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PubMed2002

Electromigration dispersion in capillary zone electrophoresis. Experimental validation of use of the Haarhoff-Van der Linde function.

This paper provides experimental validation of the use of the Haarhoff-Van der Linde (HVL) peak fitting function to fit experimental capillary zone electrophoresis (CZE) electropherograms. The test mixtures were composed of paraquat over a five order of magnitude concentration range (1.2 microM to 120 mM) and 4-aminopyridine at constant concentration (0.53 mM) as internal standard. Peak descriptors and electrophoresis parameters were extracted reliably by a Gaussian function from 4 to 40 microM; by the HVL function from 120 microM to 4 mM; and by a triangular function from 4 to 120 mM. The HVL function can be used where there is significant peak asymmetry due to electromigration distortion (EMD) and the Gaussian contribution toward the peak variance is greater than 25%. The peak centre (a1) and the Gaussian variance (a2) of the paraquat peak are shown to be independent of concentration. Diffusion coefficients obtained from a2 for both analytes were found to be in good agreement with their theoretical values. For all peaks where the distortion coefficient (a3) can be extracted, this parameter is shown to be directly proportional to the sample loading, as predicted by EMD theory. For the 4-aminopyridinium ion, mobilities calculated from a3 and measured independently are in excellent agreement. These results show that the HVL function accurately describes the two major processes, diffusion and EMD. contributing to the variance during a CZE separation.

Electrophoresis, Capillary↗

PubMed2002

Fractal characterization of complexity in temporal physiological signals.

This review first gives an overview on the concept of fractal geometry with definitions and explanations of the most fundamental properties of fractal structures and processes like self-similarity, power law scaling relationship, scale invariance, scaling range and fractal dimensions. Having laid down the grounds of the basics in terminology and mathematical formalism, the authors systematically introduce the concept and methods of monofractal time series analysis. They argue that fractal time series analysis cannot be done in a conscious, reliable manner without having a model capable of capturing the essential features of physiological signals with regard to their fractal analysis. They advocate the use of a simple, yet adequate, dichotomous model of fractional Gaussian noise (fGn) and fractional Brownian motion (fBm). They demonstrate the importance of incorporating a step of signal classification according to the fGn/fBm model prior to fractal analysis by showing that missing out on signal class can result in completely meaningless fractal estimates. Limitation and precision of various fractal tools are thoroughly described and discussed using results of numerical experiments on ideal monofractal signals. Steps of a reliable fractal analysis are explained. Finally, the main applications of fractal time series analysis in biomedical research are reviewed and critically evaluated.

Algorithms↗

PubMed1999

Intrinsic envelope fluctuations and modulation-detection thresholds for narrow-band noise carriers.

A model is presented which calculates the intrinsic envelope power of a bandpass noise carrier within the passband of a hypothetical modulation filter tuned to a specific modulation frequency. Model predictions are compared to experimentally obtained amplitude modulation (AM) detection thresholds. In experiment 1, thresholds for modulation rates of 5, 25, and 100 Hz imposed on a bandpass Gaussian noise carrier with a fixed upper cutoff frequency of 6 kHz and a bandwidth in the range from 1 to 6000 Hz were obtained. In experiment 2, three noises with different spectra of the intrinsic fluctuations served as the carrier: Gaussian noise, multiplied noise, and low-noise noise. In each case, the carrier was spectrally centered at 5 kHz and had a bandwidth of 50 Hz. The AM detection thresholds were obtained for modulation frequencies of 10, 20, 30, 50, 70, and 100 Hz. The intrinsic envelope power of the carrier at the output of the modulation filter tuned to the signal modulation frequency appears to provide a good estimate for AM detection threshold. The results are compared with predictions on the basis of the more complex auditory processing model by Dau et al.

Auditory Threshold↗

PubMed2005

A 2-D/3-D model-based method to quantify the complexity of microvasculature imaged by in vivo multiphoton microscopy.

