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PubMed2002

Generalized correlation NMR spectroscopy.

The use of generalized correlation analysis (Noda, I. Appl. Spectrosc. 1993, 47, 1329-1336) for processing two-dimensional arrays of NMR data is described. This analysis produces complex two-dimensional spectra whose cross-peak intensities are related to correlations in the responses of pairs of signals to systematically incremented perturbations. The technique extends and generalizes the applicability of two-dimensional NMR by allowing model-independent analysis of nonperiodic signals as well as model-dependent analysis of such signals. When applied to diffusion-ordered NMR data, the processing scheme produces two-dimensional output spectra having two frequency axes. Relative diffusion coefficients are encoded in the signs and intensities of the cross-peaks. Key properties of the resulting spectra are model-independent, so the approach provides an alternative to traditional DOSY processing and offers advantages for data sets that do not provide pure exponential or Gaussian response curves. When data do conform well to a known response function, the technique provides a method for extracting descriptors in a two-dimensional plot having one axis corresponding to the descriptor and the other axis corresponding to the usual chemical shift scale. Finally, the technique may be used to identify differences in the response functions of closely related samples, generating a one-dimensional spectrum with signals at frequencies whose response functions differ between two samples.

Journal Article↗

PubMed2005

Photoinduced electroreduction of chlorophyllide on alkanethiol-coated mercury.

Monolayers of n-alkanethiols of chain length from C12 to C18 were self-assembled on a hanging mercury drop electrode, and a film of chlorophyllide (Chlide) was adsorbed on top of them. The reduction photocurrents following illumination of the Chlide film were measured over the potential range in which the Chlide is electroinactive in the dark, and their action spectra were determined. Plotting the derivative of the photocurrents with respect to the applied potential against potential yields bell-shaped curves that can be fitted to a Gaussian. The potential of the Gaussian maximum was used to determine the reorganization energy lambda for the Chlide electroreduction process. An increase in the thiol chain length causes lambda to decrease regularly and the photocurrent to decay exponentially with the monolayer thickness, with a decay constant beta of about 0.17 A(-1).

Biomimetic Materials↗

PubMed2002

Simultaneous micromanipulation in multiple planes using a self-reconstructing light beam.

Optical tweezers are commonly used for manipulating microscopic particles, with applications in cell manipulation, colloid research, manipulation of micromachines and studies of the properties of light beams. Such tweezers work by the transfer of momentum from a tightly focused laser to the particle, which refracts and scatters the light and distorts the profile of the beam. The forces produced by this process cause the particle to be trapped near the beam focus. Conventional tweezers use gaussian light beams, which cannot trap particles in multiple locations more than a few micrometres apart in the axial direction, because of beam distortion by the particle and subsequent strong divergence from the focal plane. Bessel beams, however, do not diverge and, furthermore, if part of the beam is obstructed or distorted the beam reconstructs itself after a characteristic propagation distance. Here we show how this reconstructive property may be utilized within optical tweezers to trap particles in multiple, spatially separated sample cells with a single beam. Owing to the diffractionless nature of the Bessel beam, secondary trapped particles can reside in a second sample cell far removed ( approximately 3 mm) from the first cell. Such tweezers could be used for the simultaneous study of identically prepared ensembles of colloids and biological matter, and potentially offer enhanced control of 'lab-on-a-chip' and optically driven microstructures.

Journal Article↗

PubMed2004

Critical evaluation of approximate quantum decoherence rates for an electronic transition in methanol solution.

We present a quantum molecular dynamics calculation of a semiclassical decoherence function to evaluate the accuracy of alternative short-time approximations for coherence loss in the dynamics of condensed phase electronically nonadiabatic processes. The semiclassical function from mixed quantum-classical molecular dynamics simulations and frozen Gaussian wave packets is computed for the electronic transition of an excited state excess electron to the ground state in liquid methanol. The decoherence function decays on a 10 fs time scale that is qualitatively similar to the aqueous case. We demonstrate that it is the motion of the hydrogen atom, and, in particular, the hydrogen rotation around the oxygen-methyl bond which is predominantly responsible for destroying the quantum correlations between alternative states. Multiple time scales due to the slower diffusive nuclear modes, which dominate the solvation response of methanol, do not contribute to the coherence loss. The choice of the coordinate representation is investigated in detail and concluded to be irrelevant to the decay. Changes in both nuclear momenta and positions on the two alternative potential surfaces are found to contribute to decoherence, the former dominating at short times (t < 5 fs), the latter controlling the decay at longer times. Various short-time approximations to the full dynamics for the decoherence function are tested for the first time. The present treatment rigorously develops the short-time description and establishes its range of validity. Whereas the lowest-order short-time approximation proves to be a very good approximation up to about 5 fs, we also find that it bounds the decay of the decoherence function. After 5 fs, the coherence decay in fact becomes faster than the single Gaussian predicted in the lowest-order short-time limit. This decay is well reflected by an enhanced low-order approximation, which is also easily computed from equilibrium classical forces.

