Biomedical subjects

V Z Marmarelis

Publications and source records attributed to V Z Marmarelis.

At least 19 recordsLinked to original sources

PubMed2002

Modeling of nonlinear physiological systems with fast and slow dynamics. I. Methodology.

Effective modeling of nonlinear dynamic systems can be achieved by employing Laguerre expansions and feedforward artificial neural networks in the form of the Laguerre-Volterra network (LVN). This paper presents a different formulation of the LVN that can be employed to model nonlinear systems displaying complex dynamics effectively. This is achieved by using two different filter banks, instead of one as in the original definition of the LVN, in the input stage and selecting their structural parameters in an appropriate way. Results from simulated systems show that this method can yield accurate nonlinear models of Volterra systems, even when considerable noise is present, separating at the same time the fast from the slow components of these systems effectively.

Algorithms↗

PubMed2002

Modeling of nonlinear physiological systems with fast and slow dynamics. II. Application to cerebral autoregulation.

Dynamic autoregulation of cerebral hemodynamics in healthy humans is studied using the novel methodology of the Laguerre-Volterra network for systems with fast and slow dynamics (Mitsis, G. D., and V. Z. Marmarelis, Ann. Biomed. Eng. 30:272-281, 2002). Since cerebral autoregulation is mediated by various physiological mechanisms with significantly different time constants, it is used to demonstrate the efficacy of the new method. Results are presented in the time and frequency domains and reveal that cerebral autoregulation is a nonlinear and dynamic (frequency-dependent) system with considerable nonstationarities. Quantification of the latter reveals greater variability in specific frequency bands for each subject in the low and middle frequency range (below 0.1 Hz). The nonlinear dynamics are prominent also in the low and middle frequency ranges, where the frequency response of the system exhibits reduced gain.

Adult↗

PubMed2000

A novel network for nonlinear modeling of neural systems with arbitrary point-process inputs.

This paper address the issue of nonlinear model estimation for neural systems with arbitrary point-process inputs using a novel network that is composed of a pre-processing stage of a Laguerre filter bank followed by a single hidden layer with polynomial activation functions. The nonlinear modeling problem for neural systems has been attempted thus far only with Poisson point-process inputs and using cross-correlation methods to estimate low-order nonlinearities. The specific contribution of this paper is the use of the described novel network to achieve practical estimation of the requisite nonlinear model in the case of arbitrary (i.e. non-Poisson) point-process inputs and high-order nonlinearities. The success of this approach has critical implications for the study of neuronal ensembles, for which nonlinear modeling has been hindered by the requirement of Poisson process inputs and by the presence of high-order nonlinearities. The proposed methodology yields accurate models even for short input-output data records and in the presence of considerable noise. The efficacy of this approach is demonstrated with computer-simulated examples having continuous output and point-process output, and with real data from the dentate gyrus of the hippocampus.

Animals↗

PubMed2000

Laser induced fluorescence attenuation spectroscopy: detection of hypoxia.

The development of a new laser-induced fluorescence (LIF) spectroscopy technique for the measurement of the attenuation spectrum of tissue is described. The technique, termed laser-induced fluorescence attenuation spectroscopy (LIFAS), has been applied to study the effects of hypoxia on the in vivo optical properties of renal and myocardial tissue in the 350-600-nm band. Excimer laser (Xe-Cl) is used to excite a small volume of the tissue (rabbit model, N = 20) and induce autofluorescence. The emitted LIF is monitored fiberoptically at two locations that are unevenly displaced about the fluorescing volume. The optical attenuation of the tissue is calculated from the dual LIF measurements by assuming an exponential decay of the fluorescence with distance. The results indicate that hypoxia modulates the attenuation spectrum leading to characteristic changes in its shape. Primarily, the spectral profile becomes more concave between 455 nm and 505 nm and two spectral peaks at about 540 and 580 nm disappear leaving in their place a single peak at about 555 nm. The attenuation spectra of normoxic and hypoxic tissue are used to train partial least squares multivariate model for spectral classification. The model detected acute renal and myocardial hypoxia with an accuracy greater than 90% (range: 90%-96%) and 74% (range: 74%-90%), respectively.

Animals↗

PubMed1998

Nonlinear system analysis of renal autoregulation in normotensive and hypertensive rats.

