PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “Nonlinear Dynamics”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12Linked to original sources

Nonlinear dynamics of the blood flow studied by Lyapunov exponents.

In order to gain an insight into the dynamics of the cardiovascular system throughout which the blood circulates, the signals measured from peripheral blood flow in humans were analyzed by calculating the Lyapunov exponents. Over a wide range of algorithm parameters, paired values of both the global and the local Lyapunov exponents were obtained, and at least one exponent equaled zero within the calculation error. This may be an indication of the deterministic nature and finite number of degrees of freedom of the cardiovascular system governing the blood-flow dynamics on a time scale of minutes. A difference was observed in the Lyapunov dimension of controls and athletes.

Algorithms↗

Assessment of osseointegration by nonlinear dynamic response.

Quantitative assessment of osseointegration remains a goal of researchers and clinicians alike. In this study, an instrument was designed for this purpose and tested in an animal model. Effective mechanical impedance, linearized for quasi-static force, was measured in 22 implants placed in the hind tibiae of 2 large hounds. The results demonstrate that in this animal long-bone model, the effective impedance of titanium root-form implants exhibits a degree of nonlinear behavior correlated with their state of osseointegration. This observation may be the basis for useful clinical instrumentation.

Acceleration↗

Nonlinear dynamical law governs magnetic field induced changes in lymphoid phenotype.

The results of many different types of animal and human studies dealing with the biological effects of exposure to low frequency electromagnetic fields (EMFs) have consistently been both positive and negative. We addressed the question of why this pattern had occurred so commonly in biological studies involving exposure to EMFs and hypothesized that it stemmed from the prevalent use of a linear model to characterize what are inherently nonlinear input-output relationships. The hypothesis was tested by analyzing biological data using a novel statistical procedure that could be adjusted to detect either nonlinear or linear effects. The reliability of the procedure was established using positive and negative controls and by comparison with the results obtained from sampling a known nonlinear system. In four independent experiments, male and female mice were exposed continuously to 0.1 or 0.5 mT, 60 Hz, for 175 days, and the effect on 20 immune parameters was measured using flow cytometry and functional assays. In each experiment, EMF exposure resulted in statistically significant changes in lymphoid phenotype when and only when the response of the animals to the fields was analyzed as if it were governed by nonlinear laws. Our results suggest that the pattern of inconsistency in the EMF bioeffects studies is an artifact resulting from an incorrect choice of the conceptual model for the relation between the field and the biological effect it causally determines.

Animals↗

Continuous functional magnetic resonance imaging reveals dynamic nonlinearities of "dose-response" curves for finger opposition.

Linear experimental designs have dominated the field of functional neuroimaging, but although successful at mapping regions of relative brain activation, the technique assumes that both cognition and brain activation are linear processes. To test these assumptions, we performed a continuous functional magnetic resonance imaging (MRI) experiment of finger opposition. Subjects performed a visually paced bimanual finger-tapping task. The frequency of finger tapping was continuously varied between 1 and 5 Hz, without any rest blocks. After continuous acquisition of fMRI images, the task-related brain regions were identified with independent components analysis (ICA). When the time courses of the task-related components were plotted against tapping frequency, nonlinear "dose- response" curves were obtained for most subjects. Nonlinearities appeared in both the static and dynamic sense, with hysteresis being prominent in several subjects. The ICA decomposition also demonstrated the spatial dynamics with different components active at different times. These results suggest that the brain response to tapping frequency does not scale linearly, and that it is history-dependent even after accounting for the hemodynamic response function. This implies that finger tapping, as measured with fMRI, is a nonstationary process. When analyzed with a conventional general linear model, a strong correlation to tapping frequency was identified, but the spatiotemporal dynamics were not apparent.

Algorithms↗

NDRAM: nonlinear dynamic recurrent associative memory for learning bipolar and nonbipolar correlated patterns.

This paper presents a new unsupervised attractor neural network, which, contrary to optimal linear associative memory models, is able to develop nonbipolar attractors as well as bipolar attractors. Moreover, the model is able to develop less spurious attractors and has a better recall performance under random noise than any other Hopfield type neural network. Those performances are obtained by a simple Hebbian/anti-Hebbian online learning rule that directly incorporates feedback from a specific nonlinear transmission rule. Several computer simulations show the model's distinguishing properties.

Algorithms↗

[From nonequilibrium thermodynamics to nonlinear dynamics].

Differences between the thermodynamic and kinetic approaches were discussed by using a system with two or more different steady states as an example. It was shown that the behavior of such systems can be described adequately by the kinetic approach only.

Kinetics↗

Nonlinear dynamics and pattern bifurcations in a model for vegetation stripes in semi-arid environments.

