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PubMed2004

Temporal order of nonlinear dynamics in human brain.

In previous spectral analysis investigations, we demonstrated that the spontaneous activity of the alpha EEG is not stationary but rather shows cyclic alterations with a circa 1-min periodicity. Following the conclusion that a power increase in the alpha band implies a neuronal synchronization, and vice versa, an associated decrease of the EEG complexity was postulated. Accordingly, a rhythmic variation, i.e., a temporal order of the nonlinear dynamics with similar period length, was expected. Bipolar 4-min EEG recordings were obtained from 20 awake subjects (mean age: 23.5+/-2.5 years) with eyes closed for the EEG leads C3, C4, Oz, and Fz according to the 10-20 system. For the automatic evaluation of spontaneous alterations of complexity, a sliding computation of the so-called correlation dimension, using an analysis window length of 20 s continuously shifted by 1 s, was performed. The time series of complexity exhibited an oscillatory behavior with a mean period length of 58.7 s; the Friedman test statistic revealed no significant topological differences. For the rejection of the null hypothesis that the observed periodicity is a random one, two-group t-tests and ANOVA with repeated measures were performed, comparing the corresponding amplitudes and period lengths with those derived from 20 pseudo-random signals (taken from a multivariate Gaussian normal distribution). The mean relative change of EEG complexity was highly significantly increased (P<0.0001) compared to that of random data. Likewise, the difference of mean period lengths was also significant (P<0.01). The results indicate that the coupling strength of the neural network of the brain changes periodically, with a cyclic alteration from a central to a parallel processing mode of information, reflecting state transitions from synchronized, low-complex EEG activity to desynchronized high-complex activity, and vice versa. Various neuronal control mechanisms that may be acting as pacemakers responsible for the temporal order of such transients are discussed. A disturbance of the temporal order may be of pathophysiological significance.

Action Potentials↗

PubMed2005

Chromatographic preprocessing of GC-MS data for analysis of complex chemical mixtures.

Hyphenated analytical techniques such as gas chromatography-mass spectrometry (GC-MS) can provide extensive amounts of analytical data when applied to environmental samples. Quantitative analyses of complex contaminant mixtures by commercial preprocessing software are time-consuming, and baseline distortion and incomplete peak resolution increase the uncertainty and subjectivity of peak quantification. Here, we present a semi-automatic method developed specific for processing complex first-order chromatographic data (e.g. selected ion monitoring in GC-MS) prior to chemometric data analysis. Chromatograms are converted into semi-quantitative variables (e.g. diagnostic ratios (DRs)) that can be exported directly to appropriate softwares. The method is based on automatic peak matching, initial parameterization, alternating background noise reduction and peak estimation using mathematical functions (Gaussian and exponential-Gaussian hybrid) with few (i.e. three to four) parameters. It is capable of resolving convoluted peaks, and the exponential-Gaussian hybrid improves the description of asymmetric peaks (i.e. fronting and tailing). The optimal data preprocessing suggested in this article consists of estimation of Gaussian peak parameters and subsequent calculation of diagnostic ratios from peak heights. We tested the method on chromatographic data from 20 replicate oil samples and found it to be less time-consuming and subjective than commercial software, and with comparable data quality.

Gas Chromatography-Mass Spectrometry↗

PubMed2004

Optimization of an independent component analysis approach for artifact identification and removal in magnetoencephalographic signals.

OBJECTIVE: To propose a noise reduction procedure for magnetoencephalography (MEG) signals introducing an automatic detection system of artifactual components (ICs) separated by an independent component analysis (ICA) algorithm, and a control cycle on reconstructed cleaned data to recovery part of non-artifactual signals possibly lost by the blind mechanism. METHODS: The procedure consisted of three main steps: (1) ICA for blind source separation (BSS); (2) automatic detection method of artifactual components, based on statistical and spectral ICs characteristics; (3) control cycle on 'discrepancy,' i.e. on the difference between original data and those reconstructed using only ICs automatically retained. Simulated data were generated as representative mixtures of some common brain frequencies, a source of internal Gaussian noise, power line interference, and two real artifacts (electrocardiogram=ECG, electrooculogram=EOG), with the adjunction of a matrix of Gaussian external noise. Three real data samples were chosen as representative of spontaneous noisy MEG data. RESULTS: In simulated data the proposed set of markers selected three components corresponding to ECG, EOG and the Gaussian internal noise; in real-data examples, the automatic detection system showed a satisfactory performance in detecting artifactual ICs. 'Discrepancy' control cycle was redundant in simulated data, as expected, but it was a significant amelioration in two of the three real-data cases. CONCLUSIONS: The proposed automatic detection approach represents a suitable strengthening and simplification of pre-processing data analyses. The proposed 'discrepancy' evaluation, after automatic pruning, seems to be a suitable way to render negligible the risk of loose non-artifactual activity when applying BSS methods to real data. SIGNIFICANCE: The present noise reduction procedure, including ICA separation phase, automatic artifactual ICs selection and 'discrepancy' control cycle, showed good performances both on simulated and real MEG data. Moreover, application to real signals suggests the procedure to be able to separate different cerebral activity sources, even if characterized by very similar frequency contents.

