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PubMed1996

Assimilation-type and contrast-type bias of motion induced by the surround in a random-dot display: evidence for center-surround antagonism.

As a mechanism to detect differential motion, we have proposed a model of "a motion contrast detector" that has a center-surround antagonistic receptive field with respect to the direction of motion. Supporting evidence has been obtained in the studies of induced motion, motion capture, and motion aftereffect. In order to obtain further evidence in a more strictly controlled situation, we examined the perceptual bias of motion in a center stimulus induced by another, surrounding motion. By using a stochastic random-dot display configured in a center-surround concentric fashion, we measured the % signal in the center stimulus that made the stimulus perceptually stationary in the presence of a moving surround. Measurements were done for various stimulus sizes and eccentricities. The amount of bias changed as a function of stimulus size and eccentricity. At several eccentricities, smaller stimulus sizes tended to yield assimilation-type biases, whereas larger sizes tended to yield contrast-type biases. However, a spatial scaling procedure revealed that the amount of bias was a simpler function of "scaled" stimulus size that was obtained by dividing the physical size by a scaling factor at each eccentricity. In the scaled profile, assimilation-type bias changed to contrast-type bias with increasing size, reached the peak of contrast-type bias at a certain size, and decreased slightly with further increasing size. Furthermore, a model of a difference of Gaussians, DOG, function well approximated the behavior of the profile. From these results, we concluded that the process specific to perceiving relative motion is mediated by a motion contrast detector, which is possibly located in area MT.

Humans↗

PubMed2000

Liquid adsorption chromatography of polyethers: experiments and simulation.

The adsorption behavior of poly(ethylene glycol) (PEG) in reversed-phase chromatography is studied both experimentally and theoretically and a computer simulation of chromatograms is performed on the basis of these studies. The experimental conditions were: different reversed-phase adsorbents and a solvent methanol-water system as the mobile phase. At varying mobile phase compositions highly resolved chromatograms of PEG samples were obtained, in which all peaks could be identified, and the dependencies of the distribution coefficient on the degree of polymerization for PEG molecules were evaluated by processing these chromatograms. The data were interpreted by using a theory of homopolymers based on a continuum Gaussian chain model of flexible macromolecules and a slit-like model of pores of stationary phase. The theory proved to describe well the experimental data in the whole range of studied molecular masses, and the thermodynamic parameters characterizing interactions of ethylene oxide repeating units in PEG molecules with the adsorbent pore walls have been determined from the comparison of the theory with the experimental data. The dispersion of chromatographic peaks corresponding to individual oligomer molecules is also estimated. In the system studied the peak width occurred to be proportional to the distribution coefficient of corresponding macromolecule. The theory is used to develop a computer-assisted procedure for simulation of chromatograms for samples of linear homopolymers. Using the obtained data on the thermodynamic parameters and the estimates of peak dispersion, chromatograms are simulated for PEG samples at two different chromatographic conditions. These simulated chromatograms were in good quantitative agreement with the real chromatograms.

Adsorption↗

PubMed1996

Application of dimension estimation and surrogate data to the time evolution of EEG topographic variables.

Dimensional complexity (estimated correlation dimension) was measured for two topographic EEG time series: (a) the time evolution of global field power (GFP) and (b) the time evolution of sequential dissimilarity (SQD) for resting, eyes-closed and eyes-open data. Eyes-closed GFP and eyes-closed/open SQD all had an element of nonlinearity in their dynamics as evidenced by increased dimensional complexity associated with the phase-angle randomization, Gaussian surrogate-data procedure. However, none of the three gave any evidence of being deterministic chaotic processes. Eyes-open GFP dimensional complexity could not be distinguished from a linear-stochastic process.

Adult↗

PubMedDate not supplied

Mouse barrel cortex viewed as Dirichlet domains.

