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PubMed2001

Latency change estimation for evoked potentials: a comparison of algorithms.

Evoked potentials (EPs) have been widely used to quantify neurological system properties. Changes in EP latency may indicate impending neurological dysfunctions. This paper provides a review and a performance comparison of three classes of latency change estimation algorithms: correlation based, adaptive least mean square (LMS) based, and p-norm based algorithms. Data analysis based on computer simulated data and data from impact acceleration and hypoxia experiments were conducted. This concluded that correlation-based algorithms should only be used when the expected latency change is fixed and the noises are not correlated. While all adaptive LMS type algorithms were capable of tracking and estimating latency changes (fixed or variable) under Gaussian noise conditions, the direct LMS-based algorithm reduced the estimation error power given by traditional filter type LMS algorithms as much as 93%. When periodic interference was present, the frequency selective LMS algorithms outperformed other LMS-based algorithms and reduced of the estimation error power by 89%. Alpha-stable noise processes are better approximations of noises found in various EP analysis applications and adaptive p-norm based algorithms are found to be very robust under such noise conditions, eliminate erroneous abrupt latency changes other algorithms would have produced.

Algorithms↗

PubMed2005

Illusory volumes in human stereo perception.

Any complete theory of human stereopsis must model not only how the correspondences between locations in the two views are determined and the depths are recovered from their disparity, but also how the ambiguity arising from such factors as noise, periodicity, and large regions of constant intensity are resolved and missing data are interpolated. In investigating this process of recovering surface structure from sparse disparity information, using stereo pairs with sparse identifiable features, we made an observation that contradicts all extant models. It suggests the inadequacy of retinotopic representation in modeling surface perception in this stage. We also suggest a possible alternative theory, which is a minimization of the modulus of Gaussian curvature.

Depth Perception↗

PubMed1997

A Comparative Study of Self-organizing Clustering Algorithms Dignet and ART2.

A comparative study of two self-organizing clustering neural network algorithms, Dignet and ART2, has been conducted. The differences in architecture and learning procedures between the two models are compared. Comparative computer simulations on data clustering and signal detection problems with Gaussian noise were used for investigating the performance of Dignet and "fast learning" ART2. The study shows that Dignet, with a simple architecture and straightforward dynamics, is more flexible with the choice of different metrics for the measure of similarity. The system parameters in Dignet can be analytically determined from a self-adjusting process; moreover, the initial threshold value used in Dignet is directly determined from a lower-bound of the desirable operational signal-to-noise ratio. Simulations show that Dignet generally exhibits faster learning and better clustering performance on statistical pattern recognition problems. A simplified ART2 model (SART2) is derived by adopting the structural concepts from Dignet. SART2 exhibits faster learning and eliminates a "false conviction" problem that exists in the "fast learning" ART2. The comparative study is benchmarked against statistical data clustering and signal detection problems. Copyright 1997 Elsevier Science Ltd.

Journal Article↗

PubMed2006

An ignored but most favorable channel for NCO+C2H2 reaction.

The NCO+C(2)H(2) reaction has been considered as a prototype for understanding the chemical reactivity of the isocyanate radical towards unsaturated hydrocarbons in fuel-rich combustion. It has also been proposed to provide an effective route for formation of oxazole-containing compounds in organic synthesis, and might have potential applications in interstellar processes. Unfortunately, this reaction has met mechanistic controversy both between experiments and between experiments and theoretical calculations. In this paper, detailed theoretical investigations at the Becke's three parameter Lee-Yang-Parr-B3LYP6-31G(d), B3LYP6-311++G(d,p), quadratic configuration interaction with single and double excitations QCISD6-31G(d), and Gaussian-3 levels are performed for the NCO+C(2)H(2) reaction, covering various entrance, isomerization, and decomposition channels. Also, the highly cost-expensive coupled-cluster theory including single and double excitations and perturbative inclusion of triple excitations CCSD(T)/aug-cc-pVTZ single-point energy calculation is performed for the geometries obtained at the Becke's three parameter Lee-Yang-Parr-B3LYP6-311++G(d,p) level. A previously ignored yet most favorable channel via a four-membered ring intermediate with allyl radical character is found. However, formation of P(3) H+HCCNCO and the five-membered ring channel predicted by previous experimental and theoretical studies is kinetically much less competitive. With the new channel, master equation rate constant calculations over a wide range of temperatures (298-1500 K) and pressures (10-560 Torr) show that the predicted total rate constants exhibit a positive-temperature dependence and no distinct pressure dependence effect. This is in qualitative agreement with available experimental results. Under the experimental conditions, the predicted values are about 50% lower than the latest experimental results. Also, the branching ratio variations of the fragments P(2) HCN+HCCO and P(5) OCCHCN+H as well as the intermediates L1 HCHCNCO, r4 cCHCHNC-O, and L5 NCHCHCO are discussed with respect to the temperature and pressure. Future experimental reinvestigations are strongly desired to test the newly predicted channel for the model NCO+C(2)H(2) reaction. Implications of the present results in various fields are discussed.