In many semi-arid environments, vegetation is self-organised into spatial patterns. The most striking examples of this are on gentle slopes, where striped patterns are typical, running parallel to the contours. Previously, Klausmeier [1999. Regular and irregular patterns in semiarid vegetation. Science 284, 1826-1828.] has proposed a model for vegetation stripes based on competition for water. Here, we present a detailed study of the patterned solutions in the full nonlinear model, using numerical bifurcation analysis of both the pattern odes and the model pdes. We show that patterns exist for a wide range of rainfall levels, and in particular for much lower rainfall than have been considered by previous authors. Moreover, we show that for many rainfall levels, patterns with a variety of different wavelengths are stable, with mode selection dependent on initial conditions. This raises the possibility of hysteresis, and in numerical solutions of the model we show that pattern selection depends on rainfall history in a relatively simple way.

Demography↗

Hybrid grammar-based approach to nonlinear dynamical system identification from biological time series.

We introduce a grammar-based hybrid approach to reverse engineering nonlinear ordinary differential equation models from observed time series. This hybrid approach combines a genetic algorithm to search the space of model architectures with a Kalman filter to estimate the model parameters. Domain-specific knowledge is used in a context-free grammar to restrict the search space for the functional form of the target model. We find that the hybrid approach outperforms a pure evolutionary algorithm method, and we observe features in the evolution of the dynamical models that correspond with the emergence of favorable model components. We apply the hybrid method to both artificially generated time series and experimentally observed protein levels from subjects who received the smallpox vaccine. From the observed data, we infer a cytokine protein interaction network for an individual's response to the smallpox vaccine.

Algorithms↗

Random walks, random sequences, and nonlinear dynamics in human optokinetic nystagmus.

Optokinetic nystagmus (OKN) is a reflexive eye movement with target-following slow phases (SP) alternating with oppositely directed fast phases (FP). We measured the following from OKN in three humans: FP beginning and ending positions, amplitudes, and intervals and SP amplitudes and velocities. We sought to predict future values of each parameter on the basis of past values, using state-space representation of the sequence (time-delay embedding) and local second-order approximation of trajectories. Predictability is an indication of determinism: this approach allows us to investigate the relative contributions of random and deterministic dynamics in OKN. FP beginning and ending positions showed good predictability, but SP velocity was less predictable. FP and SP amplitudes and FP intervals had little or no predictability. FP beginnings and endings were as predictable as randomized versions that retain linear autocorrelation; this is typical of random walks. Predictability of FP intervals did not change under random rearrangement, which is characteristic of a random process. Only linear determinism was demonstrated; nonlinear interactions may exist that would not be detected by our present approach.

Humans↗

[The adaptive regulation of the nonlinear dynamics of brain electrical activity].

The reinforcing automated stimulation of the emotional positive hypothalamic areas which was contingent upon the multiperiodical events in the EEG structure increased the number of episodes with non-linear dynamics. It resulted in an increase in the frequency of the intracranial self-stimulation. Under conditions of controlled experiment a possibility was shown of the intentional experimental formation of the EEG episodes with different types of non-linear dynamics. At the stages preceding the associative learning, the application of fractal analysis enabled revealing a complex character of non-linearity in the bands of the EEG dominant frequencies with a slight tendency to a dominant process. The associative learning produced one dominant non-linear process which determined the dynamics of the whole system. The neurophysiological characteristics of the given adaptive process were determined as well as the difference between this process and the response to control stimulation.

Adaptation, Physiological↗

Significance of time scales in nonlinear dynamical analysis of electroencephalogram signals.

We propose to show in this paper, that the time series obtained from biological systems such as human brain are invariably nonstationary because of different time scales involved in the dynamical process. This makes the invariant parameters time dependent. We made a global analysis of the EEG data obtained from the eight locations on the skull space and studied simultaneously the dynamical characteristics from various parts of the brain. We have proved that the dynamical parameters are sensitive to the time scales and hence in the study of brain one must identify all relevant time scales involved in the process to get an insight in the working of brain.

Adult↗

The receptive field of the primate P retinal ganglion cell, II: Nonlinear dynamics.

The receptive-field properties of retinal ganglion cells (RGCs) provide information about early visual processing. In the primate retina, P cells form the largest class of RGCs (Rodieck, 1988). A detailed exploration of the dynamics of the two subdivisions of the P-cell receptive field--the center and the surround--was undertaken. In the preceding paper (Benardete & Kaplan, 1996), the first-order responses of the center and the surround of P cells were described, which were obtained with a new technique, the multiple m-sequence stimulus (Benardete & Victor, 1994). In this paper, the investigation of P-cell responses measured as S-potentials in the lateral geniculate nucleus (LGN) is continued, and significant nonlinear, second-order responses from the center and the surround are described. These responses are quantified by fitting a mathematical model, the linear-nonlinear-linear (LNL) model (Korenberg, 1973; Korenberg & Hunter, 1986; Victor, 1988) to the data. In a second series of experiments, demonstration that steady illumination of the surround modifies the gain of the center to contrast signals (see also Kaplan & Shapley, 1989) is made. In P ON cells, increasing the steady illumination of the surround decreases the gain and speeds up the center's first-order response. In P OFF cells, increasing the steady illumination of the surround increases the gain of the center while speeding up the response. The results of both sets of experiments are related to the known anatomy and physiology of the P cell.