We compared the dynamic characteristics in renal autoregulation of blood flow of normotensive Sprague-Dawley rats (SDR) and spontaneously hypertensive rats (SHR), using both linear and nonlinear systems analysis. Linear analysis yielded only limited information about the differences in dynamics between SDR and SHR. The predictive ability, as determined by normalized mean-square errors (NMSE), of a third-order Volterra model is better than for a linear model. This decrease in NMSE with a third-order model from that of a linear model is especially evident at frequencies below 0.2 Hz. Furthermore, NMSE are significantly higher in SHR than SDR, suggesting a more complex nonlinear system in SHR. The contribution of the third-order kernel in describing the dynamics of renal autoregulation in arterial blood pressure and blood flow was found to be important. Moreover, we have identified the presence of nonlinear interactions between the oscillatory components of the myogenic mechanism and tubuloglomerular feedback (TGF) at the level of whole kidney blood flow in SDR. An interaction between these two mechanisms had previously been revealed for SDR only at the single nephron level. However, nonlinear interactions between the myogenic and TGF mechanisms are not detected for SHR.

Animals↗

PubMed1995

Nonlinear neuronal mode analysis of action potential encoding in the cockroach tactile spine neuron.

Neuronal mode analysis is a recently developed technique for modelling the behavior of nonlinear systems whose outputs consist of action potentials. The system is modelled as a set of parallel linear filters, or modes, which feed into a multi-input threshold. The characteristics of the principal modes and the multi-input threshold device can be derived from Laguerre function expansions of the computed first- and second-order Volterra kernels when the system is stimulated with a randomly varying input. Neuronal mode analysis was used to model the encoder properties of the cockroach tactile spine neuron, a nonlinear, rapidly adapting, sensory neuron with reliable behavior. The analysis found two principal modes, one rapid and excitatory, the other slower and inhibitory. The two modes have analogies to two of the pathways in a block-structured model of the encoder that was developed from previous physiological investigations of the neuron. These results support the block-structured model and offer a new approach to identifying the components responsible for the nonlinear dynamic properties of this neuronal encoder.

Action Potentials↗

PubMed1995

Spectro-temporal studies of Xe-Cl excimer laser-induced arterial wall fluorescence.

We report on spectro-temporal fluorescence studies of cadaver femoral arterial walls at different stages in the progression of atherosclerosis. After excitation with a Xe-Cl excimer pulse, the time course of the fluorescence spectrum was recorded over time, and time-resolved multispectral analysis was performed. Then, under the assumption of linearity, we derived a linear spectro-temporal kernel (a weighting function) which describes the temporal behavior of the fluorescence process independently of the pulse width of the photoexcitation. The data analysis revealed both static and dynamic fluorescence characteristics which exhibited a good correlation with histological findings.

Arteriosclerosis↗

PubMed1994

Detection of interactions between myogenic and TGF mechanisms using nonlinear analysis.

Previous studies using linear techniques have provided valuable insights into the dynamic characteristics of whole kidney autoregulation and have led to the general conclusion that the myogenic mechanism and tubuloglomerular feedback (TGF) are highly nonlinear control mechanisms. To explore further the dynamic nature of these nonlinear autoregulatory mechanisms, we introduce the technique of nonlinear modeling using Volterra-Wiener kernels. In the past several years, use of Volterra-Wiener kernels for nonlinear approximation has been most notably applied to neurophysiology. Recent advances in algorithms for computation of the kernels have made this technique more attractive for the study of the dynamics of nonlinear physiological systems, such as the system mediating renal autoregulation. In this study, the general theory and requirements for using this technique are discussed. The feasibility of using the technique on whole kidney pressure and flow data is examined, and a basis for using the Volterra-Wiener kernels to detect interactions between physiological control mechanisms is established. As a result of this method, we have identified the presence of interactions between the oscillating components of the myogenic and the TGF mechanisms at the level of the whole kidney blood flow in normotensive rats. An interaction between these oscillatory components had previously been demonstrated only at the single-nephron level.

Animals↗

PubMed1993

On the efficacy of linear system analysis of renal autoregulation in rats.

In order to assess the linearity of the mechanisms subserving renal blood flow autoregulation, broad-band arterial pressure fluctuations at three different power levels were induced experimentally and the resulting renal blood flow responses were recorded. Linear system analysis methods were applied in both the time and frequency domain. In the frequency domain, spectral estimates employing FFT, autoregressive moving average (ARMA) and moving average (MA) methods were used; only the MA model showed two vascular control mechanisms active at 0.02-0.05 Hz and 0.1-0.18 Hz consistent with previous experimental findings [Holstein-Rathlou et al., Amer. J. Physiol., vol. 258, 1990.]. In the time domain, impulse response functions obtained from the MA model indicated likewise the presence of these two vascular control mechanisms, but the ARMA model failed to show any vascular control mechanism at 0.02-0.05 Hz. The residuals (i.e., model prediction errors) of the MA model were smaller than the ARMA model for all levels of arterial pressure forcings. The observed low coherence values and the significant model residuals in the 0.02-0.05 Hz frequency range suggest that the tubuloglomerular feedback (TGF) active in this frequency range is a nonlinear vascular control mechanism. In addition, experimental results suggest that the operation of the TGF mechanism is more evident at low/moderate pressure fluctuations and becomes overwhelmed when the arterial pressure forcing is too high.