Journal Article↗

PubMed2004

Mean and variance of the Gibbs free energy of oligonucleotides in the nearest neighbor model under varying conditions.

MOTIVATION: In order to assess the stability of DNA-DNA hybridizations-for example during PCR primer design or oligonucleotide selection for microarrays-one needs to predict the change in Gibbs free energy DeltaG during hybridization. The nearest neighbor model provides a good compromise between accuracy and computational simplicity for this task. To determine optimal combinations of reaction parameters (temperature, salt concentration, oligonucleotide length and GC-content), one would like to understand how DeltaG depends on all of these parameters simultaneously. RESULTS: We derive analytic results about the distribution of nearest neighbor DeltaG values for a Bernoulli random sequence model (specified by oligonucleotide length and average GC-content) under given experimental conditions. We find that the distribution of DeltaG values is approximately Gaussian and provide exact formulas for expectation and variance.

Base Composition↗

PubMed1998

Spatio-temporal fMRI analysis using Markov random fields.

Functional magnetic resonance images (fMRI's) provide high-resolution datasets which allow researchers to obtain accurate delineation and sensitive detection of activation areas involved in cognitive processes. To preserve the resolution of this noninvasive technique, refined methods are required in the analysis of the data. In this paper, we first discuss the widely used methods based on a statistical parameter map (SPM) analysis exposing the different shortcomings of this approach when considering high-resolution data. First, the often used Gaussian filtering results in a blurring effect and in delocalization of the activated area. Secondly, the SPM approach only considers false alarms due to noise but not rejections of activated voxels. We propose to embed the fMRI analysis problem into a Bayesian framework consisting of two steps: i) data restoration and ii) data analysis. We, therefore, propose two Markov random fields (MRF's) to solve these two problems. Results on three protocols (visual, motor and word recognition) are shown for two SPM approaches and compared with the proposed MRF approach.

Adult↗

PubMed2005

Isotropic polyharmonic B-splines: scaling functions and wavelets.

In this paper, we use polyharmonic B-splines to build multidimensional wavelet bases. These functions are nonseparable, multidimensional basis functions that are localized versions of radial basis functions. We show that Rabut's elementary polyharmonic B-splines do not converge to a Gaussian as the order parameter increases, as opposed to their separable B-spline counterparts. Therefore, we introduce a more isotropic localization operator that guarantees this convergence, resulting into the isotropic polyharmonic B-splines. Next, we focus on the two-dimensional quincunx subsampling scheme. This configuration is of particular interest for image processing because it yields a finer scale progression than the standard dyadic approach. However, up until now, the design of appropriate filters for the quincunx scheme has mainly been done using the McClellan transform. In our approach, we start from the scaling functions, which are the polyharmonic B-splines and, as such, explicitly known, and we derive a family of polyharmonic spline wavelets corresponding to different flavors of the semi-orthogonal wavelet transform; e.g., orthonormal, B-spline, and dual. The filters are automatically specified by the scaling relations satisfied by these functions. We prove that the isotropic polyharmonic B-spline wavelet converges to a combination of four Gabor atoms, which are well separated in the frequency domain. We also show that these wavelets are nearly isotropic and that they behave as an iterated Laplacian operator at low frequencies. We describe an efficient fast Fourier transform-based implementation of the discrete wavelet transform based on polyharmonic B-splines.

Algorithms↗

PubMed1997

Coronary artery skeleton detection based on topographic features.

A new approach to the problem of detecting the skeletons of coronary arteries in coronary angiograms is proposed. The digitized grayscale coronary angiograms are regarded as noisy sampling of the underlying continuous surface. After the application of Gaussian filtering to reduce noise, the topographic features of the smoothed image are detected based on first and second order image derivatives. Then, the candidate arteries skeleton points are detected based on the observation that arteries are smooth elongated objects having approximately a Gaussian smoothed semi-elliptical profile. Experimental results on real digitized coronary angiograms are presented.

Algorithms↗

PubMedDate not supplied

Quantitative magnetic resonance spectroscopy by optimized numerical curve fitting.