This paper presents model-based information-theoretic methods to quantify the complexity of tumor microvasculature, taking into account shape, textural, and structural irregularities. The proposed techniques are completely automated, and are applicable to optical slices (3-D) or projection images (2-D). Improvements upon the prior literature include: (i) measuring local (vessel segment) as well as global (entire image) vascular complexity without requiring explicit segmentation or tracing; (ii) focusing on the vessel boundaries in the complexity estimate; and (iii) added robustness to image artifacts common to tumor microvasculature images. Vessels are modeled using a family of super-Gaussian functions that are based on the superquadric modeling primitive common in computer vision. The superquadric generalizes a simple ellipsoid by including shape parameters that allow it to approximate a cylinder with elliptical cross-sections (generalized cylinder). The super-Gaussian is obtained by composing a superquadric with an exponential function giving a form that is similar to a standard Gaussian function but with the ability to produce level sets that approximate generalized cylinders. Importantly, the super-Gaussian is continuous and differentiable so it can be fit to image data using robust non-linear regression. This fitting enables quantification of the intrinsic complexity of vessel data vis-a-vis the super-Gaussian model within a minimum message length (MML) framework. The resulting measures are expressed in units of information (bits). Synthetic and real-data examples are provided to illustrate the proposed measures.

Algorithms↗

PubMed2002

Detection and measurement of retinal vessels in fundus images using amplitude modified second-order Gaussian filter.

In this paper, the fitness of estimating vessel profiles with Gaussian function is evaluated and an amplitude-modified second-order Gaussian filter is proposed for the detection and measurement of vessels. Mathematical analysis is given and supported by a simulation and experiments to demonstrate that the vessel width can be measured in linear relationship with the "spreading factor" of the matched filter when the magnitude coefficient of the filter is suitably assigned. The absolute value of vessel diameter can be determined simply by using a precalibrated line, which is typically required since images are always system dependent. The experiment shows that the inclusion of the width measurement in the detection process can improve the performance of matched filter and result in a significant increase in success rate of detection.

Computer Simulation↗

PubMed2004

Random dynamics of the Morris-Lecar neural model.

Determining the response characteristics of neurons to fluctuating noise-like inputs similar to realistic stimuli is essential for understanding neuronal coding. This study addresses this issue by providing a random dynamical system analysis of the Morris-Lecar neural model driven by a white Gaussian noise current. Depending on parameter selections, the deterministic Morris-Lecar model can be considered as a canonical prototype for widely encountered classes of neuronal membranes, referred to as class I and class II membranes. In both the transitions from excitable to oscillating regimes are associated with different bifurcation scenarios. This work examines how random perturbations affect these two bifurcation scenarios. It is first numerically shown that the Morris-Lecar model driven by white Gaussian noise current tends to have a unique stationary distribution in the phase space. Numerical evaluations also reveal quantitative and qualitative changes in this distribution in the vicinity of the bifurcations of the deterministic system. However, these changes notwithstanding, our numerical simulations show that the Lyapunov exponents of the system remain negative in these parameter regions, indicating that no dynamical stochastic bifurcations take place. Moreover, our numerical simulations confirm that, regardless of the asymptotic dynamics of the deterministic system, the random Morris-Lecar model stabilizes at a unique stationary stochastic process. In terms of random dynamical system theory, our analysis shows that additive noise destroys the above-mentioned bifurcation sequences that characterize class I and class II regimes in the Morris-Lecar model. The interpretation of this result in terms of neuronal coding is that, despite the differences in the deterministic dynamics of class I and class II membranes, their responses to noise-like stimuli present a reliable feature.

Animals↗

PubMed2005

[The effect of the photoelectric detector on the accuracy of the spectrometer].

