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PubMed1992

Deterministic nonlinear chaos in brain function and borderline psychopathological phenomena.

There exists a fundamental overall property of the brain which monitors, modulates, and ensures a smoothness of function and which further determines elegance and grace in functioning. This property also imparts a quality of, or a sense of proportion among all other faculties of the brain. It is postulated in this paper that such a property/function, up to now almost taken for granted, is maintained/exercised by a nonlinear deterministic chaotic mode of brain function. If this is the case, borderline psychopathological phenomena, when they flare up, can be explained as resulting from sudden reduction of such a deterministic chaotic mode and the emergence of a pathological order, as the system becomes an oscillating one.

Borderline Personality Disorder↗
PubMed2004

Multi-echo imaging in highly inhomogeneous magnetic fields.

A new pulsed field gradient multi-echo imaging technique to encode position in the phase of every echo generated by a CPMG sequence in the presence of a strongly inhomogeneous static magnetic field is presented. It was applied to improve the sensitivity in an imaging experiment by adding the echo train acquired during the CPMG sequence and to spatially resolve relaxation times of inhomogeneous specimens using single-sided probes. The sequence was implemented in a new bar-magnet MOUSE equipped with a gradient coil system to apply a pulsed magnetic field with a constant gradient along one spatial coordinate. An important reduction by a factor larger than two orders of magnitude in the acquisition time was obtained compared to the previously published single-point imaging technique.

Algorithms↗
PubMed2004

APART: automated preprocessing for NMR assignments with reduced tedium.

MOTIVATION: High-throughput NMR structure determination is a goal that will require progress on many fronts, one of which is rapid resonance assignment. An important rate-limiting step in the resonance assignment process is accurate identification of resonance peaks in the NMR spectra. Peak-picking schemes range from incomplete (which lose essential assignment connectivities) to noisy (which obscure true connectivities with many false ones). We introduce an automated preassignment process that removes false peaks from noisy peak lists by requiring consensus between multiple NMR experiments and exploiting a priori information about NMR spectra. This process is designed to accept multiple input formats and generate multiple output formats, in an effort to be compatible with a variety of user preferences. RESULTS: Automated preprocessing with APART rapidly identifies and removes false peaks from initial peak lists, reduces the burden of manual data entry, and documents and standardizes the peak filtering process. Successful preprocessing is demonstrated by the increased number of correct assignments obtained when data are submitted to an automated assignment program. AVAILABILITY: APART is available from http://sir.lanl.gov/NMR/APART.htm CONTACT: npawley@lanl.gov; rmichalczyk@lanl.gov SUPPLEMENTARY INFORMATION: Manual pages with installation instructions, procedures and screen shots can also be found at http://sir.lanl.gov/NMR/APART_Manual1.pdf.

Algorithms↗
PubMed1998

A quantitative method for the detection of edges in noisy time-series.

A modification of the edge detector of Chung & Kennedy is proposed in which the output provides confidence limits for the presence or absence of sharp edges (steps) in the input waveform. Their switching method with forward and backward averaging windows is retained, but the output approximates an ideal output function equal to the difference in these averages divided by the standard deviation of the noise. Steps are associated with peak output above a pre-set threshold. Formulae for the efficiency and reliability of this ideal detector are derived for input waveforms with Gaussian white noise and sharp edges, and serve as benchmarks for the switching edge detector. Efficiency is kept high if the threshold is a fixed fraction of the step size of interest relative to noise, and reliability is improved by increasing the window width W to reduce false output. For different steps sizes D, the window width for fixed efficiency and reliability scales as 1/D2. Versions with weighted averaging (flat, ramp, triangular) or median averaging but the same window width perform similarly. Binned above-threshold output is used to predict the locations and signs of detected steps, and simulations show that efficiency and reliability are close to ideal. Location times are accurate to order square root of W. Short pulses generate reduced output if the number of data points in the pulse is less than W. They are optimally detected by choosing W as above and collecting data at a rate such that the pulse contains approximately W data points. A Fortran program is supplied.

Signal Processing, Computer-Assisted↗
PubMed2002

Narrowband auscultatory blood pressure measurement.

Auscultatory blood pressure measurement uses the presence and absence of acoustic pulses generated by an artery (i.e., Korotkoff sound), detected with a stethoscope or a sensitive microphone, to noninvasively estimate systolic and diastolic pressures. Unfortunately, in high noise situations, such as ambulatory environments or when the patient moves moderately, the current auscultatory blood pressure method is unreliable, if at all possible. Empirical evidence suggests that the pulse beneath an artery occlusion travels relatively slow compared with the speed of sound. By placing two microphones along the bicep muscle near the brachial artery under the occlusion cuff, a similar blood pressure pulse appears in the two microphones with a relative time delay. The acoustic noise, on the other hand, appears in both microphones simultaneously. The contribution of this paper is to utilize this phenomenon by filtering the microphone waveforms to create spatially narrowband information signals. With a narrowband signal, the microphone signal phasing information is adequate for distinguishing between acoustic noise and the blood pressure pulse. By choosing the microphone spacing correctly, subtraction of the two signals will enhance the information signal and cancel the noise signal. The general spacing problem is also presented.