A technique is reported for generating the quantitative area under selected peaks within a 31P NMR spectrum. A numerical iterative method generates the fitted curve so as to minimize the RMS deviation between the fit and the experimental data. The curve is constructed from elemental grains of spectral density ('spexels'), each of which represents an elemental Lorentzian distribution, where the centre frequency and line width of the spexel may be varied within predetermined limits. This provides a fit that in principle is not restricted to a Lorentzian model. The method allows peak areas to be estimated, including the case of overlapping peaks. The method has been tested using simulated spectra containing six overlapping spectral lines each of known amplitude (ranging from 367 to 661 mV) and area; together with additional Gaussian noise with a standard deviation ranging from 30 to 646 mV. The results of fitting both unfiltered and filtered spectra were compared. The variation of quality of fit with spectral noise and filtering has been evaluated. In all cases, the method fitted the peak amplitudes to within 1% of the simulated value. The optimization processes provide an excellent non-linear spectrum filtering algorithm. Provided the noise in the spectra did not exceed ca 400 mV, prefiltered data could be adequately fitted.

Computer Simulation↗

PubMed2006

A new fluorescence band F689 in photosystem II revealed by picosecond analysis at 4-77 K: function of two terminal energy sinks F689 and F695 in PS II.

We performed picosecond time-resolved fluorescence spectroscopy in spinach photosystem II (PS II) particles at 4, 40, and 77 K and identified a new fluorescence band, F689. F689 was identified in addition to the well-known F685 and F695 bands in both analyses of decay-associated spectra and global Gaussian deconvolution of time-resolved spectra. Its fast decay suggests the energy transfer directly from F689 to the reaction center chlorophyll P680. The contribution of F689, which increases only at low temperature, explains the unusually broad and variable bandwidth of F695 at low temperature. Global analysis revealed the three types of excitation energy transfer/dissipation processes: (1) energy transfer from the peripheral antenna to the three core antenna bands F685, F689, and F695 with time constants of 29 and 171 ps at 77 and 4 K, respectively; (2) between the three core bands (0.18 and 0.82 ns); and (3) the decays of F689 (0.69 and 3.02 ns) and F695 (2.18 and 4.37 ns). The retardations of these energy transfer rates and the slow F689 decay rate produced the strong blue shift of the PS II fluorescence upon the cooling below 77 K.

Chlorophyll↗

PubMed2003

A comparison of the wavelet and short-time fourier transforms for Doppler spectral analysis.

Doppler spectrum analysis provides a non-invasive means to measure blood flow velocity and to diagnose arterial occlusive disease. The time-frequency representation of the Doppler blood flow signal is normally computed by using the short-time Fourier transform (STFT). This transform requires stationarity of the signal during a finite time interval, and thus imposes some constraints on the representation estimate. In addition, the STFT has a fixed time-frequency window, making it inaccurate to analyze signals having relatively wide bandwidths that change rapidly with time. In the present study, wavelet transform (WT), having a flexible time-frequency window, was used to investigate its advantages and limitations for the analysis of the Doppler blood flow signal. Representations computed using the WT with a modified Morlet wavelet were investigated and compared with the theoretical representation and those computed using the STFT with a Gaussian window. The time and frequency resolutions of these two approaches were compared. Three indices, the normalized root-mean-squared errors of the minimum, the maximum and the mean frequency waveforms, were used to evaluate the performance of the WT. Results showed that the WT can not only be used as an alternative signal processing tool to the STFT for Doppler blood flow signals, but can also generate a time-frequency representation with better resolution than the STFT. In addition, the WT method can provide both satisfactory mean frequencies and maximum frequencies. This technique is expected to be useful for the analysis of Doppler blood flow signals to quantify arterial stenoses.

Algorithms↗

PubMed2004

Using fragment chemistry data mining and probabilistic neural networks in screening chemicals for acute toxicity to the fathead minnow.

The paper is illustrating how the general data mining methodology may be adapted to provide solutions to the problem of high throughput virtual screening of organic chemicals for possible acute toxicity to the fathead minnow fish. The present approach involves mining fragment information from chemical structures and is using probabilistic neural networks to model the relationship between structure and toxicity. Probabilistic neural networks implement a special class of multivariate non-linear Bayesian statistical models. The mathematical principles supporting their use for value prediction purposes are clarified and their peculiarities discussed. As part of the research phase of the data mining process, a dataset consisting of 800 structures and associated fathead minnow (Pimephales promelas) 96-h LC50 acute toxicity endpoint information is used for both the purpose of identifying an advantageous combination of fragment descriptors and for training the neural networks. As a result, two powerful models are generated. Model 1 implements the basic PNN with Gaussian kernel (statistical corrections included) while Model 2 implements the PNN with Gaussian kernel and separated variables. External validation is performed using a separate dataset consisting of 86 structures and associated toxicity information. Both learning and generalization capabilities of the two models are investigated and their limitations discussed.