An optimized photoelectric detector will increase the precision of a spectrometer, thus indicates an important way to develop high performance spectrometer. With an eye to this, a model describing the process that spectrogram is integrated and sampled by photoelectric detector and restored after low-pass filtering is developed. Based on the model, the influence of the characteristic parameters of the detector on the spectral line in the frequency domain is analyzed and the relation between the full width half maximum (FWHM) of the spectra line and the integral interval, sampling space and sensitivity of the detector is deduced. The conclusion indicates that both the integral interval and sampling space should be 1/6 of the FWHM for a spectral line with gaussian profile as a result of compromise between accuracy and feasibility. Moreover, the critical point deciding the right situation for scanner and array detector is given. Other guide line to optimize the photoelectric detector and increase accuracy is suggested also.

Algorithms↗

PubMed1999

Amplitude distribution of calcium sparks in confocal images: theory and studies with an automatic detection method.

Determination of the calcium spark amplitude distribution is of critical importance for understanding the nature of elementary calcium release events in striated muscle. In the present study we show, on general theoretical grounds, that calcium sparks, as observed in confocal line scan images, should have a nonmodal, monotonic decreasing amplitude distribution, regardless of whether the underlying events are stereotyped. To test this prediction we developed, implemented, and verified an automated computer algorithm for objective detection and measurement of calcium sparks in raw image data. When the sensitivity and reliability of the algorithm were set appropriately, we observed highly left-skewed or monotonic decreasing amplitude distributions in skeletal muscle cells and cardiomyocytes, confirming the theoretical predictions. The previously reported modal or Gaussian distributions of sparks detected by eye must therefore be the result of subjective detection bias against small amplitude events. In addition, we discuss possible situations when a modal distribution might be observed.

Algorithms↗

PubMed2003

Statistical properties of BOLD magnetic resonance activity in the human brain.

We investigated the random variability of BOLD (blood oxygen level dependent) activation during rest, or null-hypothesis, conditions in which the observers were neither receiving controlled sensory stimuli nor performing cognitive tasks. The data indicate that the distributions for the BOLD variation across space are skewed, with non-Gaussian tails, while the distributions for the temporal variation within individual voxels are predominantly Gaussian. The proportion of voxels that show non-Gaussian properties is highly correlated with the magnitude of head movement of the observers. In all observers, the white matter showed less variability than the gray matter. The distributions for the spatial and the temporal variations are robust across observers despite differences in the data acquisition methods (EPI vs. spiral) and magnetic field strength (1.5 vs. 3 T). In most cases, the non-Gaussian tails of the spatial distribution can be eliminated by normalizing the amplitude in each voxel to its standard deviation before cumulating across voxels. We therefore recommend such a normalization procedure before any data manipulations are performed on fMRI data.

Adult↗

PubMed2004

Modeling and decoding motor cortical activity using a switching Kalman filter.

We present a switching Kalman filter model for the real-time inference of hand kinematics from a population of motor cortical neurons. Firing rates are modeled as a Gaussian mixture where the mean of each Gaussian component is a linear function of hand kinematics. A "hidden state" models the probability of each mixture component and evolves over time in a Markov chain. The model generalizes previous encoding and decoding methods, addresses the non-Gaussian nature of firing rates, and can cope with crudely sorted neural data common in on-line prosthetic applications.

Action Potentials↗

PubMed2003

Correction of uneven illumination (vignetting) in digital microscopy images.

BACKGROUND: Many digital microscopy images suffer from poor illumination at the peripheries (vignetting), often attributable to factors related to the light path between the camera and the microscope. A commonly used method for correcting this has been to use the illumination of an empty field as a correction filter (white shading correction). AIMS: To develop an alternative shading correction method that does not require this additional image. METHODS: / RESULTS: This report outlines an alternative shading correction method that is based upon the intrinsic properties of the image, which are revealed through Gaussian smoothing. The technique can be implemented within Adobe Photoshop or other graphics editing software and works well with both haematoxylin and eosin and immunohistochemical images. CONCLUSIONS: This technique provides an effective means of optimising digital microscopy image appearances for printing, image analysis, or telepathology.

Computer Graphics↗

PubMed1986

The statistics of quantifiable homeostasis. I. Simple linear homeostasis.

