are finally incorporated to construct the cardiorespiratory synchrogram, which is a visual tool...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • American journal of physiology. Heart and circulatory physiology

دوره 306 5  شماره 

صفحات  -

تاریخ انتشار 2014