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PubMed2005

The dual klepsydra model of internal time representation and time reproduction.

We present a model of the internal representation and reproduction of temporal durations, the 'dual klepsydra' model (DKM). Unlike most contemporary models operating on a 'pacemaker-counter' scheme, the DKM does not assume an oscillatory process as the internal time-base. It is based on irreversible, dissipative processes in inflow/outflow systems (leaky klepsydrae), whose states are continuously compared; if their states are equal, durations are subjectively perceived as equal. Model-based predictions fit experimental time reproduction data with good accuracy, and show qualitative features not accounted for by other models. The deterministic model is characterized by two parameters, kappa (outflow rate coefficient) and eta (ratio of inflow rates). A stochastic version of the model (SDKM) assumes randomly fluctuating inflows, involves two more parameters, and accounts for intra-individual variance of reproduced durations. Analysis of the SDKM leads to non-trivial problems in the stochastic theory, briefly sketched here. Methods of parameter estimation for both deterministic and stochastic versions are given. Applying the DKM to the subjective experience of time passage, we show how subjective measure of elapsed time is constituted. Finally, essential features of the model and its possible neurophysiological interpretation are discussed.

Animals↗
PubMed1986

Poisson process stimulation of an excitable membrane cable model.

The convergence of multiple inputs within a single-neuronal substrate is a common design feature of both peripheral and central nervous systems. Typically, the result of such convergence impinges upon an intracellularly contiguous axon, where it is encoded into a train of action potentials. The simplest representation of the result of convergence of multiple inputs is a Poisson process; a general representation of axonal excitability is the Hodgkin-Huxley/cable theory formalism. The present work addressed multiple input convergence upon an axon by applying Poisson process stimulation to the Hodgkin-Huxley axonal cable. The results showed that both absolute and relative refractory periods yielded in the axonal output a random but non-Poisson process. While smaller amplitude stimuli elicited a type of short-interval conditioning, larger amplitude stimuli elicited impulse trains approaching Poisson criteria except for the effects of refractoriness. These results were obtained for stimulus trains consisting of pulses of constant amplitude and constant or variable durations. By contrast, with or without stimulus pulse shape variability, the post-impulse conditional probability for impulse initiation in the steady-state was a Poisson-like process. For stimulus variability consisting of randomly smaller amplitudes or randomly longer durations, mean impulse frequency was attenuated or potentiated, respectively. Limitations and implications of these computations are discussed.

Animals↗
PubMed2006

Time dependent neural network models for detecting changes of state in complex processes: applications in earth sciences and astronomy.

A computational intelligence approach is used to explore the problem of detecting internal state changes in time dependent processes; described by heterogeneous, multivariate time series with imprecise data and missing values. Such processes are approximated by collections of time dependent non-linear autoregressive models represented by a special kind of neuro-fuzzy neural network. Grid and high throughput computing model mining procedures based on neuro-fuzzy networks and genetic algorithms, generate: (i) collections of models composed of sets of time lag terms from the time series, and (ii) prediction functions represented by neuro-fuzzy networks. The composition of the models and their prediction capabilities, allows the identification of changes in the internal structure of the process. These changes are associated with the alternation of steady and transient states, zones with abnormal behavior, instability, and other situations. This approach is general, and its sensitivity for detecting subtle changes of state is revealed by simulation experiments. Its potential in the study of complex processes in earth sciences and astrophysics is illustrated with applications using paleoclimate and solar data.

Artificial Intelligence↗
PubMed1994

Reduction of brain noise influence in evoked neuromagnetic source localization using noise spatial correlation.

In magnetoencephalographic measurements, magnetic fields caused by spontaneous brain activities not related to the neural activities under study are often referred to as brain noise. This is because the accuracy in neural source localization is considerably degraded by such spontaneous neuromagnetic fields. This paper reports the experimental results of applying the previously proposed noise covariance method to reducing the degradation caused by brain noise and to improving the accuracy in localizing auditory-evoked neural sources. Firstly we present the results of our experiments using measured brain noise and computer-generated signal fields. These results confirm that the covariance method can, in principle, improve the accuracy of evoked neural source localization. Next, the method was applied to source localization for actual neuromagnetic fields evoked by speech sounds. The results obtained strongly suggest that the method is effective in processing actual evoked neuromagnetic data.