Algorithms↗

PubMed2005

Thermal decomposition hazard evaluation of hydroxylamine nitrate.

Hydroxylamine nitrate (HAN) is an important member of the hydroxylamine family and it is a liquid propellant when combined with alkylammonium nitrate fuel in an aqueous solution. Low concentrations of HAN are used primarily in the nuclear industry as a reductant in nuclear material processing and for decontamination of equipment. Also, HAN has been involved in several incidents because of its instability and autocatalytic decomposition behavior. This paper presents calorimetric measurement for the thermal decomposition of 24 mass% HAN/water. Gas phase enthalpy of formation of HAN is calculated using both semi-empirical methods with MOPAC and high-level quantum chemical methods of Gaussian 03. CHETAH is used to estimate the energy release potential of HAN. A Reactive System Screening Tool (RSST) and an Automatic Pressure Tracking Adiabatic Calorimeter (APTAC) are used to characterize thermal decomposition of HAN and to provide guidance about safe conditions for handling and storing of HAN.

Calorimetry↗

PubMed2006

Limited flexibility in the filter underlying saccadic targeting.

The choice of where to look in a visual scene depends on visual processing of information from potential target locations. We examined to what extent the sampling window, or filter, underlying saccadic eye movements is under flexible control and adjusted to the behavioural task demands. Observers performed a contrast discrimination task with systematic variations in the spatial scale and location of the visual signals: small (sigma=0.175 degrees ) or large (sigma=0.8 degrees ) Gaussian signals were presented 4.5 degrees , 6 degrees , or 9 degrees away from central fixation. In experiment 1, we measured the accuracy of the first saccade as a function of target contrast. The efficiency of saccadic targeting decreased with increases in both scale and eccentricity. In experiment 2, the filter underlying saccadic targeting was estimated with the classification image method. We found that the filter (1) had a center-surround organisation, even though the signal was Gaussian; (2) was much too small for the large scale items; (3) remained constant up to the largest measured eccentricity of 9 degrees . The filter underlying the decision of where to look is not fixed, and can be adjusted to the task demands. However, there are clear limits to this flexibility. These limits reflect the coding of visual information by early mechanisms, and the extent to which the neural circuitry involved in programming saccadic eye movements is able to appropriately weigh and combine the outputs from these mechanisms.

Choice Behavior↗

PubMed2004

Electron and nuclear dynamics of molecular clusters in ultraintense laser fields. II. Electron dynamics and outer ionization of the nanoplasma.

