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PubMed1996

A method for checking regression models in survival analysis based on the risk score.

We propose to perform model check for the Cox and Aalen regression models using martingale residual processes grouped after the risk score. Asymptotic distributions of the grouped martingale residual processes are deduced, so both formal and graphical model check can be performed. The method is validated by stochastic simulation. A data example with patients with primary biliary cirrhosis of the liver is discussed.

Humans↗
PubMed2000

A B-cell receptor-specific selection step governs immature to mature B cell differentiation.

Seventy percent of peripheral immature conventional (B2) B cells fail to develop into mature B cells. The nature of this cell loss has not been characterized; the process that governs which immature B cells develop into long-lived peripheral B cells could be either stochastic or selective. Here, we demonstrate that this step is in fact selective, in that the fate of an immature B cell is highly dependent on its Ig receptor specificity. A significant skewing of the B cell receptor repertoire occurs by the time cells enter the mature B cell fraction, which indicates that there is selection of only a minority of immature B cells to become mature B cells. Because only a few heavy-light chain pairs are enhanced of the diverse available repertoire, we favor the idea that selection is positive for these few heavy-light chain pairs rather than negative against nearly all others. Because most immature B cells are lost at this transition, this putative positive selection event is likely to be a major force shaping the mature B cell receptor repertoire available for adaptive immune responses.

Animals↗
PubMed2004

Analysis of sleep-stage characteristics in full-term newborns by means of spectral and fractal parameters.

STUDY OBJECTIVES: In this work, we studied the behavior of the fractal dimension during each of the neonatal electroencephalogram (EEG) sleep phases and during the awake state, comparing the results with those of the classical spectral parameters and with zero crossing values. DESIGN: Fractal dimension, zero crossing, and spectral parameters of the EEG bands were determined for each 2-second frame of the EEG sleep-time series. Eight channels of each EEG recording were examined. PARTICIPANTS: Twenty healthy full-term newborns (10 boys and 10 girls) with normal psychomotor development evaluated at 24 and 36 months of age, were chosen to participate in this study. MEASUREMENTS AND RESULTS: Fractal analysis showed that where rhythmic and regular activity are present, as during quiet sleep, the fractal dimension is low and rises when bioelectric activity is more variable and complex, reaching its maximum value during wakefulness. The discriminative value of this parameter was similar to that of some spectral bands. CONCLUSIONS: This work was an initial attempt to apply techniques derived from the nonlinear deterministic studies used to evaluate system complexity, to the neonatal EEG, in order to acquire a normative database that can be used as a reference in neurological pathologies. Fractal dimension alone or together with zero crossing and theta and delta bands could be used for computerized discrimination of neonatal EEG sleep phases.

Cerebral Cortex↗
PubMed2003

Practical algorithm for reducing convex spike noises on a spectrum.

Quantitative data analysis and high-sensitivity measurements by use of Raman and infrared spectroscopy often suffer from noisy spikes such as those due to cosmic rays and water vapor. Since these spikes are unidirectional and isolated, the conventional smoothing techniques do a poor job of removing them. However, a small modification can improve these smoothing techniques significantly. In this paper, we present a simple denoising technique for a single-scan spectrum that is corrupted by convex spikes. In general, the noisy spikes arising from cosmic rays or water vapor have a much narrower bandwidth compared with target "informative" bands in Raman and infrared spectra. This means that these noisy spikes can be separated from the target bands by means of the difference in the bandwidths. The proposed method employs the moving window averaging procedure to distinguish and separate the convex spike. The proposed algorithm allows us to take away the convex spikes from measured spectra without preparing multiply recorded spectra and (much) biasing the measured spectrum.

Acetamides↗
PubMed2000

Sensitivity analysis in quantitative microbial risk assessment.