Adult↗
PubMed1992

Epidemiologic mapping using the "kriging" method: application to an influenza-like illness epidemic in France.

This paper presents the application of a technique from the earth sciences, the "kriging" method, to the field of geographic epidemiology. Both the principles of the method and the basic equations are given. A key advantage of the method is that it relies on an analysis of the spatial variability of the data and allows the representation of the variable under study as a continuous process throughout a country. Application of the kriging method to the geographic distribution of an epidemic of influenza-like illness in France is discussed.

Epidemiologic Methods↗
PubMed2006

Bayesian restoration using a new nonstationary edge-preserving image prior.

In this paper, we propose a class of image restoration algorithms based on the Bayesian approach and a new hierarchical spatially adaptive image prior. The proposed prior has the following two desirable features. First, it models the local image discontinuities in different directions with a model which is continuous valued. Thus, it preserves edges and generalizes the on/off (binary) line process idea used in previous image priors within the context of Markov random fields (MRFs). Second, it is Gaussian in nature and provides estimates that are easy to compute. Using this new hierarchical prior, two restoration algorithms are derived. The first is based on the maximum a posteriori principle and the second on the Bayesian methodology. Numerical experiments are presented that compare the proposed algorithms among themselves and with previous stationary and non stationary MRF-based with line process algorithms. These experiments demonstrate the advantages of the proposed prior.

Algorithms↗
PubMed2004

Characterization of aqueous and solid inclusion complexes of diuron and isoproturon with beta-cyclodextrin.

The interaction of diuron and isoproturon herbicides with beta-cyclodextrin is conducive to the formation of inclusion compounds in aqueous solution as well as in the solid state. The physico-chemical study of these complexes was carried out by various analytical techniques such as ultraviolet (UV), Fourier transform infrared (FT-IR), Raman, X-ray diffraction, and 1H-NMR (nuclear magnetic resonance) spectroscopies. The existence of inclusion complexes in water solution between the beta-cyclodextrin and each of the herbicides was revealed by electronic absorption and 1H-NMR spectroscopies. A 1:1 stoichiometry was determined for both complexes in aqueous medium from UV absorption spectra by using the Benesi-Hildebrand method; the relative stability constants at room temperature were calculated at 2700 +/- 300 L mol(-1) and 750 +/- 50 L mol(-1) for isoproturon and diuron, respectively. In the solid state, inclusion processes with beta-cyclodextrin were characterized by means of infrared and Raman techniques and confirmed by X-ray diffraction spectra.

Cyclodextrins↗
PubMedDate not supplied

[Does DNA alone determine the development of the organism? (the information aspect of the problem)].

Two closely related controversial problems are discussed: whether the developmental processes can be reduced to the synthesis of polypeptides encoded in DNA, and whether the information in DNA is equivalent to that in the adult organism. Critically considered are the ideas that DNA is only responsible for the protein synthesis, whereas morphogenesis proceeds independently and according to epigenetic regularities of its own. It is stated that development is the realization of genetic information in which more elementary (molecular) processes unambiguously determine a more complex cellular level which in its turn determines morphogenesis of tissues and organs. Various mechanisms of the appearance of new information in the course of development are considered. The statement is made that new information concerns only some individual characters of the organism, whereas most of information that determines the process of development and the structure of the adult organism is created in the course of evolution, is stored in DNA and inherited.

Animals↗
PubMed1996

An application of a marked point process in pre-clinical medicine.

Several authors have employed marked point processes to model complex survival time data. In this paper it is proposed to illustrate further the flexibility of marked point processes by using such a framework to model pre-clinical data which comprise survival times accompanied by ordinal outcomes.