We explore electron dynamics in molecular (CD4)(1061) clusters and elemental Xen (n=249-2171) clusters, responding to ultraintense (intensity I=10(16)-10(19) W cm(-2)) laser fields. Molecular dynamics simulations (including magnetic field and relativistic effects) and analyses of high-energy electron dynamics and nuclear ion dynamics in a cluster interacting with a Gaussian shaped laser field (frequency 0.35 fs(-1), photon energy 1.44 eV, phase 0, temporal width 25 fs) elucidated the time dependence of inner ionization, the formation of a nanoplasma of unbound electrons within the cluster or its vicinity, and of outer ionization. We determined the cluster size and the laser intensity dependence of these three sequential-parallel electronic processes. The characteristic times for cluster inner ionization (tau(ii)) and for outer ionization (tau(oi)) fall in the femtosecond time domain, i.e., tau(ii)=2-9 fs and tau(oi)=4-15 fs for (CD4)(1061), tau(ii)=7-30 fs and tau(oi)=5-13 fs for Xe(n) (n=479,1061), with both tau(ii) and tau(oi) decreasing with increasing I, in accord with the barrier suppression ionization mechanism for inner ionization of the constituents and the cluster barrier suppression ionization mechanism for outer ionization. The positive delay times Deltatau(OI) between outer and inner ionization (e.g., Deltatau(OI)=6.5 fs for Xen at I=10(16) W cm(-2) and Deltatau(OI)=0.2 fs for (CD4)(1061) at I=10(19) W cm(-2)) demonstrate that the outer/inner ionization processes are sequential. For (CD4)(1061), tau(ii) tau(oi), reflecting on the energetic hierarchy in the ionization of the Xe atoms. Quasiresonance contributions to the outer ionization of the nanoplasma were established, as manifested in the temporal oscillations in the inner/outer ionization levels, and in the center of mass of the nanoplasma electrons. The formation characteristics, dynamics, and response of the nanoplasma in molecular or elemental clusters were addressed. The nanoplasma is positively charged, with a high-average electron density [rho(P)=(2-3)10(22) cm(-3)], being characterized by high-average electron energies epsilon(av) (e.g., in Xe(1061) clusters epsilon(av)=54 eV at I=10(16) W cm(-2) and epsilon(av)=0.56-0.37 keV at I=10(18) W cm(-2), with epsilon(av) proportional, variant I(1/2)). Beyond the cluster boundary the average electron energy markedly increases, reaching electron energies in the range of 1.2-40 keV for outer ionization of Xe(n) (n=249-2171) clusters. The nanoplasma exhibits spatial inhomogeneity and angular anisotropy induced by the laser field. Femtosecond time scales are predicted for the nanoplasma production (rise times 7-3 fs), for the decay (decay times approximately 5 fs), and for the persistence time (30-10 fs) of a transient nanoplasma at I=10(17)-10(18) W cm(-2). At lower intensities of I=10(16) W cm(-2) a persistent nanoplasma with a "long" lifetime of > 50 fs will prevail.

Journal Article↗

PubMed1992

The extraction and use of facial features in low bit-rate visual communication.

A review is given of experimental investigations by the author and his collaborators into methods of extracting binary features from images of the face and hands. The aim of the research has been to enable deaf people to communicate by sign language over the telephone network. Other applications include model-based image coding and facial-recognition systems. The paper deals with the theoretical postulates underlying the successful experimental extraction of facial features. The basic philosophy has been to treat the face as an illuminated three-dimensional object and to identify features from characteristics of their Gaussian maps. It can be shown that in general a composite image operator linked to a directional-illumination estimator is required to accomplish this, although the latter can often be omitted in practice.

Face↗

PubMed1999

Photon dose calculation based on electron multiple-scattering theory: primary dose deposition kernels.

The transport of the secondary electrons resulting from high-energy photon interactions is essential to energy redistribution and deposition. In order to develop an accurate dose-calculation algorithm for high-energy photons, which can predict the dose distribution in inhomogeneous media and at the beam edges, we have investigated the feasibility of applying electron transport theory [Jette, Med. Phys. 15, 123 (1988)] to photon dose calculation. In particular, the transport of and energy deposition by Compton electron and electrons and positrons resulting from pair production were studied. The primary photons are treated as the source of the secondary electrons and positrons, which are transported through the irradiated medium using Gaussian multiple-scattering theory [Jette, Med. Phys. 15, 123 (1988)]. The initial angular and kinetic energy distribution(s) of the secondary electrons (and positrons) emanating from the photon interactions are incorporated into the transport. Due to different mechanisms of creation and cross-section functions, the transport of and the energy deposition by the electrons released in these two processes are studied and modeled separately based on first principles. In this article, we focus on determining the dose distribution for an individual interaction site. We define the Compton dose deposition kernel (CDK) or the pair-production dose deposition kernel (PDK) as the dose distribution relative to the point of interaction, per unit interaction density, for a monoenergetic photon beam in an infinite homogeneous medium of unit density. The validity of this analytic modeling of dose deposition was evaluated through EGS4 Monte Carlo simulation. Quantitative agreement between these two calculations of the dose distribution and the average energy deposited per interaction was achieved. Our results demonstrate the applicability of the electron dose-calculation method to photon dose calculation.

Algorithms↗

PubMed2005

Phase-space analysis of acoustics fields and its application to waveguide.

A description of two-dimensional acoustic fields by means of a joint "space-wave number" representation is discussed. A function defined in the phase-space domain (x,y,k(x),k(y)) is associated with a signal which is a function of spatial coordinates (x,y). This paper presents two methods to realize it. The first is to associate with each point (x,y) of the wave field a two-dimensional wave number spectrum (k(x),k(y)), called local spectrum. The second is to process by other coordinates the wave field along an arbitrary direction, introduced in quantum mechanics for the study of classical billiards, and provided by the Birkhoff variables (s,cos phi). Phase-space diagrams are given by quadratic phase-space distributions. Simulations are presented for wave fields in a 2D planar waveguide for a pedagogical point of view with Gaussian beam or point-source excitation, and nonuniform waveguides as a sudden area expansion chamber and an open billiard with a single incoming mode at the entrance of each of them. In these problems, local spectrum and Birkhoff analysis are used in order to identify the structures hidden in the field. The result is the contribution of different wave vectors which contribute to the field value at the analysis point or at a certain section of the boundary, and show complicated structure of the acoustic field like whispering gallery or diffracted waves.

