Chaotic behavior of the coronary circulation

The regulation of the coronary circulation is a complex paradigm in which many inputs that influence vasomotor tone have to be integrated to provide the coronary vasomotor adjustments to cardiac metabolism and to perfusion pressure. We hypothesized that the integration of many disparate signals that influence membrane potential of smooth muscle cells, calcium sensitivity of contractile filaments, receptor trafficking result in complex non-linear characteristics of coronary vasomotion. To test this hypothesis, we measured an index of vasomotion, flowmotion, the periodic fluctuations of flow that reflect dynamic changes in resistances in the microcirculation. Flowmotion was continuously measured in periods ranging from 15 to 40 min under baseline conditions, during antagonism of NO synthesis, and during combined purinergic and NOS antagonism in the beating heart of anesthetized open-chest dogs. Flowmotion was measured in arterioles ranging from 80 to 135 μm in diameter. The signals from the flowmotion measurements were used to derive quantitative indices of non-linear behavior: power spectra, chaotic attractors, correlation dimensions, and the sum of the Lyapunov exponents (Kolmogorov–Sinai entropy), which reflects the total chaos and unpredictability of flowmotion. Under basal conditions, the coronary circulation demonstrated chaotic non-linear behavior with a power spectra showing three principal frequencies in flowmotion. Blockade of nitric oxide synthase or antagonism of purinergic receptors did not affect the correlation dimensions, but significantly increased the Kolmogorov–Sinai entropy, altered the power spectra of flowmotion, and changed the nature of the chaotic attractor. These changes are consistent with the view that certain endogenous controls, nitric oxide and various purines (AMP, ADP, ATP, adenosine) make the coronary circulation more predictable, and that blockade of these controls makes the control of flow less predictable and more chaotic. Supported by NIH grant HL32788.     

用相空间内邻近轨线伸展的相关性研究脑电的混沌特性

本文的研究针对目前脑电的非线性动力学研究中一个尚未定论的关键问题：脑电究竟是混沌信号还是无序的随机信号？文中介绍了作者的研究成果：用相空间中一对邻近轨线伸展的伸关性来鉴别混沌和无序的随机运动,并应用这种新的混沌行为分析方法证明了脑电的混沌特性,作为比较和验证,本文也介绍了用该方法对加上不同水平噪声和Lorenz系统仿真的研究结果。     

心率信号非线性动力结构的确定

在Silvio等提出的压力反射控制心脏活动的短期压力模型的基础上,推导出关于心率信号的一种四参量的非线性结构,通过实际的心率信号降维分析,表明心率信号存在非线性动力结构,为心率信号是确定性低维混沌的诊断提供了依据。     

Dimensional Analysis of No-Task Human EEG Using the Grassberger-Procaccia Method

A method developed by Grassberger and Procaccia allows estimation of the dimensional complexity of the state-space attractor of a time series. Saturation of dimensional-complexity estimates with increasing values of embedding dimension is considered a strong indication that the time series is governed by deterministic chaos. The present investigation employed the Grassberger-Procaccia method to estimate EEG dimensional complexity in a multi-subject, factorial experiment. Twelve subjects were tested under two no-task conditions (eyes closed and open), with the block of two conditions being repeated four times. EEG was recorded from the nineteen 10-20 loci. Dimensional complexity declined across Blocks 1-3 and then leveled off, and was higher in the eyes-open than in the eyes-closed condition. Condition also interacted with locus in that the increase in dimensional complexity associated with opening the eyes was greater over occipital loci. Comparison with the results of Fourier analysis indicated that a similar but not identical pattern of effects was obtained for alpha (8-12 Hz) power. Further, across the entire data set, if alpha power exceeded a value of about 70 microV2, dimensional complexity was uniformly low, a finding in concert with previous results indicating that the eyes-closed, occipital alpha rhythm possibly represents deterministic chaos of relatively low dimension.     