Adrenal Glands↗
PubMed2005

Transient information flow in a network of excitatory and inhibitory model neurons: role of noise and signal autocorrelation.

We investigate the performance of sparsely-connected networks of integrate-and-fire neurons for ultra-short term information processing. We exploit the fact that the population activity of networks with balanced excitation and inhibition can switch from an oscillatory firing regime to a state of asynchronous irregular firing or quiescence depending on the rate of external background spikes. We find that in terms of information buffering the network performs best for a moderate, non-zero, amount of noise. Analogous to the phenomenon of stochastic resonance the performance decreases for higher and lower noise levels. The optimal amount of noise corresponds to the transition zone between a quiescent state and a regime of stochastic dynamics. This provides a potential explanation of the role of non-oscillatory population activity in a simplified model of cortical micro-circuits.

Action Potentials↗
PubMed1993

The joint distribution of patterns in random sequences with application to the RC-measure for expressivity.

A method was previously developed for computation of pattern probabilities in random sequences under Markov chain models. We extend this method to the calculation of the joint distribution for two patterns. An application yields the distribution of the right choice measure for expressivity and how significance bounds depend on sequence length. These bounds are used to show that the choice of pyrimidine in codon position 3 of Escherichia coli genes deviates considerably from a general Markov process model for coding regions. We also derive some statistical evidence that this significant deviation is limited to codon position 3.

Algorithms↗
PubMedDate not supplied

Psychiatric admissions and choice of abortion.

A statistical analysis is presented of the intensities of admissions to psychiatric hospitals among women in Denmark who either gave birth to a child in the year 1975 or had an induced abortion in the same year. The models used are time-continuous Markov and semi-Markov processes, and the methods employed include non-parametric and semi-parametric analysis of counting processes. The influence of prior psychiatric admissions on the choice of terminating the pregnancy with an induced abortion is also studied.

Abortion, Induced↗
PubMed2000

Dynamics of prey moving through a predator field: a model of migrating juvenile salmon.

The migration of a patch of prey through a field of relatively stationary predators is a situation that occurs frequently in nature. Making quantitative predictions concerning such phenomena may be difficult, however, because factors such as the number of the prey in the patch, the spatial length and velocity of the patch, and the feeding rate and satiation of the predators all interact in a complex way. However, such problems are of great practical importance in many management situations; e.g., calculating the mortality of juvenile salmon (smolts) swimming down a river or reservoir containing many predators. Salmon smolts often move downstream in patches short compared with the length of the reservoir. To take into account the spatial dependence of the interaction, we used a spatially-explicit, individual-based modeling approach. We found that the mortality of prey depends strongly on the number of prey in the patch, the downstream velocity of prey in the patch, and the dispersion or spread of the patch in size through time. Some counterintuitive phenomena are predicted, such as predators downstream capturing more prey per predator than those upstream, even though the number of prey may be greatly depleted by the time the prey patch reaches the downstream predators. Individual-based models may be necessary for complex spatial situations, such as salmonid migration, where processes such as schooling occur at fine scales and affect system predictions. We compare some results to predictions from other salmonid models.

Animals↗
PubMed2005

Effects of body composition and leisure-time physical activity on transitions in physical functioning in the elderly.

Physical activity and body composition were examined with respect to variation in functional limitation over a 6-year period (four surveys conducted between 1994 and 2000) based on a cohort of 1,655 community-dwelling older women and men living in Sonoma, California. Measures of functional limitation and physical activity were based on standard self-report questions. Measures of body composition (lean mass, fat mass) were estimated from bioelectric impedance by using population-specific prediction equations derived from dual-energy x-ray absorptiometry. For women, a one-unit gain in lean mass:fat mass ratio reduced the report of limitation at all surveys 65.5% (95% confidence interval: 21.8, 87.4). A similar reduction was not observed for men; however, there was a 3% increase in the report of no limitation at any survey. The effect of high levels of physical activity reduced new functional limitation that occurred at the last survey by 36.8% (95% confidence interval: 0.0, 92.2) for men and 52.7% (95% confidence interval: 13.5, 91.9) for women. In summary, higher levels of physical activity appeared to reduce the risk of future functional limitation conditional on the level of functioning established early in the disablement process by lean mass:fat mass ratio.