Animals↗

Cross-correlation frequency-resolved optical gating for studying ultrashort-pulse nonlinear dynamics in arbitrary fibers.

We describe a cross-correlation frequency-resolved optical-gating system specifically designed for studying nonlinear pulse-propagation dynamics in fibers of arbitrary length at telecommunication wavelengths. The formation of optical solitons and the appearance of temporal phase slips are observed in 100 m of fiber. The wide phase-matching bandwidth and high sensitivity of this system allow us to visualize femtosecond-pulse evolution in a range of linear and nonlinear propagation regimes.

Journal Article↗

Nonlinear dynamics as an essential tool for non-destructive characterization of soft nanostructures using tapping-mode atomic force microscopy.

Tapping-mode atomic force microscopy provides a means for successful and non-intrusive characterization of soft physical and biological structures at the nanoscale. Its full potential can only be realized, provided that the response of the oscillating probe tip to the strongly nonlinear, near-field force interactions with the structure and the intermittency of contact can be accurately modelled, analysed, controlled and interpreted. To this end, this paper reviews some experimental observations of fundamentally nonlinear behaviour of the tip dynamics. It discusses the nonlinear phenomenology that explains their presence in the tapping-mode operation of the atomic force microscope. Particular emphasis is placed on the coexistence of different steady-state responses and their origin in transitions across regions of rapidly varying force characteristics. The heuristics of a recently developed method for treating such transitions are presented and insights into its implications are drawn from related micro- and nanoscale applications.

Journal Article↗

[The theta rhythm of the rat hippocampus as a nonlinear dynamic process].

The theta rythm of the rat's hippocampus in paradoxical phase of sleep and in orientational behavior is investigated by estimating the attractor's dimension. It is shown that the theta rhythm of the hippocampus consists of a regular component and an irregular one of high dimension which relation is in the wide variation depending on the state of the animal. The frequency characteristics of both components are revealed as well as the mechanisms of their forming. Some hypothesis that concern their biological nature are suggested.

Animals↗

A biophysical model of nonlinear dynamics underlying plateau potentials and calcium spikes in purkinje cell dendrites.

Computational capabilities of Purkinje cells (PCs) are central to the cerebellum function. Information originating from the whole nervous system converges on their dendrites, and their axon is the sole output of the cerebellar cortex. PC dendrites respond to weak synaptic activation with long-lasting, low-amplitude plateau potentials, but stronger synaptic activation can generate fast, large amplitude calcium spikes. Pharmacological data have suggested the involvement of only the P-type of Ca channels in both of these electric responses. However, the mechanism allowing this Ca current to underlie responses with such different dynamics is still unclear. This mechanism was explored by constraining a biophysical model with electrophysiological, Ca-imaging, and single ion channel data. A model is presented here incorporating a simplified description of [Ca](i) regulation and three ionic currents: 1) the P-type Ca current, 2) a delayed-rectifier K current, and 3) a generic class of K channels activating sharply in the sub-threshold voltage range. This model sustains fast spikes and long-lasting plateaus terminating spontaneously with recovery of the resting potential. Small depolarizing, tonic inputs turn plateaus into a stable membrane state and endow the dendrite with bistability properties. With larger tonic inputs, the plateau remains the unique equilibrium state, showing long traces of transient inhibitory inputs that are called "valley potentials" because their dynamics mirrors that of inverted, finite-duration plateaus. Analyzing the slow subsystem obtained by assuming instantaneous activation of the delayed-rectifier reveals that the time course of plateaus and valleys is controlled by the slow [Ca](i) dynamics, which arises from the high Ca-buffering capacity of PCs. A bifurcation analysis shows that tonic currents modulate sub-threshold dynamics by displacing the resting state along a hysteresis region edged by two saddle-node bifurcations; these bifurcations mark transitions from finite-duration plateaus to bistability and from bistability to valley potentials, respectively. This low-dimensionality model may be introduced into large-scale models to explore the role of PC dendrite computations in the functional capabilities of the cerebellum.

Algorithms↗

Nonlinear dynamics of a gas bubble in an incompressible elastic medium.

A nonlinear model in the form of the Rayleigh-Plesset equation is developed for a gas bubble in an essentially incompressible elastic medium such as a tissue or rubberlike medium. Two constitutive laws for the elastic medium are considered: the Mooney potential, and Landau's expansion of the strain energy density. These two constitutive laws are compared at quadratic order to obtain a relation between their respective elastic constants. Attention is devoted to the relative importance of shear stress on the bubble dynamics, allowing for the equilibrium gas pressure in the bubble to differ substantially from the pressure at infinity. The model for the bubble motion is approximated to quadratic order to assess the importance of shear stress in the surrounding medium relative to that of the gas pressure in the bubble. Relations are derived for the value of the shear wave speed at which the two contributions are comparable, which provide an assessment of when shear stress in the surrounding medium must be taken into account when modeling bubble dynamics.

Journal Article↗