Barrels are patterned groups of neurons in rodent somatosensory cortex that correspond one to one with the animal's facial whiskers. Dirichlet domains are a class of convex polygon found frequently in nature, often arising by nucleation from center points. Analytic and graphical methods were devised to verify the hypothesis that Dirichlet domains accurately describe the adult barrel fields of normal mice. We found that normal barrel fields and abnormal barrel fields caused by supernumerary whiskers or lesions to the whisker pad are closely approximated by this mathematical formalism. This implies that each developing cortical barrel organizes about a center point. Experiments in neonatal animals (Senft and Woolsey, 1991a) demonstrate foci in the thalamocortical afferent (TCA) distributions. These results support an hypothesis in which TCAs are the nucleating agents causing barrels to organize as Dirichlet domains. This is made possible because TCA terminals from each barreloid (a whisker-related group of cells in the ventrobasal complex of the thalamus) initially colonize somatosensory cortex with an approximately "Gaussian" distribution. These peaked groups of related TCAs behave as Dirichlet domain centers. They generate barrel structures competitively, in animals with normal or with perturbed whisker patterns, via statistical epigenetic interactions within and between distinct TCA Gaussians associated with separate whiskers. This leads to selective axon outgrowth and pruning of single TCA branches, regulated by the TCA population, and creates beneath each Gaussian the dense knot of related TCA arbors typical of the barrel cortex. Similar parcellation of neuronal processes into contending subgroups having spatially coherent actions could lead to nucleation of other geometric patterns as Dirichlet domains elsewhere in the brain.

Animals↗

PubMed2005

Protein secondary structures (alpha-helix and beta-sheet) at a cellular level and protein fractions in relation to rumen degradation behaviours of protein: a new approach.

Studying the secondary structure of proteins leads to an understanding of the components that make up a whole protein, and such an understanding of the structure of the whole protein is often vital to understanding its digestive behaviour and nutritive value in animals. The main protein secondary structures are the alpha-helix and beta-sheet. The percentage of these two structures in protein secondary structures influences protein nutritive value, quality and digestive behaviour. A high percentage of beta-sheet structure may partly cause a low access to gastrointestinal digestive enzymes, which results in a low protein value. The objectives of the present study were to use advanced synchrotron-based Fourier transform IR (S-FTIR) microspectroscopy as a new approach to reveal the molecular chemistry of the protein secondary structures of feed tissues affected by heat-processing within intact tissue at a cellular level, and to quantify protein secondary structures using multicomponent peak modelling Gaussian and Lorentzian methods, in relation to protein digestive behaviours and nutritive value in the rumen, which was determined using the Cornell Net Carbohydrate Protein System. The synchrotron-based molecular chemistry research experiment was performed at the National Synchrotron Light Source at Brookhaven National Laboratory, US Department of Energy. The results showed that, with S-FTIR microspectroscopy, the molecular chemistry, ultrastructural chemical make-up and nutritive characteristics could be revealed at a high ultraspatial resolution ( approximately 10 microm). S-FTIR microspectroscopy revealed that the secondary structure of protein differed between raw and roasted golden flaxseeds in terms of the percentages and ratio of alpha-helixes and beta-sheets in the mid-IR range at the cellular level. By using multicomponent peak modelling, the results show that the roasting reduced (P<0.05) the percentage of alpha-helixes (from 47.1 % to 36.1 %: S-FTIR absorption intensity), increased the percentage of beta-sheets (from 37.2 % to 49.8 %: S-FTIR absorption intensity) and reduced the alpha-helix to beta-sheet ratio (from 0.3 to 0.7) in the golden flaxseeds, which indicated a negative effect of the roasting on protein values, utilisation and bioavailability. These results were proved by the Cornell Net Carbohydrate Protein System in situ animal trial, which also revealed that roasting increased the amount of protein bound to lignin, and well as of the Maillard reaction protein (both of which are poorly used by ruminants), and increased the level of indigestible and undegradable protein in ruminants. The present results demonstrate the potential of highly spatially resolved synchrotron-based infrared microspectroscopy to locate 'pure' protein in feed tissues, and reveal protein secondary structures and digestive behaviour, making a significant step forward in and an important contribution to protein nutritional research. Further study is needed to determine the sensitivities of protein secondary structures to various heat-processing conditions, and to quantify the relationship between protein secondary structures and the nutrient availability and digestive behaviour of various protein sources. Information from the present study arising from the synchrotron-based IR probing of the protein secondary structures of protein sources at the cellular level will be valuable as a guide to maintaining protein quality and predicting digestive behaviours.

Animal Feed↗

PubMedDate not supplied

Utilization of mathematical processing of retinal images with use of adaptive contrast control (ACC) method to detect quantity of vascular endings.