Animals↗

PubMed1993

Modeling of neural systems by use of neuronal modes.

A methodology for modeling spike-output neural systems from input-output data is proposed, which makes use of "neuronal modes" (NM) and "multi-input threshold" (MT) operators. The modeling concept of NM's was introduced in a previously published paper in order to provide concise and general mathematical representations of the nonlinear dynamics involved in signal transformation and coding by a class of neural systems. This paper presents and demonstrates (with computer simulations) a method by which the NM's are determined using the 1st- and 2nd-order kernel estimates of the system, obtained from input-output data. The MT operator (i.e., a binary operator with multiple real-valued operands which are the outputs of the NM's) possesses an intrinsic refractory mechanism and generates the sequence of output spikes. The spike-generating characteristics of the MT operator are determined by the "trigger regions" defined on the basis of data. This approach is offered as a reasonable compromise between modeling complexity and prediction accuracy, which may provide a common methodological framework for modeling a certain class of neural systems.

Computer Simulation↗

PubMed1991

Wiener analysis of nonlinear feedback in sensory systems.

Experimental studies of certain sensory systems (e.g., vertebrate retinal cells and auditory fibers) have yielded qualitative evidence of the presence of nonlinear feedback. However, no methods have been available to provide the tools for quantitative analysis of this nonlinear feedback mechanism and subsequent modeling of the overall dynamics of these sensory systems. Recent results offer the analytical means to relate Wiener kernel measurements with corresponding nonlinear feedback models and, thus, the ability to model the overall dynamics of such sensory systems. Furthermore, our analytical results offer an explanation for experimentally observed changes in the waveform of Wiener kernel estimates obtained for different white-noise input mean and/or power levels.

Animals↗

PubMed1989

Estimation of peripheral chemoreflex gain from spontaneous sigh responses.

A method is proposed for quantifying the responsiveness of the peripheral chemoreflex loop to CO2 by utilizing the natural fluctuations in ventilation and end-tidal PCO2 which occur subsequent to the appearance of spontaneous sighs. The advantage of this method lies in its simplicity and noninvasiveness: the need for administering inhaled mixtures with high CO2 content is eliminated. Using autoregressive moving-average (ARMA) analysis, we demonstrate that post-sigh responses can be adequately described by a simple chemoreflex model that contains first-order dynamics and a pure time delay. The effective gain of this model is shown to reflect peripheral chemosensitivity closely when the estimation procedure is applied to 'data' obtained from computer simulations of the respiratory control system. Although central chemosensitivity affects the absolute values of effective gain, the slope of the linear correlation between effective and peripheral gains remains unchanged. Application of the procedure to spontaneously breathing anesthetized dogs shows that, in every case, effective gain increased with the induction of hypoxia, which is known to enhance peripheral chemosensitivity.

Animals↗

PubMed1989

Signal transformation and coding in neural systems.

The subject of signal transformation and coding in neural systems is fundamental in understanding information processing by the nervous system. This paper addresses this issue at the level of neural units (neurons) using nonparametric nonlinear dynamic models. These models are variants of the general Wiener-Bose model, adapted to this problem as to represent the nonlinear dynamics of neural signal transformation using a set of parallel filters (neuron modes) followed by a binary operator with multiple real-valued operands (equal in number to the number of modes). The postulated model constitutes a reasonable compromise between mathematical complexity and current neurophysiological evidence. It incorporates nonlinear dynamics and spike generation mechanisms in a fairly general, yet parsimonious manner. Although this study has objectives limited to a single unit and represents a small contribution in a vast and complex research area, it is hoped that it will facilitate progress in the systematic study of the functional organization of neural systems with multiple units.

Action Potentials↗

PubMed1988

Coherence and apparent transfer function measurements for nonlinear physiological systems.

