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Vasilis Z Marmarelis

Publications and source records attributed to Vasilis Z Marmarelis.

9 recordsLinked to original sources
PubMed2006

Principal dynamic mode analysis of action potential firing in a spider mechanoreceptor.

The encoding of mechanical stimuli into action potentials in two types of spider mechanoreceptor neurons is modeled by use of the principal dynamic modes (PDM) methodology. The PDM model is equivalent to the general Wiener-Bose model and consists of a minimum set of linear dynamic filters (PDMs), followed by a multivariate static nonlinearity and a threshold function. The PDMs are obtained by performing eigen-decomposition of a matrix constructed using the first-order and second-order Volterra kernels of the system, which are estimated by means of the Laguerre expansion technique, utilizing measurements of pseudorandom mechanical stimulation (input signal) and the resulting action potentials (output signal). The static nonlinearity, which can be viewed as a measure of the probability of action potential firing as a function of the PDM output values, is computed as the locus of points of the latter that correspond to output action potentials. The performance of the model is assessed by computing receiver operating characteristic (ROC) curves, akin to the ones used in decision theory and quantified by computing the area under the ROC curve. Three PDMs are revealed by the analysis. The first PDM exhibits a high-pass characteristic, illustrating the importance of the velocity of slit displacement in the generation of action potentials at the mechanoreceptor output, while the second and third PDMs exhibit band-pass and low-pass characteristics, respectively. The corresponding three-input nonlinearity exhibits asymmetric behavior with respect to its arguments, suggesting directional dependence of the mechanoreceptor response on the mechanical stimulation and the PDM outputs, in agreement to our findings from a previous study (Ann Biomed Eng 27:391-402, 1999). Differences between the Type A and B neurons are observed in the zeroth-order Volterra kernels (related to the average firing), as well as in the magnitudes of the second and third PDMs that perform band-pass and low-pass processing of the input signal, respectively.

Action Potentials↗
PubMed2006

Cerebral hemodynamics during orthostatic stress assessed by nonlinear modeling.

The effects of orthostatic stress, induced by lower body negative pressure (LBNP), on cerebral hemodynamics were examined in a nonlinear context. Spontaneous fluctuations of beat-to-beat mean arterial blood pressure (MABP) in the finger, mean cerebral blood flow velocity (MCBFV) in the middle cerebral artery, as well as breath-by-breath end-tidal CO2 concentration (P(ET(CO2))) were measured continuously in 10 healthy subjects under resting conditions and during graded LBNP to presyncope. A two-input nonlinear Laguerre-Volterra network model was employed to study the dynamic effects of MABP and P(ET(CO2)) changes, as well as their nonlinear interactions, on MCBFV variations in the very low (VLF; below 0.04 Hz), low (LF; 0.04-0.15 Hz), and high frequency (HF; 0.15-0.30 Hz) ranges. Dynamic cerebral autoregulation was described by the model terms corresponding to MABP, whereas cerebral vasomotor reactivity was described by the model P(ET(CO2)) terms. The nonlinear model terms reduced the output prediction normalized mean square error substantially (by 15-20%) and had a prominent effect in the VLF range, both under resting conditions and during LBNP. Whereas MABP fluctuations dominated in the HF range and played a significant role in the VLF and LF ranges, changes in P(ET(CO2)) accounted for a considerable fraction of the VLF and LF MCBFV variations, especially at high LBNP levels. The magnitude of the linear and nonlinear MABP-MCBFV Volterra kernels increased substantially above -30 mmHg LBNP in the VLF range, implying impaired dynamic autoregulation. In contrast, the magnitude of the P(ET(CO2))-MCBFV kernels reduced during LBNP at all frequencies, suggesting attenuated cerebral vasomotor reactivity under dynamic conditions. We speculate that these changes may reflect a progressively reduced cerebrovascular reserve to compensate for the increasingly unstable systemic circulation during orthostatic stress that could ultimately lead to cerebral hypoperfusion and syncope.

Adult↗
PubMed2006

Segmentation methodology for automated classification and differentiation of soft tissues in multiband images of high-resolution ultrasonic transmission tomography.

This paper presents a novel segmentation methodology for automated classification and differentiation of soft tissues using multiband data obtained with the newly developed system of high-resolution ultrasonic transmission tomography (HUTT) for imaging biological organs. This methodology extends and combines two existing approaches: the L-level set active contour (AC) segmentation approach and the agglomerative hierarchical kappa-means approach for unsupervised clustering (UC). To prevent the trapping of the current iterative minimization AC algorithm in a local minimum, we introduce a multiresolution approach that applies the level set functions at successively increasing resolutions of the image data. The resulting AC clusters are subsequently rearranged by the UC algorithm that seeks the optimal set of clusters yielding the minimum within-cluster distances in the feature space. The presented results from Monte Carlo simulations and experimental animal-tissue data demonstrate that the proposed methodology outperforms other existing methods without depending on heuristic parameters and provides a reliable means for soft tissue differentiation in HUTT images.