Absorptiometry, Photon↗
PubMed2005

Image analysis for cDNA microarrays.

OBJECTIVES: We characterize typical problems encountered in microarray image analysis and present algorithmic approaches dealing with background estimation, spot identification and intensity extraction. Validation of the quality of resulting measurements is discussed. METHODS: We describe sources for errors in microarray images and present algorithms that have been specifically developed to deal with such experimental imperfections. RESULTS: For the image analysis of hybridization experiments, discriminating spot regions from a background is the most critical step. Spot shape detection algorithms, intensity histogram methods and hybrid approaches have been proposed. The correctness of final intensity estimates is difficult to verify. Nevertheless, the application of sophisticated algorithms provides a significant reduction of the possible information loss. CONCLUSIONS: The initial analysis step for array hybridization experiments is the estimation of expression intensities. The quality of this process is crucial for the validity of interpretations from subsequent analysis steps.

Algorithms↗
PubMed2002

Image registration: an essential tool for nuclear medicine.

There is increasing interest in being able to automatically register medical images from either the same or different modalities. Registered images are proving useful in a range of applications, not only providing more correlative information to aid in diagnosis, but also assisting with the planning and monitoring of therapy, both surgery and radiotherapy. The practising nuclear medicine specialist is faced with a dilemma in choosing an appropriate method since the literature in the field is extensive, with conflicting evidence as to what methods are optimal. Although most barriers to implementing registration in routine practice have been removed, there remains a lack of commercial, validated software. The alternative is to install a dual-modality instrument. The objective of this review is to present a general overview of medical image registration with emphasis on the application and issues relevant to nuclear medicine.

Algorithms↗
PubMed2001

Perceiving visual expansion without optic flow.

When an observer moves forward in the environment, the image on his or her retina expands. The rate of this expansion conveys information about the observer's speed and the time to collision. Psychophysical and physiological studies have provided abundant evidence that these expansionary motions are processed by specialized mechanisms in mammalian visual systems. It is commonly assumed that the rate of expansion is estimated from the divergence of the optic-flow field (the two-dimensional field of local translational velocities). But this rate might also be estimated from changes in the size (or scale) of image features. To determine whether human vision uses such scale-change information, we have synthesized stochastic texture stimuli in which the scale of image elements increases gradually over time, while the optic-flow pattern is random. Here we show, using these stimuli, that observers can estimate expansion rates from scale-change information alone, and that pure scale changes can produce motion after-effects. These two findings suggest that the visual system contains mechanisms that are explicitly sensitive to changes in scale.

Adaptation, Ocular↗
PubMed2006

Harnessing microtubule dynamic instability for nanostructure assembly.

Intracellular molecular machines synthesize molecules, tear apart others, transport materials, transform energy into different forms, and carry out a host of other coordinated processes. Many molecular processes have been shown to work outside of cells, and the idea of harnessing these molecular machines to build nanostructures is attractive. Two examples are microtubules and motor proteins, which aid cell movement, help determine cell shape and internal structure, and transport vesicles and organelles within the cell. These molecular machines work in a stochastic, noisy fashion: microtubules switch randomly between growing and shrinking in a process known as dynamic instability; motor protein movement along microtubules is randomly interrupted by the motor proteins falling off. A common strategy in attempting to gain control over these highly dynamic, stochastic processes is to eliminate some processes (e.g., work with stabilized microtubules) in order to focus on others (interaction of microtubules with motor proteins). In this paper, we illustrate a different strategy for building nanostructures, which, rather than attempting to control or eliminate some dynamic processes, uses them to advantage in building nanostructures. Specifically, using stochastic agent-based simulations, we show how the natural dynamic instability of microtubules can be harnessed in building nanostructures, and discuss strategies for ensuring that "unreliable" stochastic processes yield a robust outcome.

Binding Sites↗