The occurrence of foodborne disease remains a widespread problem in both the developing and the developed world. A systematic and quantitative evaluation of food safety is important to control the risk of foodborne diseases. World-wide, many initiatives are being taken to develop quantitative risk analysis. However, the quantitative evaluation of food safety in all its aspects is very complex, especially since in many cases specific parameter values are not available. Often many variables have large statistical variability while the quantitative effect of various phenomena is unknown. Therefore, sensitivity analysis can be a useful tool to determine the main risk-determining phenomena, as well as the aspects that mainly determine the inaccuracy in the risk estimate. This paper presents three stages of sensitivity analysis. First, deterministic analysis selects the most relevant determinants for risk. Overlooking of exceptional, but relevant cases is prevented by a second, worst-case analysis. This analysis finds relevant process steps in worst-case situations, and shows the relevance of variations of factors for risk. The third, stochastic analysis, studies the effects of variations of factors for the variability of risk estimates. Care must be taken that the assumptions made as well as the results are clearly communicated. Stochastic risk estimates are, like deterministic ones, just as good (or bad) as the available data, and the stochastic analysis must not be used to mask lack of information. Sensitivity analysis is a valuable tool in quantitative risk assessment by determining critical aspects and effects of variations.

Animals↗
PubMed1998

Note on the non-homogeneous Prendiville process.

By creating an auxiliary process, this note obtains complete solution to the distribution of the non-homogeneous Prendiville process. In addition, an error in the literature of the original Prendiville process is corrected.

Birth Rate↗
PubMed1992

Chaotic dynamics in autonomic nervous system activity of a patient during a psychotherapy session.

Chaos theory and nonlinear dynamical modeling have been applied successfully in a variety of scientific fields ranging from the physical sciences to population biology. More recently, investigators have modeled long-term psychological processes by applying this paradigm to subjective measures. Yet, mathematically rigorous dynamical modeling of transient psychodynamic processes remains uncharted. Human behaviors and intrapsychic processes often defy prediction, yet psychodynamic theory views these as fundamentally deterministic. We postulate that a nonlinear dynamical analysis of mental states and mental control processes may help reconcile the paradox that seemingly random mental states are thought ultimately to result from deterministic, rather than stochastic, psychological processes. As an initial empirical approach, we examined spontaneously occurring autonomic activity of a patient during 1 hr of psychotherapy and illustrate that cardiac responses associated with psychologically meaningful events possess nonlinear characteristics indicative of chaos. Such nonlinear analyses may shed light on fundamental issues of psychological functioning.

Adult↗
PubMed2006

Emotional task-dependent low-frequency fluctuations and methylphenidate: Wavelet scaling analysis of 1/f-type fluctuations in fMRI of the cerebellar vermis.

UNLABELLED: Ion channel currents, neural firing patterns, and brain BOLD signals display 1/f-type fluctuations or fractal properties in time. By design, fMRI methods attempt to minimize the contribution of variance from low-frequency physiological 1/f-noise. New fMRI methods are described to visualize and measure 1/f-type BOLD fluctuations in volunteers recalling affectively neutral or emotional memories or meditating (i.e., attending to breathing) then retrospectively rating emotional content. A wavelet scaling exponent (alpha) was used to characterize signals from 0.015625 to 0.5Hz in cerebellar lobules VIII to X of the vermis (posterior inferior vermis; PIV), a region coordinating balance, eye tracking, locomotion, and vascular tone, and a possible site of pathology in attention deficit hyperactivity disorder (ADHD). RESULTS: Changes in alpha and emotional measures were correlated in PIV voxels (r = 0.622, d.f .= 14, P < 0.0005), but not other regions examined. In contrast, conventional means and standard deviations of PIV voxels were unchanged. Methylphenidate, shown to decrease slow oscillations in rodent basal ganglia [Ruskin DN, Bergstrom DA, Shenker A, Freeman LE, Baek D, Walters JR. Drugs used in the treatment of attention-deficit/hyperactivity disorder affect postsynaptic firing rate and oscillation without preferential dopamine autoreceptor action. Biol Psychiatry 2001;49:340-50.], abolished task-dependent alpha changes in the PIV of an adult with ADHD. Wavelet analysis of long BOLD time series appears well suited to fractal physiology and studies of pharmacologically modulated cerebellar-thalamic-cortical function in ADHD or other psychiatric disorders.

Adult↗
PubMed2002

A computer system for acoustic analysis of pathological voices and laryngeal diseases screening.

A system for acoustic analysis of pathological voices is proposed. The vocalized part of the voice signal is separated and all glottal cycles are traced by means of a cross-correlation detector. Based on the so determined beginning and duration of all glottal cycles, shimmer, jitter, several harmonics-to-noise ratios and other widely used acoustic parameters are calculated. New parameters are also introduced for estimation of the turbulent noise in voice signals (Turbulent Noise Index - TNI) and for the "breathy" voice characterization (Normalized First Harmonic Energy - NFHE). These parameters are applied for laryngeal pathology detection. An identification accuracy of 96.1% by the K-nearest neighbors' method has been achieved. The system is clinically tested.