Algorithms↗
PubMed2005

Soft tissue differentiation using multiband signatures of high resolution ultrasonic transmission tomography.

In this paper, we are interested in soft tissue differentiation by multiband images obtained from the High-Resolution Ultrasonic Transmission Tomography (HUTT) system using a spectral target detection method based on constrained energy minimization (CEM). We have developed a new tissue differentiation method (called "CEM filter bank") consisting of multiple CEM filters specially designed for detecting multiple types of tissues. Statistical inference on the output of the CEM filter bank is used to make a decision based on the maximum statistical significance rather than the magnitude of each CEM filter output. We test and validate this method through three-dimensional interphantom/intraphantom soft tissue classification where target profiles obtained from an arbitrary single slice are used for differentiation over multiple other tomographic slices. The performance of the proposed classifier is assessed using receiver operating characteristic analysis. We also apply our method to classify tiny structures inside a bovine kidney and sheep kidneys. Using the proposed method we can detect physical objects and biological tissues such as styrofoam balls, chicken tissue, calyces, and vessel-duct successfully.

Algorithms↗
PubMed2005

Half-thickness inversion layer high-frequency ultrasonic transducers using LiNbO3 single crystal.

Half-thickness inversion layer high-frequency ultrasonic transducers were fabricated using lithium niobate (LiNbO3) single crystal plate. The transducers developed for this study used a 36 degrees rotated Y-cut LiNbO3 thin plate with an active element thickness of 115 microm. The designed center frequency was in the range of 30 to 60 MHz. Half-thickness inversion layer was formed after the sample was annealed at a high temperature, and it is shown that the inversion layer thickness can be controlled by the temperature. Silver powder/epoxy composite and parylene were used as acoustic matching layers. A lossy silver epoxy was used as the backing material. Using an analytical method, the electrical impedance for different inversion layer ratios was determined. The measured resonant frequency was consistent with the modeled data. Even-order higher frequency broadband ultrasonic transducers with a center frequency at 60 MHz was obtained using half-thickness inversion layer of LiNbO3 single crystal.

Journal Article↗
PubMed2005

An analytical model of multilayer ultrasonic transducers with an inversion layer.

Inversion layer ultrasonic transducers have been investigated recently as an interesting approach in wideband transducer design. In this paper we present an analytical model of multilayer ultrasonic transducers with an inversion layer. Our analysis of the wave propagation problem of an inversion layer transducer includes a functional decomposition of the electrical input impedance. It becomes clear from this decomposition that an inversion layer transducer can be modeled as three elements in series connection, i.e., a clamped capacitance, a classical motional impedance, and a coupled motional impedance. The first two elements make up the classical model of a single element transducer. The coupled motional impedance describes the coupled interaction between the regular and the inverted piezoelectric sublayers, and thus reflects the effect of an inversion layer. We present examples which show that inversion layer transducers are advantageous in achieving such useful features as dual-frequency operation mode as used in harmonic imaging or broadband performance desired in most ultrasonic applications.

Journal Article↗
PubMed2004

Nonlinear modeling of the dynamic effects of arterial pressure and CO2 variations on cerebral blood flow in healthy humans.

The effect of spontaneous beat-to-beat mean arterial blood pressure fluctuations and breath-to-breath end-tidal CO2 fluctuations on beat-to-beat cerebral blood flow velocity variations is studied using the Laguerre-Volterra network methodology for multiple-input nonlinear systems. The observations made from experimental measurements from ten healthy human subjects reveal that, whereas pressure fluctuations explain most of the high-frequency blood flow velocity variations (above 0.04 Hz), end-tidal CO2 fluctuations as well as nonlinear interactions between pressure and CO2 have a considerable effect in the lower frequencies (below 0.04 Hz). They also indicate that cerebral autoregulation is strongly nonlinear and dynamic (frequency-dependent). Nonlinearities are mainly active in the low-frequency range (below 0.04 Hz) and are more prominent in the dynamics of the end-tidal CO2-blood flow velocity relationship. Significant nonstationarities are also revealed by the obtained models, with greater variability evident for the effects of CO2 on blood flow velocity dynamics.

Adult↗