PURPOSE: The authors investigated whether the method of mathematical processing of retinal images with the use of a computer can be used to evaluate ocular background figures of patients with physiologic retinal findings. This method is based on identification of vascular endings in an examined retinal area. When the authors mention vascular endings, they do not refer to factual endings, but recognizable vascular endings; there are no endings in a vascular system. METHODS: Adaptive contrast control (ACC) method was used to determine a number of vascular endings. The method is based on mathematical processing of a digitized retina picture with the use of a computer. On a digitized retinal picture, the vascular system is identified with the use of the conditional erosion methodology, and the number of vascular endings is then determined. The ACC method was used to process a file of retinal pictures of 38 patients (76 eyes) with physiologic retinal findings. RESULTS: Based on the results of statistical analysis, the authors detected that the number of vascular endings showed a normal curve (Gaussian distribution, p=0.05). A tight correlation between quantities of vascular endings in the right and the left eyes was also detected, which means that the quantity of vascular endings in the right and the left eyes is in a very close correlation (p=0.05). CONCLUSIONS: The authors highlight that the curve of the number of vascular endings of patients with physiologic retinal findings shows a Gaussian distribution.

Adolescent↗

PubMedDate not supplied

Stochastic ICA contrast maximisation using OJA's nonlinear PCA algorithm.

Independent Component Analysis (ICA) is an important extension of linear Principal Component Analysis (PCA). PCA performs a data transformation to provide independence to second order, that is, decorrelation. ICA transforms data to provide approximate independence up to and beyond second order yielding transformed data with fully factorable probability densities. The linear ICA transformation has been applied to the classical statistical signal-processing problem of Blind Separation of Sources (BSS), that is, separating unknown original source signals from a mixture whose mode of mixing is undetermined. In this paper it is shown that Oja's Nonlinear PCA algorithm performs a general stochastic online adaptive ICA. This analysis is corroborated with three simulations. The first separates unknown mixtures of original natural images, which have sub-Gaussian densities, the second separates linear mixtures of natural speech whose densities are super-Gaussian. Finally unknown mixtures of original images, which have both sub- and super-Gaussian densities are separated.

Algorithms↗

PubMed2003

Photoinduced electron transfer in alpha-helical polypeptides: dependence on conformation and electron donor-acceptor distance.

Long distance electron transfer in proteins is a multiple-pathway process whose kinetics is modulated by the dynamics of flexible peptide chains. Such complexity can be observed even in relatively simple systems, eg. donor bridge acceptor, where the bridge is a polypeptide alpha-helix. We have investigated a series of 24-residue helical polypeptides that exist as monomers in water alcohol media. The principal chromophore and electron acceptor, a pyrene moiety, is connected to the N-terminus via a flexible linker. The electron donor, a tryptophan residue, was placed various distances away from the pyrene-labeled terminus. Time-resolved emission spectroscopy, associated with the fluorescent pendant, pyrene, was employed to study the photoinduced electron-transfer kinetics for the polypeptide analogs. Mechanisms involving only through-bond pathways could not account for the pattern of measured fast charge-separation rates. When the electron donor was placed far enough from the acceptor (i.e. at least six residues apart), a decrease in the electron-transfer rates with the donor acceptor distance was observed. The emission decays for polypeptides with the electron donor exhibited complex behavior and could not be fit using a single-exponential function. For the treatment of the time-resolved data, a multi-exponential model was developed that is based on the assumption of a Gaussian distribution of the classical electronic coupling beta values among the conformers responsible for the observed electron-transfer processes. This approach proved to be informative because, in addition to the mean values of the electron-transfer rate constants, the widths of the distributions of these rates illustrate the size of the conformational space explored by the flexible chains that provide pathways for electron transfer.

Amino Acid Sequence↗

PubMed1991

Estimation of bladder wall location in ultrasound images.

A method of automatically estimating the location of the bladder wall in ultrasound images is proposed. Obtaining this estimate is intended to be the first stage in the development of an automatic bladder volume calculation system. The first step in the bladder wall estimation scheme involves globally processing the images using standard image processing techniques to highlight the bladder wall. Separate processing sequences are required to highlight the anterior bladder wall and the posterior bladder wall. The sequence to highlight the anterior bladder wall involves Gaussian smoothing and second differencing followed by zero-crossing detection. Median filtering followed by thresholding and gradient detection is used to highlight as much of the rest of the bladder wall as was visible in the original images. Then a 'bladder wall follower'--a line follower with rules based on the characteristics of ultrasound imaging and the anatomy involved--is applied to the processed images to estimate the bladder wall location by following the portions of the bladder wall which are highlighted and filling in the missing segments. The results achieved using this scheme are presented.

Female↗

PubMed2001

Dynamics of inherent structure in supercooled liquids near kinetic glass transition.