The statistical properties are explored of the least-squares estimators of the parameters of a deterministic linear model for homeostasis with random, normally distributed technical errors. The parameters are: the amplitude of perturbation (A), the homing value (H), the restoration constant (B), and the lag time (L). The former two, although important in their own right, tell us nothing about the processes of biologic restitution and are thus considered "nuisance" parameters; the latter two are the "business" parameters, which tell us about the processes of biologic adjustment. The properties studied include bias and precision and their relationships to the number of data points and to the size of the technical error. Efforts have been concentrated on data points equally spaced over six lag times (which corresponds roughly to the period of observation used in loading studies, such as glucose tolerance tests). The distributions of these four estimators are studied in sets of 100 Monte Carlo simulations, each with 15, 30, and 100 data points, respectively. The estimators are virtually unbiased and all satisfactorily close to Gaussian. The residual mean-square errors (the divisor being four less than the number of data points, since four parameters are estimated) seem to be unbiased estimators of the variances of the errors. Moreover, when suitably scaled, the residual sums of squares have distributions close to the chi-square distribution for the appropriate degrees of freedom and with the corresponding means and variances. The correlations among the estimators are modest and, except where A is involved, small.

Homeostasis↗

PubMed2003

Intrinsic fluorescence spectroscopy of glutamate dehydrogenase: Integrated behavior and deconvolution analysis.

In this paper, we present a deconvolution method aimed at spectrally resolving the broad fluorescence spectra of proteins, namely, of the enzyme bovine liver glutamate dehydrogenase (GDH). The analytical procedure is based on the deconvolution of the emission spectra into three distinct Gaussian fluorescing bands G(j). The relative changes of the G(j) parameters are directly related to the conformational changes of the enzyme, and provide interesting information about the fluorescence dynamics of the individual emitting contributions. Our deconvolution method results in an excellent fitting of all the spectra obtained with GDH in a number of experimental conditions (various conformational states of the protein) and describes very well the dynamics of a variety of phenomena, such as the dependence of hexamers association on protein concentration, the dynamics of thermal denaturation, and the interaction process between the enzyme and external quenchers. The investigation was carried out by means of different optical experiments, i.e., native enzyme fluorescence, thermal-induced unfolding, and fluorescence quenching studies, utilizing both the analysis of the "average" behavior of the enzyme and the proposed deconvolution approach.

Animals↗

PubMed1998

Fibronectin in bronchoalveolar lavage fluid in lung cancer: tumor or inflammatory marker?

OBJECTIVE: To evaluate the potential value of the level of fibronectin (FN) in the bronchoalveolar lavage fluid (BALF) as a lung tumor marker. METHOD: We compare the results of determinations in the tumor-bearing and tumor-free lungs of 38 patients with lung cancer, in 19 patients with benign lung diseases and in 13 healthy control subjects. FN was determined in BALF by a competitive ELISA and was also measured in plasma with a nephelometric assay. FN levels in BALF are expressed also referred to total protein content (ng FN/mg TP). RESULTS: The distribution of FN levels in BALF was not gaussian, and the levels in cancer patients were significantly greater than in healthy controls or in the contralateral lung. There was no significative difference in the levels in cancer compared with several benign conditions. In this study we observed a positive correlation between FN levels and total protein and polymorphonuclear leukocytes in BALF in the lung cancer and benign diseases group. CONCLUSION: These results do not support the possibility that FN levels in BALF were a general marker of lung cancer, and suggest that FN may mark the existence of pathologic lung processes associated with inflammation and, perhaps tissue repair after bronchopulmonary injury.

Aged↗

PubMed1999

Factors limiting peripheral pattern discrimination.