Animals↗

PubMed1989

Very large neurons of the inner retina of humans and other mammals.

Large ganglion cells, called parasol cells, are known to occur in the Golgi-stained, human retina. This report describes a population of much larger cells that is not stained by Golgi technique. These cells may be located in the human ganglion cell layer using Nomarski differential interference contrast optics and unstained, flatmounted tissue. These cells are regularly distributed in young and old adults in a Gaussian fashion along the radii that extend from the perimacula toward the far periphery. The author did not find the cells in the central retina. The most frequent (J-type) cells have soma diameters between 26 and 40 microns. Rare (S-type) cells measure up to 55 microns in diameter. Many cells have processes that appear to be axons or dendrites. These cell types may be especially sensitive to damage early in diseases of the inner retina.

Adult↗

PubMed1999

Phase transitions in open quantum systems.

We consider the behavior of open quantum systems through the dependence of the coupling to one decay channel by introducing the coupling parameter alpha, which is proportional to the average degree of overlapping. Under critical conditions, a reorganization of the spectrum takes place that creates a bifurcation of the time scales with respect to the lifetimes of the resonance states. We derive analytically the conditions under which the reorganization process can be understood as a second-order phase transition and illustrate our results by numerical investigations. The conditions are fulfilled, e.g., for a uniform picket-fence level distribution with equal coupling of the states to the continuum. Energy dependencies within the system are included. We consider also the case of an unfolded Gaussian orthogonal ensemble and of a spectrum bounded from below. In all these cases, the reorganization of the spectrum occurs at the critical value alpha(crit) of the control parameter globally over the whole energy range of the spectrum. All states act cooperatively.

Journal Article↗

PubMed1984

Malignant cell detection and cervical cancer screening.

A study was conducted to determine the isolated, single-cell detection characteristics of human observers as this information relates to cervical cancer screening. Two interrelated experiments were performed. First, the receiver operating characteristic (ROC) was obtained for slide screening. In this experiment, approximately 1,200 slides were examined. Second, ROCs were obtained for human observer cell discrimination, using a rating method. An individual's curves were computed, assuming a multiple decision criterion. In this experiment, 6,375 cells from the same specimens used in the slide screening experiment were studied. In both experiments, results were analyzed using a Gaussian signal-detection model. This approach provided analytical detection criteria and rigorous definition of ROCs. These experiments addressed the problem of where the screening information lies: (1) in individual cells alone or (2) with additional components in global or other a priori information. We quantified the detection requirements of (1) the Papanicolaou smear screening process, Az = 0.99, and (2) the capabilities of trained cytotechnologists on isolated single cells, Az = 0.87. System modeling using intermediate cell detection instead of "rare event" detection resulted in a reduction of the predicted number of cells required for analysis from approximately 60,000 to 750.

Female↗

PubMed1995

Signal-to-noise ratio enhancement of cardiac late potentials using ensemble correlation.

An optimal one-weight "filter" is presented for the purpose of improving the signal-to-noise ratio of averaged ECG recordings in the analysis of late potentials. Based on a simple statistical model, the filter is estimated from the ensemble correlation of available beats. The correlation estimator is found by a maximum likelihood procedure in which the observed signal is assumed to have a Gaussian distribution. The performance of the optimal filter is studied in relation to an ensemble with individual or subaveraged beats.

Action Potentials↗

PubMed1999

Adaptive estimation of latency change in evoked potentials by direct least mean p-norm time-delay estimation.

Evoked potentials (EP) have been widely used to quantify neurological system properties. Changes in EP latency may indicate impending neurological injury. Traditional EP analyses are developed under the condition that the background noise in EP analysis are Gaussian distributed. This paper proposes a latency change detection and estimation algorithm under alpha-stable noise condition, a generalization of Gaussian noise assumption. An analysis shows that the alpha-stable model fits the noises found in the impact acceleration experiment under study better than the Gaussian model. The robustness of the proposed algorithm is demonstrated through computer simulations and experimental data analysis under both Gaussian and alpha-stable noise environments.

Algorithms↗

PubMed2005

Fetal electrocardiogram extraction by sequential source separation in the wavelet domain.

This paper addresses the problem of fetal electrocardiogram extraction using blind source separation (BSS) in the wavelet domain. A new approach is proposed, which is particularly advantageous when the mixing environment is noisy and time-varying, and that is shown, analytically and in simulation, to improve the convergence rate of the natural gradient algorithm. The distribution of the wavelet coefficients of the source signals is then modeled by a generalized Gaussian probability density, whereby in the time-scale domain the problem of selecting appropriate nonlinearities when separating mixtures of both sub- and super-Gaussian signals is mitigated, as shown by experimental results.

Algorithms↗