Journal Article↗

PubMed2005

Reconstruction of air contaminant concentration distribution in a two-dimensional plane by computed tomography and remote sensing FTIR spectroscopy.

This research combined open path FTIR (OP-FTIR) technique and computed tomography (CT) to reconstruct air contaminant concentration distribution in a two-dimensional plane. Remote sensing FTIR instrument was used to scan radial beam geometry and obtain path integrated concentration (PIC) data of acetone gas in the measuring plane. Smooth basis function minimization (SBFM) algorithm was adopted to reconstruct gaseous concentration distribution. For the purpose of finding out the preferable number of Gaussians used in SBFM algorithm, single-Gaussian, double-Gaussian, and three-Gaussian models were used respectively. Experimental results showed that the reconstruction result of acetone concentration distribution by SBFM algorithm with double-Gaussian model agreed with real distribution more qualitatively and quantitatively than single-Gaussian and three-Gaussian. Also, it has been proved that simulated annealing algorithm used in the optimization process of SBFM reconstruction was feasible and effective. Although computed tomography and remote sensing FTIR technique (CT-RS-FTIR) is still at the laboratory study stage, with further improvement of SBFM algorithm and beam geometry, it promises to be used in air pollution monitoring widely.

Acetone↗

PubMed2002

Kawasaki-type dynamics: diffusion in the kinetic Gaussian model.

In this Brief Report, we retain the basic idea and at the same time generalize Kawasaki's dynamics, the spin-pair exchange mechanism, to a spin-pair redistribution mechanism, and present a normalized redistribution probability. This serves to unite various order-parameter-conserved processes into a universal framework in microscopics and provides the basis for further treatment. As an example of the applications, we treated the kinetic Gaussian model and obtained the exact diffusion equation. We observed critical slowing down near the critical point and found that the critical dynamic exponent z = 1/v = 2 is independent of space dimensionality and the assumed mechanism, whether Glauber type or Kawasaki type.

Journal Article↗

PubMed2004

A computational model of auditory selective attention.

The human auditory system is able to separate acoustic mixtures in order to create a perceptual description of each sound source. It has been proposed that this is achieved by an auditory scene analysis (ASA) in which a mixture of sounds is parsed to give a number of perceptual streams, each of which describes a single sound source. It is widely assumed that ASA is a precursor of attentional mechanisms, which select a stream for attentional focus. However, recent studies suggest that attention plays a key role in the formation of auditory streams. Motivated by these findings, this paper presents a conceptual framework for auditory selective attention in which the formation of groups and streams is heavily influenced by conscious and subconscious attention. This framework is implemented as a computational model comprising a network of neural oscillators, which perform stream segregation on the basis of oscillatory correlation. Within the network, attentional interest is modeled as a Gaussian distribution in frequency. This determines the connection weights between oscillators and the attentional process, which is modeled as an attentional leaky integrator (ALI). Acoustic features are held to be the subject of attention if their oscillatory activity coincides temporally with a peak in the ALI activity. The output of the model is an "attentional stream," which encodes the frequency bands in the attentional focus at each epoch. The model successfully simulates a range of psychophysical phenomena.

Action Potentials↗

PubMed2002

Population coding and decoding in a neural field: a computational study.