Previous reports indicate that some foveally discriminable compound gratings are indiscriminable in peripheral vision, even when they are scaled by the ratio of peripheral to foveal grating acuity. To determine the stimulus properties that limit peripheral discrimination, we used Gaussian derivatives of various orders. These patterns are spatially localized and have intrinsic even or odd symmetry. Our results show that certain odd symmetric patterns are discriminable in the periphery, while others are not. Furthermore, certain even symmetric patterns are not peripherally discriminable. These data are consistent with three limitations on peripheral pattern discrimination: (1) Patterns that produce different maximum neural responses will be peripherally discriminable. (2) Positional uncertainty and undersampling degrade discrimination of high spatial frequency patterns in the periphery. (3) Patterns generating substantial neural activity within a constrained region are processed as textures in peripheral vision so that pattern details within that region are no longer available for discrimination. A neural model incorporating inhibition of simple cells by complex cells implements a transition between contour analysis and texture analysis in peripheral vision and explains the experimental data.

Fovea Centralis↗

PubMed2002

A new level detector for ion channel analysis.

The algorithm proposed here for automatic level detection in noisy time series of patch-clamp current is based on the detection of jump-free sections in the time series. The detector moves along the time series and uses a chi(2) test for the detection of jumps. When a jump is detected, the mean value, the variance and the length of the preceding jump-free section are stored. A Student's t-test was employed for the assignment of detected jump-free sections to discrete levels of the Markov model and for rejection of all sections with multiple assignments. The choice of the two significance levels is based on a 3-D diagram displaying the average number of detected levels from several time series vs. the significance levels of jump detection and of level assignment. The correct one is selected out of several plateaus with integer number of levels by means of the criterion of minimum scatter or other plausibility considerations. The test has been applied to simulated data obtained from a 2-state model and a 5-state aggregated Markov model, and the influences of SNR and of gating frequency are shown. Finally, the performance of the level detector is compared with a fit-by-eye and with a fit of the amplitude histogram by a sum of gaussians. At high noise, the fit of amplitude histograms failed, whereas the other two approaches were about equal.

Algorithms↗

PubMed2005

Cortical thickness analysis examined through power analysis and a population simulation.

We have previously developed a procedure for measuring the thickness of cerebral cortex over the whole brain using 3-D MRI data and a fully automated surface-extraction (ASP) algorithm. This paper examines the precision of this algorithm, its optimal performance parameters, and the sensitivity of the method to subtle, focal changes in cortical thickness. The precision of cortical thickness measurements was studied using a simulated population study and single subject reproducibility metrics. Cortical thickness was shown to be a reliable method, reaching a sensitivity (probability of a true-positive) of 0.93. Six different cortical thickness metrics were compared. The simplest and most precise method measures the distance between corresponding vertices from the white matter to the gray matter surface. Given two groups of 25 subjects, a 0.6-mm (15%) change in thickness can be recovered after blurring with a 3-D Gaussian kernel (full-width half max = 30 mm). Smoothing across the 2-D surface manifold also improves precision; in this experiment, the optimal kernel size was 30 mm.

Algorithms↗

PubMed2005

Why is second-order vision less efficient than first-order vision?

Research has shown that the sensitivity to second-order modulations of carrier contrast is lower than that to first-order luminance modulations stimuli. We sought to compare the efficiency of processing first- and second-order information. Employing a phase-discrimination paradigm we found that when humans were given sufficient a priori information of signal parameters they detected both luminance and contrast modulations of 0.6 and 2c/deg by a phase-sensitive algorithm. The overall detection efficiency for second-order patterns, however, was lower that that for first-order stimuli. To study the factors which limit the efficiency of first- and second-order vision, we measured detection performance for luminance and contrast modulations of 0.6 and 2c/deg embedded in Gaussian noise. The results showed that the detection of second-order patterns had lower sampling efficiency and higher additive internal noise as compared to the detection of first-order stimuli. Classification images for detecting contrast modulations of 2c/deg resembled the side-band component of the contrast modulations which suggests that human observers may detect contrast modulations of a sinusoidal carrier using first-order luminance channels. The lower sensitivity of the mechanism detecting second-order patterns might be due to higher levels of additive internal noise and lower sampling efficiency than those of the mechanism analysing first-order patterns.

Contrast Sensitivity↗