Acoustics↗
PubMed2003

Noise reduction for magnetic resonance images via adaptive multiscale products thresholding.

Edge-preserving denoising is of great interest in medical image processing. This paper presents a wavelet-based multiscale products thresholding scheme for noise suppression of magnetic resonance images. A Canny edge detector-like dyadic wavelet transform is employed. This results in the significant features in images evolving with high magnitude across wavelet scales, while noise decays rapidly. To exploit the wavelet interscale dependencies we multiply the adjacent wavelet subbands to enhance edge structures while weakening noise. In the multiscale products, edges can be effectively distinguished from noise. Thereafter, an adaptive threshold is calculated and imposed on the products, instead of on the wavelet coefficients, to identify important features. Experiments show that the proposed scheme better suppresses noise and preserves edges than other wavelet-thresholding denoising methods.

Algorithms↗
PubMed2003

Speckle reduction in optical coherence tomography by "path length encoded" angular compounding.

Speckle, the dominant factor reducing image quality in optical coherence tomography (OCT), limits the ability to identify cellular structures that are essential for diagnosis of a variety of diseases. We describe a new high-speed method for implementing angular compounding by path length encoding (ACPE) for reducing speckle in OCT images. By averaging images obtained at different incident angles, with each image encoded by path length, ACPE maintains high-speed image acquisition and requires minimal modifications to OCT probe optics. ACPE images obtained from tissue phantoms and human skin in vivo demonstrate a qualitative improvement over traditional OCT and an increased SNR that correlates well with theory.

Algorithms↗
PubMed2006

On indeterminism, chaos, and small number particle systems in the brain.

This paper presents rational, theoretical, and empirical grounds for doubting the principle of determinism in nature and in the brain, and discusses implications of this for free will and the chaos model of the brain. Small number particle systems are practically indeterministic and may be intrinsically indeterministic. Determinism in nature has often been taken to preclude free will. Strict determinism is a concept frequently applied to systems theory, establishing, e.g., the uniqueness of state-space trajectories. In order to consider determinism as a law of nature, however, one must be able to subject it to empirical tests. Presently, one is not able to and whether this can be shown to enable free will or not is not clear. It does remove, at least for the present, determinism itself as a rationale for precluding free will. The work partially supports the chaos model, but weakens the computational computer metaphor of brain function.

Animals↗
PubMed2003

From wavelets to adaptive approximations: time-frequency parametrization of EEG.

This paper presents a summary of time-frequency analysis of the electrical activity of the brain (EEG). It covers in details two major steps: introduction of wavelets and adaptive approximations. Presented studies include time-frequency solutions to several standard research and clinical problems, encountered in analysis of evoked potentials, sleep EEG, epileptic activities, ERD/ERS and pharmaco-EEG. Based upon these results we conclude that the matching pursuit algorithm provides a unified parametrization of EEG, applicable in a variety of experimental and clinical setups. This conclusion is followed by a brief discussion of the current state of the mathematical and algorithmical aspects of adaptive time-frequency approximations of signals.

Algorithms↗
PubMed2005

Phase-unwrapping algorithm for images with high noise content based on a local histogram.

We present a robust algorithm of phase unwrapping that was designed for use on phase images with high noise content. We proceed with the algorithm by first identifying regions with continuous phase values placed between fringe boundaries in an image and then phase shifting the regions with respect to one another by multiples of 2pi to unwrap the phase. Image pixels are segmented between interfringe and fringe boundary areas by use of a local histogram of a wrapped phase. The algorithm has been used successfully to unwrap phase images generated in a three-dimensional shape measurement for noninvasive quantification of human skin structure in dermatology, cosmetology, and plastic surgery.

Algorithms↗
PubMed1993

Automatic detection of K-complexes: validation in normals and dysthymic patients.