Algorithms↗
PubMed2005

Local signaling with molecular diffusion as a decoder of Ca2+ signals in synaptic plasticity.

Synaptic plasticity is induced by the influx of calcium ions (Ca2+) through N-methyl-D-aspartate receptors (NMDARs), and the direction and strength of the response depend on the frequency of the synaptic inputs. Recent studies have shown that the direction of synaptic plasticity is also governed by two distinct NMDAR subtypes (NR1/NR2A, NR1/NR2B). How are the different types of regulation (frequency-dependent and receptor-specific) processed simultaneously? To clarify the molecular basis of this dual dependence of synaptic plasticity, we have developed a mathematical model of spatial Ca2+ signaling in a dendritic spine. Our simulations revealed that calmodulin (CaM) activation in the vicinity of NMDARs is strongly affected by the diffusion coefficient of CaM itself, and that this 'local CaM diffusion system' works as a dual decoder of both the frequency of Ca2+ influxes and their postsynaptic current shapes, generated by two NMDAR subtypes, implying that spatial factors may underlie the complicated regulation scheme of synaptic plasticity.

Animals↗
PubMed2006

Optimal representation of sensory information by neural populations.

Sensory information is encoded by populations of neurons. The responses of individual neurons are inherently noisy, so the brain must interpret this information as reliably as possible. In most situations, the optimal strategy for decoding the population signal is to compute the likelihoods of the stimuli that are consistent with an observed neural response. But it has not been clear how the brain can directly compute likelihoods. Here we present a simple and biologically plausible model that can realize the likelihood function by computing a weighted sum of sensory neuron responses. The model provides the basis for an optimal decoding of sensory information. It explains a variety of psychophysical observations on detection, discrimination and identification, and it also directly predicts the relative contributions that different sensory neurons make to perceptual judgments.

Animals↗
PubMed1999

Noise power spectra of images from digital mammography detectors.

Noise characterization through estimation of the noise power spectrum (NPS) is a central component of the evaluation of digital x-ray systems. We begin with a brief review of the fundamentals of NPS theory and measurement, derive explicit expressions for calculation of the one- and two-dimensional (1D and 2D) NPS, and discuss some of the considerations and tradeoffs when these concepts are applied to digital systems. Measurements of the NPS of two detectors for digital mammography are presented to illustrate some of the implications of the choices available. For both systems, two-dimensional noise power spectra obtained over a range of input fluence exhibit pronounced asymmetry between the orthogonal frequency dimensions. The 2D spectra of both systems also demonstrate dominant structures both on and off the primary frequency axes indicative of periodic noise components. Although the two systems share many common noise characteristics, there are significant differences, including markedly different dark-noise magnitudes, differences in NPS shape as a function of both spatial frequency and exposure, and differences in the natures of the residual fixed pattern noise following flat fielding corrections. For low x-ray exposures, quantum noise-limited operation may be possible only at low spatial frequency. Depending on the method of obtaining the 1D NPS (i.e., synthetic slit scanning or slice extraction from the 2D NPS), on-axis periodic structures can be misleadingly smoothed or missed entirely. Our measurements indicate that for these systems, 1D spectra useful for the purpose of detective quantum efficiency calculation may be obtained from thin cuts through the central portion of the calculated 2D NPS. On the other hand, low-frequency spectral values do not converge to an asymptotic value with increasing slit length when 1D spectra are generated using the scanned synthetic slit method. Aliasing can contribute significantly to the digital NPS, especially near the Nyquist frequency. Calculation of the theoretical presampling NPS and explicit inclusion of aliased noise power shows good agreement with measured values.

Biophysics↗
PubMed2003

Improved neural representation of vowels in electric stimulation using desynchronizing pulse trains.