Journal Article↗

PubMed1988

Mislocalization of diplopic images.

When observers dichoptically view bar stimuli at disparities beyond the fusion limit, the bars are perceived as being closer together than they really are. When 6.0-cycle/deg vertical derivative-of-Gaussian bars are adjusted into apparent alignment with binocularly presented spots, the mislocalization of each bar's half-image is typically 2-5 arcmin for disparities below 60 arcmin. The effect does not generalize to an additional monocular probe bar at more-eccentric locations, thus excluding reflex vergence eye movements as an explanation. Instead, the results indicate a process of interocular matching that seeks to attribute similar directions as well as depths to matching half-images.

Depth Perception↗

PubMed2003

A fast and reliable technique for muscle activity detection from surface EMG signals.

The estimation of on-off timing of human skeletal muscles during movement is an important issue in surface electromyography (EMG) signal processing with relevant clinical applications. In this paper, a novel approach to address this issue is proposed. The method is based on the identification of single motor unit action potentials from the surface EMG signal with the use of the continuous wavelet transform. A manifestation variable is computed as the maximum of the outputs of a bank of matched filters at different scales. A threshold is applied to the manifestation variable to detect EMG activity. A model, based on the physical structure of the muscle, is used to test the proposed technique on synthetic signals with known features. The resultant bias of the onset estimate is lower than 40 ms and the standard deviation lower than 30 ms in case of additive colored Gaussian noise with signal-to-noise ratio as low as 2 dB. Comparison with previously developed methods was performed, and representative applications to experimental signals are presented. The method is designed for a complete real-time implementation and, thus, may be applied in clinical routine activity.

Action Potentials↗

PubMed2005

Change in relaxation scenario at the order-disorder transition of a colloidal fluid of hard spheres seen from the Gaussian limit of the self-intermediate scattering function.

Self-intermediate scattering functions (ISFs) are measured by dynamic light scattering for the colloidal fluid of hard spheres for both equilibrium and nonequilibrium (undercooled) conditions, i.e., for volume fractions below and above the known freezing transition of the hard-sphere system. The delay time tau(m) where the mean-squared displacement, or the low wave-vector limit of the ISF, exhibits its maximum stretching is identified as a characteristic of the non-Markovian process(es) and is used to separate the ISF into fast (tau < tau(m)) and slow (tau > tau(m)) contributions. Each of these contributions exposes qualitative differences in the dynamics of the particles between the equilibrium and nonequilibrium colloidal fluids. These changes in the relaxation scenario signal the colloidal fluid's awareness of its traversal of the freezing volume fraction.

Journal Article↗

PubMedDate not supplied

Automated determination of parameters describing power spectra of micrograph images in electron microscopy.

The current theory of image formation in electron microscopy has been semi-quantitatively successful in describing data. The theory involves parameters due to the transfer function of the microscope (defocus, spherical aberration constant, and amplitude constant ratio) as well as parameters used to describe the background and attenuation of the signal. We present empirical evidence that at least one of the features of this model has not been well characterized. Namely the spectrum of the noise background is not accurately described by a Gaussian and associated "B-factor;" this becomes apparent when one studies high-quality far-from focus data. In order to have both our analysis and conclusions free from any innate bias, we have approached the questions by developing an automated fitting algorithm. The most important features of this routine, not currently found in the literature, are (i). a process for determining the cutoff for those frequencies below which observations and the currently adopted model are not in accord, (ii). a method for determining the resolution at which no more signal is expected to exist, and (iii). a parameter-with units of spatial frequency-that characterizes which frequencies mainly contribute to the signal. Whereas no general relation is seen to exist between either of these two quantities and the defocus, a simple empirical relationship approximately relates all three.

Algorithms↗

PubMed2006

Enhancing digital cephalic radiography with mixture models and local gamma correction.