This study uses a neural field model to investigate computational aspects of population coding and decoding when the stimulus is a single variable. A general prototype model for the encoding process is proposed, in which neural responses are correlated, with strength specified by a gaussian function of their difference in preferred stimuli. Based on the model, we study the effect of correlation on the Fisher information, compare the performances of three decoding methods that differ in the amount of encoding information being used, and investigate the implementation of the three methods by using a recurrent network. This study not only rediscovers main results in existing literatures in a unified way, but also reveals important new features, especially when the neural correlation is strong. As the neural correlation of firing becomes larger, the Fisher information decreases drastically. We confirm that as the width of correlation increases, the Fisher information saturates and no longer increases in proportion to the number of neurons. However, we prove that as the width increases further--wider than (sqrt)2 times the effective width of the turning function--the Fisher information increases again, and it increases without limit in proportion to the number of neurons. Furthermore, we clarify the asymptotic efficiency of the maximum likelihood inference (MLI) type of decoding methods for correlated neural signals. It shows that when the correlation covers a nonlocal range of population (excepting the uniform correlation and when the noise is extremely small), the MLI type of method, whose decoding error satisfies the Cauchy-type distribution, is not asymptotically efficient. This implies that the variance is no longer adequate to measure decoding accuracy.

Neural Networks, Computer↗

PubMed2006

The spike-triggered average of the integrate-and-fire cell driven by gaussian white noise.

We compute the exact spike-triggered average (STA) of the voltage for the nonleaky integrate-and-fire (IF) cell in continuous time, driven by gaussian white noise. The computation is based on techniques from the theory of renewal processes and continuous-time hidden Markov processes (e.g., the backward and forward Fokker-Planck partial differential equations associated with first-passage time densities). From the STA voltage, it is straightforward to derive the STA input current. The theory also gives an explicit asymptotic approximation for the STA of the leaky IF cell, valid in the low-noise regime sigma --> 0. We consider both the STA and the conditional average voltage given an observed spike "doublet" event, that is, two spikes separated by some fixed period of silence. In each case, we find that the STA as a function of time-preceding-spike, tau, has a square root singularity as tau approaches zero from below and scales linearly with the scale of injected noise current. We close by briefly examining the discrete-time case, where similar phenomena are observed.

Action Potentials↗

PubMed2000

Interferometric data analysis based on Markov nonlinear filtering methodology.

For data processing in conventional phase shifting interferometry, Fourier transform, and least-squares-fitting techniques, a whole interferometric data series is required. We propose a new interferometric data processing methodology based on a recurrent nonlinear procedure. The signal value is predicted from the previous step to the next step, and the prediction error is used for nonlinear correction of an a priori estimate of the parameters phase, visibility, or frequency of interference fringes. Such a recurrent procedure is correct on the condition that the noise component be a Markov stochastic process realization. The accuracy and stability of the recurrent Markov nonlinear filtering algorithm were verified by computer simulations. It was discovered that the main advantages of the proposed methodology are dynamic data processing, phase error minimization, and high noise immunity against the influence of non-Gaussian noise correlated with the signal and the automatic solution of the phase unwrapping problem.

Algorithms↗

PubMed1980

[Effect of fluctuating electromagnetic fields on the processes of growth and blastomogenesis].

Rats were exposed to low-frequency electromagnetic field, adequate to the natural background, with Gaussian energy distribution, spectrum width 15 kHz, and field intensity 5 V/cm. Electric fluctuations were shown to have an inhibitory action on the normal growth of the animals and on blastoma development. This action reaches maximum with the greatest build-up gradient. As the frequency band of the field of action increase, the inhibitory effect declines.

Animals↗

PubMed1999

Impairment in preattentive visual processing in patients with Parkinson's disease.

We explored the possibility of whether preattentive visual processing is impaired in Parkinson's disease. With this aim, visual discrimination thresholds for orientation texture stimuli were determined in two separate measurement sessions in 16 patients with idiopathic Parkinson's disease. The results were compared with those of 16 control subjects age-matched and 16 young healthy volunteers. Discrimination thresholds were measured in a four-alternative spatial forced-choice paradigm, in which subjects judged the location of a target embedded in a background of distractors. Four different stimulus configurations were employed: (i) a group of vertical targets among horizontal distractors ('vertical line targets'); (ii) targets with varying levels of orientation difference on a background of spatially filtered vertically oriented noise ('Gaussian filtered noise'); (iii) one 'L' among 43 '+' signs ('texton'), all of which assess preattentive visual processing; and (iv) control condition, of one 'L' among 43 'T' distractors ('non-texton' search target), which reflects attentive visual processing. In two of the preattentive tasks (filtered noise and texton), patients with Parkinson's disease required significantly greater orientation differences and longer stimulus durations, respectively. In contrast, their performance in the vertical line target and non-texton search target was comparable to that of the matched control subjects. These differences were more pronounced in the first compared with the second session. Duration of illness and age within the patient group correlated significantly with test performance. In all conditions tested, the young control subjects performed significantly better than the more elderly control group, further indicating an effect of age on this form of visual processing. The results suggest that, in addition to the well documented impairment in retinal processing, idiopathic Parkinson's disease is associated with a deficit in preattentive cortical visual processing.