Current cochlear implant processors poorly represent sound waveforms in the temporal discharge patterns of auditory-nerve fibers (ANFs). A previous study [Litvak et al., J. Acoust. Soc. Am. 114, 2079-2098 (2003)] showed that the temporal representation of sinusoidal stimuli can be improved in a majority of ANFs by encoding the stimuli as small modulations of a sustained, high-rate (5 kpps), desynchronizing pulse train (DPT). Here, these findings are extended to more complex stimuli by recording ANF responses to pulse trains modulated by bandpass filtered vowels. Responses to vowel modulators depended strongly on the discharge pattern evoked by the unmodulated DPT. ANFs that gave sustained responses to the DPT had period histograms that resembled the modulator waveform for low (< 5%) modulation depths. Spectra of period histograms contained peaks near the formant frequencies. In contrast, ANFs that gave a transient (< 1 min) response to the DPT poorly represented the formant frequencies. A model incorporating a linear modulation filter, a noisy threshold, and neural refractoriness predicts the shapes of period histograms for both types of fibers. These results suggest that a DPT-enhanced strategy may achieve good representation of the stimulus fine structure in the temporal discharge patterns of ANFs for frequencies up to 1000 Hz. It remains to be seen whether these temporal discharge patterns can be utilized by cochlear implant subjects.

Animals↗
PubMed1992

Simulation of a diffusion process with randomly distributed jumps in neuronal context.

In stochastic neuronal models, an interspike interval corresponds to the time interval during which the process imitating the membrane potential reaches a threshold from an initial depolarization. For neurons with an extensive dendritic structure, a stochastic process combining diffusion and discontinuous development of its trajectory is considered a good description of the membrane potential. Due to a lack of analytical solutions of the threshold passage distribution for such a process, a method for computer simulation is introduced here. For the diffusion Ornstein-Uhlenbeck process with exponentially distributed moments of constant jumps a program is given. The relation between the simulation step, accuracy of simulation and amount of computing time required is discussed.

Computer Simulation↗
PubMed1996

Collective epidemic models.

A number of models have been proposed to describe the spread of infectious diseases of the S-I-R type. Most of them account for variable infectivity levels, and very few incorporate variable susceptibility levels. In the present work, a new epidemic model, called a collective model, is constructed that combines both variabilities in a general way. It is then established how to determine the exact distribution of the final state and the severity of the epidemic when the infection process stops.

Communicable Diseases↗
PubMed2005

Estimating the life-span of oligodendrocytes from clonal data on their development in cell culture.

This paper presents a new method to analyze clonal data on oligodendrocyte development in cell culture. The process of oligodendrocyte generation from precursor cells is modelled as a multi-type Bellman-Harris branching process as suggested in an earlier paper [K. Boucher, A. Zorin, A.Y. Yakovlev, M. Mayer-Proschel, M. Noble, An alternative stochastic model of generation of oligodendrocytes in cell culture, J. Math. Biol. 43 (2001) 22]. This model has been extended to allow for death of oligodendrocytes as well as a dissimilar distribution of the first mitotic cycle duration as compared to the subsequent cycles of precursor cells, which lengths are assumed to be independent and identically distributed random variables. Since the time-span of oligodendrocytes is not directly observable in clonal data, plausible parametric assumptions are invoked to make estimation problems tractable. In particular, the time to cell death follows a two-parameter gamma distribution, while the lapse of time between the event of cell death and the event of cell disintegration is assumed to be exponentially distributed. A simulated pseudo maximum likelihood method for estimation of model parameters has been developed using simulation-based approximations of the expected numbers and variance-covariance matrices for different types of cells. Finite sample properties of the estimation procedure are studied by computer simulations. The proposed method is illustrated with an analysis of the clonal development of O-2A progenitor cells isolated from the rat optic nerve and the corpus callosum.

Animals↗
PubMed2005

Modelling climate change: the role of unresolved processes.

Our understanding of the climate system has been revolutionized recently, by the development of sophisticated computer models. The predictions of such models are used to formulate international protocols, intended to mitigate the severity of global warming and its impacts. Yet, these models are not perfect representations of reality, because they remove from explicit consideration many physical processes which are known to be key aspects of the climate system, but which are too small or fast to be modelled. The purpose of this paper is to give a personal perspective of the current state of knowledge regarding the problem of unresolved scales in climate models. A recent novel solution to the problem is discussed, in which it is proposed, somewhat counter-intuitively, that the performance of models may be improved by adding random noise to represent the unresolved processes.

Climate↗