正常青、老年人心率关联维数研究

本文采用关联维数和相空间图的方法，研究了２０名正常青、老年人的心率变异性。研究结果表明：１０分钟心率数据最适合于关联维数分析；青年人关联维数均值为５．３３５±０．２３８，老年人为４．３７６±０．４２５；正常青年人关联维数高于老年人     

Disrupted Relationships,Chaos, and Altered Family Meals in Food-Insecure Households: Experiences of Caregivers and Children

BackgroundRegular family meals foster healthy physical and social development of children but often occur less frequently in households experiencing food insecurity. How food insecurity influences the quality of these interactions is not understood well.ObjectiveTo better understand family meal experiences of caregivers and children living in food-insecure households.DesignA qualitative method with cross-sectional sample was used, collecting data using semistructured interview guides.ParticipantsTwenty ethnically diverse caregiver–child (aged 9 to 15 years) dyads in South Carolina were interviewed.Statistical analysisData were analyzed using grounded theory in Nvivo 10.ResultsFood-insecure households described family meals that varied in frequency, location, and quality of foods served, especially during times of food shortages. Interpersonal relationships drove the quality of mealtime interactions for these households. Household chaos not only influenced the frequency and location of meals, but also strained mealtime interactions in households with poor interpersonal relationships. In these homes, household chaos included conflicts with work and afterschool schedules, food shortages, coping with poverty and food insecurity (eg, working extra hours or seeking food assistance), and children visiting multiple homes, particularly when food was limited. All households experienced chaos, but strong interpersonal relationships were described as the primary reason for enjoyable mealtime experiences with few disruptions.ConclusionsExploring family meal experiences of children in food-insecure households highlights the importance of interpersonal relationships and regular, positive mealtime interactions that may strengthen emotional connections in families to improve child health outcomes.     

混沌理论与内科学临床教学设计

教学设计是教学过程中的一个重要环节。将混沌理论引入内科学临床教学设计,通过蝴蝶效应、分形与奇异吸引子3个基本概念在临床教学设计中的启示,提出教学过程设计要弹性灵活;要重视元认知的设计与培养;以及采用正负反馈相结合的控制机制;以适应信息时代以人为本、能力培养的教学要求。     

“Dynamic” connectivity in neural systems

The study of functional interdependences between brain regions is a rapidly growing focus of neuroscience research. This endeavor has been greatly facilitated by the appearance of a number of innovative methodologies for the examination of neurophysiological and neuroimaging data. The aim of this article is to present an overview of dynamical measures of interdependence and contrast these with statistical measures that have been more widely employed. We first review the motivation, conceptual basis, and experimental approach of dynamical measures of interdependence and their application to the study of neural systems. A consideration of boot-strap “surrogate data” techniques, which facilitate hypothesis testing of dynamical measures, is then used to clarify the difference between dynamical and statistical measures of interdependence. An overview of some of the most active research areas—such as the study of the “synchronization manifold,” dynamical interdependence in neurophysiology data and the putative role of nonlinear desynchronization—is then given. We conclude by suggesting that techniques based on dynamical interdependence—or “dynamical connectivity”—show significant potential for extracting meaningful information from functional neuroimaging data.     

Deterministic Model of Ion Channel Flipping with Fractal Scaling of Kinetic Rates

The flipping of ion channels in biological membranes has usually been modeled in terms of Markov transitions between open and closed states. The basic assumption of this approach is that channel flipping between open and closed states is an inherent stochastic process, due to random thermal fluctuations of units forming the channel protein. In this paper, we propose a different view of channel flipping, one not involving external stochastic causes. We consider the channel as a physical dynamic system, the unpredictable flipping of which is due to a deterministic mechanism which sustains a chaotic dynamics. In particular, we presume the changes in the channel conformation are due to delayed interaction between the ionic flow through the channel and the protein forming the channel. The model proposed here describes the channel by means of macroscopic physical quantities such as conductance, current, membrane, and reversal potentials and predicts open and closed dwell time distributions consisting of multiple exponential components and exhibiting power-law scaling over a wide range of time scales. The effective kinetic rate computed through use of simulation data shows fractal properties in good agreement with those seen experimentally. This mathematical model of the ion channel is physically consistent in terms of a plausible real system and may provide a novel key to understanding the complex behavior of the flipping process. © 1999 Biomedical Engineering Society. PAC99: 8716Uv, 8710+e, 8717Aa, 0545Df, 8716Dg, 8719Nn, 8714Ee     

太极图揭秘:太极图与生理系统中的定态、振荡和混沌

目的:探讨太极图中潜藏的现代科学意义,并提出一些与其相关的科学研究问题。方法:将太极图与生理系统的某些非线性动力学研究结果进行比较性研究,并做出逻辑推断。结果:太极图与生理系统的极限环振荡所产生的向量场及其运动方程的动力学轨迹具有根本的相似。结论:太极图与生理系统中的定态、极限环振荡以及混沌密切相关,这些包含在太极图中的关于生理系统的极限环振荡性质及其对生物医学的意义是我们今后将要研究和讨论的课题,也是一个有着重大理论和临床价值的研究领域。