Adult↗

PubMed1998

Selection of task-dependent diffusion filters for the post-processing of SPECT images.

Iterative reconstruction from single photon emission computed tomography (SPECT) data requires regularization to avoid noise amplification and edge artefacts in the reconstructed image. This is often accomplished by stopping the iteration process at a relatively low number of iterations or by post-filtering the reconstructed image. The aim of this paper is to develop a method to automatically select an optimal combination of stopping iteration number and filters for a particular imaging situation. To this end different error measures between the distribution of a phantom and a corresponding filtered SPECT image are minimized for different iteration numbers. As a study example, simulated data representing a brain study are used. For post-reconstruction filtering, the performance of 3D linear diffusion (Gaussian filtering) and edge preserving 3D nonlinear diffusion (Catté scheme) is investigated. For reconstruction methods which model the image formation process accurately, error measures between the phantom and the filtered reconstruction are significantly reduced by performing a high number of iterations followed by optimal filtering compared with stopping the iterative process early. Furthermore, this error reduction can be obtained over a wide range of iteration numbers. Only a negligibly small additional reduction of the errors is obtained by including spatial variance in the filter kernel. Compared with Gaussian filtering, Catté diffusion can further reduce the error in some cases. For the examples considered, using accurate image formation models during iterative reconstruction is far more important than the choice of the filter.

Biophysical Phenomena↗

PubMed2000

Molden: a pre- and post-processing program for molecular and electronic structures.

Molden is a software package for pre- and postprocessing of computational chemistry program data. Interfacing to the ab initio programs Games-US/UK and Gaussian and to the semi-empirical package MOPAC is provided. The emphasis is on computation and visualization of electronic and molecular properties but, e.g., reaction pathways can be simulated as well. Some molecular properties of interest are processed directly from the output of the computational chemistry programs, others are calculated in MOLDEN before display. The package features different options to display MOLecular electronic DENsity, each focusing on a different structural aspect: molecular orbitals, electron density, molecular minus atomic density and the Laplacian of the electron density. To display difference density, either the spherically averaged atomic density or the oriented ground state atomic density can be used for a number of standard basis sets. The quantum mechanical electrostatic potential or a distributed multiple expansion derived electrostatic potential can be calculated and atomic charges can be fitted to these potentials calculated on Connolly surface(s). Reaction pathways and molecular vibrations can be visualized. Input structures can be generated with a Z-matrix editor. A variety of graphics languages is supported: XWindows, postscript, VRML and Povray format.

Computer Simulation↗

PubMed2003

A wavelet-based spatially adaptive method for mammographic contrast enhancement.

A method aimed at minimizing image noise while optimizing contrast of image features is presented. The method is generic and it is based on local modification of multiscale gradient magnitude values provided by the redundant dyadic wavelet transform. Denoising is accomplished by a spatially adaptive thresholding strategy, taking into account local signal and noise standard deviation. Noise standard deviation is estimated from the background of the mammogram. Contrast enhancement is accomplished by applying a local linear mapping operator on denoised wavelet magnitude values. The operator normalizes local gradient magnitude maxima to the global maximum of the first scale magnitude subimage. Coefficient mapping is controlled by a local gain limit parameter. The processed image is derived by reconstruction from the modified wavelet coefficients. The method is demonstrated with a simulated image with added Gaussian noise, while an initial quantitative performance evaluation using 22 images from the DDSM database was performed. Enhancement was applied globally to each mammogram, using the same local gain limit value. Quantitative contrast and noise metrics were used to evaluate the quality of processed image regions containing verified lesions. Results suggest that the method offers significantly improved performance over conventional and previously reported global wavelet contrast enhancement methods. The average contrast improvement, noise amplification and contrast-to-noise ratio improvement indices were measured as 9.04, 4.86 and 3.04, respectively. In addition, in a pilot preference study, the proposed method demonstrated the highest ranking, among the methods compared. The method was implemented in C++ and integrated into a medical image visualization tool.