We present a description of the dynamics of a supercooled binary Lennard-Jones liquid in term of the potential landscape of the system. The slowing down of the dynamics in supercooled liquids near the kinetic glass transition is related to the existence of basins in the potential landscape. The inherent structures that are the local potential minima in the configuration space obtained by a quench process are employed to represent the configurations of the basins. We present time correlation functions of the inherent structure, both the self and the coherent part, as a function of wave vector. We also calculated the mean-square displacement, and the non-Gaussian parameter of the van Hove self-correlation function. Compared with the dynamics of original configurations, the short-time relaxation has almost been eliminated by the quench process. However, the long-time alpha relaxations remain essentially the same. We conclude that the long-time alpha relaxation is the result of cross-basin transition in the potential landscape in the configuration space.

Journal Article↗

PubMed2004

Wavelets and functional magnetic resonance imaging of the human brain.

The discrete wavelet transform (DWT) is widely used for multiresolution analysis and decorrelation or "whitening" of nonstationary time series and spatial processes. Wavelets are naturally appropriate for analysis of biological data, such as functional magnetic resonance images of the human brain, which often demonstrate scale invariant or fractal properties. We provide a brief formal introduction to key properties of the DWT and review the growing literature on its application to fMRI. We focus on three applications in particular: (i) wavelet coefficient resampling or "wavestrapping" of 1-D time series, 2- to 3-D spatial maps and 4-D spatiotemporal processes; (ii) wavelet-based estimators for signal and noise parameters of time series regression models assuming the errors are fractional Gaussian noise (fGn); and (iii) wavelet shrinkage in frequentist and Bayesian frameworks to support multiresolution hypothesis testing on spatially extended statistic maps. We conclude that the wavelet domain is a rich source of new concepts and techniques to enhance the power of statistical analysis of human fMRI data.

Algorithms↗

PubMed2006

Superresolution and noise filtering using moving least squares.

An irregularly spaced sampling raster formed from a sequence of low-resolution frames is the input to an image sequence superresolution algorithm whose output is the set of image intensity values at the desired high-resolution image grid. The method of moving least squares (MLS) in polynomial space has proved to be useful in filtering the noise and approximating scattered data by minimizing a weighted mean-square error norm, but introducing blur in the process. Starting with the continuous version of the MLS, an explicit expression for the filter bandwidth is obtained as a function of the polynomial order of approximation and the standard deviation (scale) of the Gaussian weight function. A discrete implementation of the MLS is performed on images and the effect of choice of the two dependent parameters, scale and order, on noise filtering and reduction of blur introduced during the MLS process is studied.

Algorithms↗

PubMed2006

Uncertainty in diffusion tensor based fibre tracking.

BACKGROUND: Diffusion tensor imaging and related fibre tracking techniques have the potential to identify major white matter tracts afflicted by an individual pathology or tracts at risk for a given surgical approach. However, the reliability of these techniques is known to be limited by image distortions, image noise, low spatial resolution, and the problem of identifying crossing fibres. This paper intends to bridge the gap between the requirements of neurosurgical applications and basic research on fibre tracking uncertainty. METHOD: We acquired echo planar diffusion tensor data from both 1.5 T and 3.0 T scanners. For fibre tracking, an extended deflection-based algorithm is employed with enhanced robustness to impaired fibre integrity such as caused by diffuse or infiltrating pathological processes. Moreover, we present a method to assess and visualize the uncertainty of fibre reconstructions based on variational complex Gaussian noise, which provides an alternative to the bootstrap method. We compare fibre tracking results with and without variational noise as well as with artificially decreased image resolution and signal-to-noise. FINDINGS: Using our fibre tracking technique, we found a high robustness to decreased image resolution and signal-to-noise. Still, the effects of image quality on the tracking result will depend on the employed fibre tracking algorithm and must be handled with care, especially when being used for neurosurgical planning or resection guidance. An advantage of the variational noise approach over the bootstrap technique is that it is applicable to any given set of diffusion tensor images. CONCLUSIONS: We conclude that the presented approach allows for investigating the uncertainty of diffusion tensor imaging based fibre tracking and might offer a perspective to overcome the problem of size underestimation observed by existing techniques.

Adult↗

PubMed1993

Modelling the growth of solid tumours and incorporating a method for their classification using nonlinear elasticity theory.

Medically, tumours are classified into two important classes--benign and malignant. Generally speaking, the two classes display different behaviour with regard to their rate and manner of growth and subsequent possible spread. In this paper, we formulate a new approach to tumour growth using results and techniques from nonlinear elasticity theory. A mathematical model is given for the growth of a solid tumour using membrane and thick-shell theory. A central feature of the model is the characterisation of the material composition of the model through the use of a strain-energy function, thus permitting a mathematical description of the degree of differentiation of the tumour explicitly in the model. Conditions are given in terms of the strain-energy function for the processes of invasion and metastasis occurring in a tumour, being interpreted as the bifurcation modes of the spherical shell which the tumour is essentially modelled as. Our results are compared with actual experimental results and with the general behaviour shown by benign and malignant tumours. Finally, we use these results in conjunction with aspects of surface morphogenesis of tumours (in particular, the Gaussian and mean curvatures of the surface of a solid tumour) in an attempt to produce a mathematical formulation and description of the important medical processes of staging and grading cancers. We hope that this approach may form the basis of a practical application.