A model-based automatic K-complex (Kc) detector was applied to all-night single-channel sleep electroencephalographic (EEG) recordings from normal and dysthymic patients. The performance of the detector was analyzed in the two groups, and the differences obtained were discussed. The results showed that the detection rate of Kc in the normal group was around 92% through all stages of non-rapid eye movement (NREM) sleep, but with high numbers of "false" positives in stage 4 NREM, which reached 57%. In the dysthymic patients "true" detection included 85% of the Kc, but the percentage of "false" positives dropped to 25% in stage 4 NREM. Most of the "false" detections in the normal group were due to sharp delta activity during slow wave sleep (SWS). The results in the patient group were expected, because sleep in dysthymics showed a reduction in SWS when compared to normals. The behavior and automatic artifact rejection mechanisms of the detector are briefly presented. The model-based Kc detector performed significantly better than other automatic detectors described in the literature; it was found to be a useful tool for routine sleep EEG studies.

Adult↗
PubMed1984

Demographic influences on mitochondrial DNA lineage survivorship in animal populations.

Probability models of branching processes and computer simulations of these models are used to examine stochastic survivorship of female lineages under a variety of demographic scenarios. A parameter II, defined as the probability of survival of two or more independent lineages over G generations, is monitored as a function of founding size of a population, population size at carrying capacity, and the frequency distributions of surviving progeny. Stochastic lineage extinction can be very rapid under certain biologically plausible demographic conditions. For stable-sized populations initiated by n females and/or regulated about carrying capacity k = n, it is highly probable that within about 4n generations all descendants will trace their ancestries to a single founder female. For a given mean family size, increased variance decreases lineage survivorship. In expanding populations, however, lineage extinction is dramatically slowed, and the final k value is a far more important determinant of II than is the size of the population at founding. The results are discussed in the context of recent empirical observations of low mitochondrial DNA (mtDNA) sequence heterogeneity in humans and expected distributions of asexually transmitted traits among sexually reproducing species.

Animals↗
PubMed2001

[Psychophysiological mechanisms of the vitauct].

Psychophysiological mechanisms of vitaukt in human information processing were studied. 90 women and 60 men and in four age groups: 20-29, 30-39, 40-49 and 50-60 were examined. The information processing was studied by three computer's tests with difference complexity. The time and accuracy of each assignment were registered for each tests. The psychophysiological organization as characteristic of human functional system was studied by entropy. The results are showed increase of determinism of psychophysiological organization with simplification of informational processing. Aging weakening of psychophysiological organization determinism reflects in the increasing of informational processing protraction. The psychophysiological mechanism of vitaukt relation with increases the stochastic of informational processing system in aging involution condition.

Adaptation, Physiological↗
PubMed2001

Information transfer with rate-modulated Poisson processes: a simple model for nonstationary stochastic resonance.

Stochastic resonance in a simple model of information transfer is studied for sensory neurons and ensembles of ion channels. An exact expression for the information gain is obtained for the Poisson process with the signal-modulated spiking rate. This result allows one to generalize the conventional stochastic resonance (SR) problem (with periodic input signal) to the arbitrary signals of finite duration (nonstationary SR). Moreover, in the case of a periodic signal, the rate of information gain is compared with the conventional signal-to-noise ratio. The paper establishes the general nonequivalence between both measures notwithstanding their apparent similarity in the limit of weak signals.

Action Potentials↗
PubMed2001

Protein-protein ratchets: stochastic simulation and application to processive enzymes.

Interaction between a protein and a series of binding sites on a cytoskeletal substrate can create a resistance, or "protein friction," as the protein is moved along the substrate. If attachment and detachment rates are specified asymmetrically, this resistance can depend on the direction of movement, and the binding interaction acts as a ratchet. Stochastic computer simulations have been used to examine this type of protein-protein interaction. The performance of a protein-protein ratchet in the piconewton and nanometer range is significantly limited by thermal fluctuations, which in experimental measurements with single molecules are evident as Brownian motion. Simulations with a two-component model combining a conventional motor enzyme model with a protein-protein ratchet confirm previous suggestions that the processive movement of a single motor enzyme molecule against a load, as seen in experiments with inner arm dynein molecules, might be made possible by an accessory protein interaction that prevents backward slippage. When this accessory protein interaction is defined so that it acts as a ratchet, backward slippage can be prevented with minimal interference with forward progression.

Binding Sites↗
PubMed2005

A stochastic model and a functional central limit theorem for information processing in large systems of neurons.

The paper deals with information transmission in large systems of neurons. We model the membrane potential in a single neuron belonging to a cell tissue by a non time-homogeneous Cox-Ingersoll-Ross type diffusion; in terms of its time-varying expectation, this stochastic process can convey deterministic signals. We model the spike train emitted by this neuron as a Poisson point process compensated by the occupation time of the membrane potential process beyond the excitation threshold. In a large system of neurons 1 < or = i < or = N processing independently the same deterministic signal, we prove a functional central limit theorem for the pooled spike train collected from the N neurons. This pooled spike train allows to recover the deterministic signal, up to some shape transformation which is explicit.

Action Potentials↗