Many studies of physiological systems utilize input-output experimental data to develop mathematical descriptions (models) of the system dynamics. Linear methods in the frequency domain are most commonly employed to obtain transfer function characteristics in the form of gain and phase plots. Coherence measurements are a companion tool in these studies, aimed at testing the linearity assumption and assessing the quality of the experimental data (i.e. the noise content). Many physiological systems possess intrinsic nonlinearities. The effect of these nonlinearities on the aforementioned measurements has been largely a matter of conjecture. This paper is a rigorous study of how coherence and apparent transfer function measurements are affected by system nonlinearities. The study is placed in the framework of the Volterra-Wiener theory of nonlinear systems, and it is intended to assist biomedical investigators in interpreting their experimental results in such cases. The class of quadratic nonlinear systems is discussed in greater detail, and simulation examples are presented in order to illustrate some of the more practically important analytical derivations.

Animals↗

PubMed1988

Quantifying deficiencies associated with Parkinson's disease by use of time-series analysis.

In order to assess quantitatively the state of the disease or the effect of drugs in parkinsonian patients, it would be helpful to have at our disposal mathematical models that reflect in their parameter values the deficiencies associated with the disease. This paper proposes a class of such models that are easily obtained in practice and lend themselves to useful interpretations. A pursuit manual tracking experiment is used to derive these models for patients with Parkinson's disease undergoing drug therapy and for normal controls. The input (one-dimensional visual target) and operator's output (manual tracking) are analyzed using a time series approach aiming at obtaining an auto-regressive moving-average (ARMA) model that minimizes the mean square error between the actual and model response. This mathematical model takes the form of a difference equation expressing, in discrete time, the present output value as a linear combination of past output values and past and present input values. Our experimental results indicate that a difference equation (ARMA model) involving the two previous output values and the present and past input values fits best both patient and control data. A comparison between the mean estimated model parameters for patients and controls shows a statistically significant difference in two of these parameters. The first parameter, which is significantly increased in patients, relates the current response of the patient to the immediately preceding response which represents an increased 'damping' of the motor dynamics, reflecting the muscular rigidity associated with the disease (motor disorder). The other parameter, which is significantly decreased in patients, represents the relative degree to which the current response of the patient is influenced by the target position information at the previous point in time which points to a deficiency in sensing/processing of this information (possible a sensory disorder). Our results also showed a marked reduction in the mean-square error of a second trial of the experiment in normal subjects but failed to do so for the patients, possibly indicating learning deficiencies associated with the disease.

Adult↗

PubMed1987

Applications of minimum-order Wiener modeling to retinal ganglion cell spatiotemporal dynamics.

In a previous paper (Marmarelis et al. 1986) we presented the concept of minimum-order Wiener (MOW) modeling of continuous-input/spike-output (CISO) systems. The associated MOW methodology aims at obtaining low-order Wiener models for CISO systems of practical interest. The assertion was made that many neurophysiological systems that fall in this class can be studied effectively by the use of this method. We have chosen a sensory system to demonstrate the efficacy of the method with actual experimental data. The response of retinal ganglion cells to spatiotemporal visual stimuli was studied with this approach and a second-order MOW model was obtained. The results appear to corroborate the adequacy of this model in terms of predicting the timing of the output spikes.

Animals↗

PubMed1987

A linear spatio-temporal model of the light-to-bipolar cell system and its response characteristics to moving bars.

A linear spatio-temporal model for the visual pathway from receptor to bipolar cell is presented. This model is based on histological and electrophysiological data obtained from previously published work. The model incorporates the salient linear spatio-temporal dynamic characteristics of the light-to-bipolar cell system, and aims at furthering our understanding of the integrated spatio-temporal response characteristics of this system. This model is used to examine the way spatial and temporal dynamic characteristics combine to form the response of a single bipolar and of a combination of two bipolars to a moving bar stimulus. A unimodal "speed sensitivity curve" is identified that can be used to postulate speed detection schemes based on simple thresholding operations. The dependence of this speed sensitivity curve on specific temporal and spatial parameters of the receptive field is studied, giving rise to some simple speed discrimination schemata.

Animals↗

PubMed1987

Use of a random forcing for high-frequency ventilation.

Previous applications of high-frequency oscillatory ventilation (HFOV) have used cyclic forcings with the frequency of oscillation considered to be a fundamental parameter. A question that is addressed in the present study is whether or not periodicity is an essential requirement for this mode of ventilation to occur. It was found possible to adequately ventilate anesthetized and paralyzed cats with volume excursions below the dead-space level using a random band-limited forcing. Experimental conditions were close to a constant flow variance (VARF) state, and arterial CO2 tension varied linearly as a function of the ratio of noise bandwidth and VARF. Periodicity per se did not appear to be a requirement for HFOV to occur, a result consistent with predictions of Taylor dispersion theory.

Animals↗