Cell Division↗

PubMed1992

A mathematical model for the growth and classification of a solid tumor: a new approach via nonlinear elasticity theory using strain-energy functions.

Medically, tumors are classified into two important classes--benign and malignant. Generally speaking, the two classes display different behaviour with regard to their rate and manner of growth and subsequent possible spread. In this paper, we formulate a new approach to tumor growth using results and techniques from nonlinear elasticity theory. A mathematical model is given for the growth of a solid tumor using membrane and thick-shell theory. A central feature of the model is the characterization of the material composition of the tumor through the use of a strain energy function, thus permitting a mathematical description of the degree of differentiation of the tumor explicitly in the model. Conditions are given in terms of the strain energy function for the processes of invasion and metastasis occurring in a tumor, being interpreted as the bifurcation modes of the spherical shell, which the tumor is essentially modeled as. Our results are compared with actual medical experimental results and with the general behavior shown by benign and malignant tumors. Finally, we use these results in conjunction with aspects of surface morphogenesis of tumors (in particular, the Gaussian and mean curvatures of the surface of a solid tumor) in an attempt to produce a mathematical formulation and description of the important medical processes of staging and grading cancers. We hope that this approach may form the basis of a practical application.

Animals↗

PubMed1995

Contrast, noise, and blur affect performance and appreciation of digital radiographs.

We have studied the effect of the simultaneous variation of contrast, noise, and blur on the perceived quality of digital radiograph images. Three images were processed with different levels of roentgen photon noise, different luminance (gray-level) ranges, and different amounts of Gaussian blur. Observers had to rate the quality of the images on a numerical scale. To study how the quality judgment is related to the visibility of small details (diagnostic quality), an artificial detail was added to each image. The detail could be in two possible locations. The visibility of this detail was measured in a two-alternative forced-choice experiment. One of the conclusions is that the quality judgment was based mainly on blur, whereas the visibility of details was affected mostly by noise.

Analysis of Variance↗

PubMed1985

A practical, high-resolution, microcomputer-based method for the analysis of relaxation data exhibiting multicomponent exponential decays.

We have developed and tested a practical, rapid, high-resolution, microcomputer-based method for the analysis of multicomponent exponential decays. The analysis utilizes the Fourier deconvolution technique and includes methods to reduce noise both in the input data and in the results. The developed method is particularly well suited for analysing decays consisting of a wide range of decay times. The method resolves two exponential decays differing by a factor of two when the input data are mathematically generated and without noise, and resolves two decays differing by a factor of three when 2% Gaussian noise is present in the same data. The method lends itself to routine analysis of any relaxation process consisting of exponential decays, including biomedical applications such as enzyme kinetics, circulatory transport functions, pharmacokinetics, plasma exchange therapy, and analysis of compartmental models for any process.

Birefringence↗

PubMed2006

Computer-aided detection of colonic polyps using low-dose CT acquisitions.

RATIONALE AND OBJECTIVES: This report proposes an alternative method for the automatic detection of colonic polyps that is robust enough to be directly applicable on low-dose computed tomographic data. MATERIALS AND METHODS: The polyp modeling process takes into account both the gray-level appearance of polyps (intensity profiles) and their geometry (extended Gaussian images). Spherical harmonic decompositions are used for comparison purposes, allowing fast estimation of the similarity between a candidate and a set of previously computed models. Starting from the original raw data (acquired at 55 mA), five patient data sets (prone and supine scans) are reconstructed at different dose levels (to 5 mA) by using different kernel filters, slice overlaps, and increments. Additionally, the efficacy of applying an edge-preserving smoothing filter before detection is assessed. RESULTS: Although image quality decreases when decreasing acquisition milliamperes, all polyps greater than 6 mm are detected successfully, even at 15 mA. Although not important at high doses, smoothing improves detection results for ultra-low-dose (tube current<15 mA) data. CONCLUSION: The advantage of low-dose scans is a significant decrease in effective dose from 4.93 to 1.61 mSv while retaining high detection values, particularly important when thinking of population screening.

Algorithms↗