Algorithms↗

PubMed2006

SAR amplitude probability density function estimation based on a generalized Gaussian model.

In the context of remotely sensed data analysis, an important problem is the development of accurate models for the statistics of the pixel intensities. Focusing on synthetic aperture radar (SAR) data, this modeling process turns out to be a crucial task, for instance, for classification or for denoising purposes. In this paper, an innovative parametric estimation methodology for SAR amplitude data is proposed that adopts a generalized Gaussian (GG) model for the complex SAR backscattered signal. A closed-form expression for the corresponding amplitude probability density function (PDF) is derived and a specific parameter estimation algorithm is developed in order to deal with the proposed model. Specifically, the recently proposed "method-of-log-cumulants" (MoLC) is applied, which stems from the adoption of the Mellin transform (instead of the usual Fourier transform) in the computation of characteristic functions and from the corresponding generalization of the concepts of moment and cumulant. For the developed GG-based amplitude model, the resulting MoLC estimates turn out to be numerically feasible and are also analytically proved to be consistent. The proposed parametric approach was validated by using several real ERS-1, XSAR, E-SAR, and NASA/JPL airborne SAR images, and the experimental results prove that the method models the amplitude PDF better than several previously proposed parametric models for backscattering phenomena.

Algorithms↗

PubMed1998

Understanding the discrepancies between 31P MR spectroscopy assessed liver metabolite concentrations from different institutions.

The high divergence between the liver metabolite concentrations and pH values reported in previous quantitative 31P magnetic resonance studies, for instance phosphomonoester (0.7-3.8 mM) and phosphodiester (3.5-9.7 mM), has not been addressed in the literature. To assess what level of discrepancy can be caused by processing and metabolite integration, in this study chemical shift imaging localized 31P magnetic resonance spectra of human liver were quantitated by three methods currently applied in clinical practice: peak areas defined manually by placement of two cursors vs. frequency domain curve fitting with the assumption of either Gaussian or Lorentzian line shapes. Large reproducible differences were found in liver metabolite peak areas but not in pH, indicating that processing and peak integration methods can only explain part of the discrepancies between the results from different institutions.

Adenosine Triphosphate↗

PubMed1999

Experimental observations of non-Gaussian behavior and stringlike cooperative dynamics in concentrated quasi-two-dimensional colloidal liquids.

We report, from direct observation of particle trajectories as a function of time, the presence of stringlike cooperative motion in a quasi-two-dimensional liquid. We have used digital video microscopy to study the equilibrium dynamics of suspensions of sterically stabilized uncharged poly(methylmethacrylate) spheres confined in a thin glass cell. Our experiments reveal the existence, in semidilute and dense liquid states, of a transition in the qualitative dynamical behavior of the system. At short times particles undergo unhindered Brownian motion, at intermediate times they undergo uncorrelated binary collisions, and at long times these one-particle self-diffusive modes are coupled to collective longitudinal acoustic modes of the fluid, the signature of which is local fluctuating domains of enhanced particle mobility. We study the properties of these domains by examining the density dependence of the van Hove self-correlation function and its deviation from Gaussian behavior. We observe that periods of non-Gaussian behavior correlate precisely with the timing of events involved in the relaxation of "caged" particles and their nearest neighbors. In contrast with relaxation processes in supercooled liquids, the lifetime of dynamical heterogeneities in a dissipative colloidal suspension is found to shift towards shorter time scales with increasing particle density. During time periods for which a quasi-two-dimensional system follows Gaussian behavior, we observe that, as predicted by Cichocki and Felderhof [J. Phys. Condens. Matter 6, 7287 (1994)], the time dependence of the evolution of the effective diffusion coefficient from its short time to its long time value has the form (ln t)/t. This last finding is true for all observed particle densities. To our knowledge, these results are the first experimental verification of the existence of microscopic cooperativity and the predicted temporal evolution of the diffusion coefficient for Brownian motion in concentrated quasi-two-dimensional liquids.

Journal Article↗