We present a new algorithm, called the soft-tissue filter, that can make both soft and bone tissue clearly visible in digital cephalic radiographies under a wide range of exposures. It uses a mixture model made up of two Gaussian distributions and one inverted lognormal distribution to analyze the image histogram. The image is clustered in three parts: background, soft tissue, and bone using this model. Improvement in the visibility of both structures is achieved through a local transformation based on gamma correction, stretching, and saturation, which is applied using different parameters for bone and soft-tissue pixels. A processing time of 1 s for 5 Mpixel images allows the filter to operate in real time. Although the default value of the filter parameters is adequate for most images, real-time operation allows adjustment to recover under- and overexposed images or to obtain the best quality subjectively. The filter was extensively clinically tested: quantitative and qualitative results are reported here.

Algorithms↗

PubMed1980

Detection of temporally uncertain signals.

The effects of signal uncertainty on detection performance were measured using a new procedure that allows precise specification of the initial temporal uncertainty. Five different models of the detection process, two assuming a continous representation of the sensory input and three assuming a discrete representation, were compared with the obtained data. The effects of varying signal uncertainty (the number of potential signal intervals was one, five, or ten) had little effect on detection performance. The one-parameter form of the choice model can be rejected without hesitation. The continuous Gaussian model and the symmetric two-state model are significantly different from the data. The high threshold and sophisticated two-state models provide accurate descriptions of the data that cannot be rejected on statistical grounds.

Acoustic Stimulation↗

PubMed2002

Surface curvatures of trabecular bone microarchitecture.

Microstructure of trabecular bone has been examined with a particular emphasis on surface curvatures in two-phase (trabecular and intertrabecular space- i.e., marrow space) structures. Three trabecular bone samples, quantified as "plate-like," "rod-like," and a mixture of these two structural elements according to the structure model index (SMI), were subjected to analysis based on (differential) geometry. A correspondence between the SMI and the mean curvature was found. A method to measure surface curvatures is proposed. The gaussian curvatures averaged over the surfaces for the three analyzed bone structures were all found to be negative, demonstrating their surfaces to be, on average, hyperbolic. In addition, the Euler-Poincaré characteristics and the genus, both characterizing topological features of bone connectivity, were estimated from integral gaussian curvature (Gauss-Bonnet theorem). The three bone microstructures were found to be topologically analogous to spheres with one to three handles.

Bone and Bones↗

PubMed2004

Denoising functional MR images: a comparison of wavelet denoising and Gaussian smoothing.

We present a general wavelet-based denoising scheme for functional magnetic resonance imaging (fMRI) data and compare it to Gaussian smoothing, the traditional denoising method used in fMRI analysis. One-dimensional WaveLab thresholding routines were adapted to two-dimensional (2-D) images, and applied to 2-D wavelet coefficients. To test the effect of these methods on the signal-to-noise ratio (SNR), we compared the SNR of 2-D fMRI images before and after denoising, using both Gaussian smoothing and wavelet-based methods. We simulated a fMRI series with a time signal in an active spot, and tested the methods on noisy copies of it. The denoising methods were evaluated in two ways: by the average temporal SNR inside the original activated spot, and by the shape of the spot detected by thresholding the temporal SNR maps. Denoising methods that introduce much smoothness are better suited for low SNRs, but for images of reasonable quality they are not preferable, because they introduce heavy deformations. Wavelet-based denoising methods that introduce less smoothing preserve the sharpness of the images and retain the original shapes of active regions. We also performed statistical parametric mapping on the denoised simulated time series, as well as on a real fMRI data set. False discovery rate control was used to correct for multiple comparisons. The results show that the methods that produce smooth images introduce more false positives. The less smoothing wavelet-based methods, although generating more false negatives, produce a smaller total number of errors than Gaussian smoothing or wavelet-based methods with a large smoothing effect.

Algorithms↗

PubMed1986

A design for a general digital filter for state estimation of an arbitrary stochastic sound system.

This article describes a new attempt at the design of a general digital filter for the state estimation of a nonstationary nonlinear stochastic sound system. A recursive algorithm for estimating the higher-order statistics of arbitrary-function type, mean, and variance is obtained by introducing a new expansion form of Bayes' theorem. Further, the state probability density function (PDF) can also be estimated in a unified form of orthogonal or nonorthogonal series expansions by using these estimates. This method is widely applicable for cases where the random-noise fluctuation is non-Gaussian. The estimation algorithm proposed in this article agrees completely with a well-known Kalman filtering theory [J. Basic Eng. 82, 35-45 (1960); Kalman and Buchy, J. Basic Eng. 83, 95-108 (1961)], as a simplified special case when the stochastic system is of linear type with Gaussian random excitation. The validity and effectiveness of the proposed theory were confirmed experimentally by applying it to actually observed room acoustic data and road-traffic noise data.

Algorithms↗