Effects of set-inducing instructions on recall from dichotic inputs.
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Attention↗
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Results for “Probability Theory”
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Information theory and neural coding.
Information theory quantifies how much information a neural response carries about the stimulus. This can be compared to the information transferred in particular models of the stimulus-response function and to maximum possible information transfer. Such comparisons are crucial because they validate assumptions present in any neurophysiological analysis. Here we review information-theory basics before demonstrating its use in neural coding. We show how to use information theory to validate simple stimulus-response models of neural coding of dynamic stimuli. Because these models require specification of spike timing precision, they can reveal which time scales contain information in neural coding. This approach shows that dynamic stimuli can be encoded efficiently by single neurons and that each spike contributes to information transmission. We argue, however, that the data obtained so far do not suggest a temporal code, in which the placement of spikes relative to each other yields additional information.
Algorithms↗
Molecular simulations for the conformational assessment of a porphyrin-fullerene dyad in different environments.
Conformational space of a porphyrin-fullerene dyad with the donor and acceptor connected by a relatively flexible linker is studied by molecular dynamics simulations in both non-polar and polar solvents, as well as in vacuum. The most probable conformations obtained from the vacuum MD simulations were optimized with semi-empirical (SE) and density functional theory (DFT) methods and the extent of the structural changes is assessed. The computational results indicate the co-existence of different conformers in both polar and nonpolar solvents showing agreement with experimental results. The most probable vacuum conformations at 300 K are similar to the ones at 0 K, while the structures most often observed in the solvents show less compact conformations. Optimization with SE and DFT calculations leads to structures, which represent relatively well the folded conformations in solvent, which validates the electronic structure calculations relevant to describing photoinduced electron-transfer in H2P-O34-C60.
Computer Simulation↗
The bases of speech pathology and audiology: evaluation as the resolution of uncertainty.
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Communication↗
Hidden ethical issues in clinical decision analysis.
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Decision Making↗
Chaos and the evolution of cooperation.
The "iterated prisoner's dilemma" is the most widely used model for the evolution of cooperation in biological societies. Here we show that a heterogeneous population consisting of simple strategies, whose behavior is totally specified by the outcome of the previous round, can lead to persistent periodic or highly irregular (chaotic) oscillations in the frequencies of the strategies and the overall level of cooperation. The levels of cooperation jump up and down in an apparently unpredictable fashion. Small recurrent and simultaneous invasion attempts (caused by mutation) can change the evolutionary dynamics from converging to an evolutionarily stable strategy to periodic oscillations and chaos. Evolution can be twisted away from defection, toward cooperation. Adding "generous tit-for-tat" greatly increases the overall level of cooperation and can lead to long periods of steady cooperation. Since May's paper [May, R. M. (1976) Nature (London) 261, 459-467], "simple mathematical models with very complicated dynamics" have been found in many biological applications, but here we provide an example of a biologically relevant evolutionary game whose dynamics display deterministic chaos. The simulations bear some resemblance to the irregular cycles displayed by the frequencies of host genotypes and specialized parasites in evolutionary "arms races" [Hamilton, W. D., Axelrod, R. & Tanese, R. (1990) Proc. Natl. Acad. Sci. USA 87, 3566-3573; Seger, J. (1988) Philos. Trans. R. Soc. London B 319, 541-555].
Biological Evolution↗
Rapid and accurate estimates of statistical significance for sequence data base searches.
A central question in sequence comparison is the statistical significance of an observed similarity. For local alignment containing gaps to optimize sequence similarity this problem has so far not been solved mathematically. Using as a basis the Chen-Stein theory of Poisson approximation, we present a practical method to approximate the probability that a local alignment score is a result of chance alone. For a set of similarity scores and gap penalties only one simulation of random alignments needs to be calculated to derive the key information allowing us to estimate the significance of any alignment calculated under this setting. We present applications to data base searching and the analysis of pairwise and self-comparisons of proteins.
Algorithms↗
One-parameter item response theory models for psychomotor tests involving repeated, independent attempts.
Three one-parameter item response theory models are given as viable models that describe the observed score probabilities of an examinee who takes a multiple attempts, single-item test of a psychomotor skill. These models include the Binomial Trials Model, the Poisson Counts Model, and the Inverse Binomial Model. The paper presents these models and offers suggestions for their estimation and subsequent use in the assessment of psychomotor behavior.
Bayes Theorem↗
Allowance for heterogeneous stacking in the DNA helix-coil transition theory.
Melting profiles of eight DNA molecules with lengths ranging from 849 to 4362 bp have been measured in an SSC buffer where the melting is an equilibrium process up to complete strand separation. A theoretical analysis shows that the melting profiles depend on only eight invariants that are linear combinations of 10 original stacking parameters. As a result it is impossible to determine the 10 parameters from the melting profiles. The 8 variants have been determined by fitting theoretical profiles to experimental ones for two fragments. Then theoretical and experimental profiles are compared for those 6 fragments that were not used in the fitting procedure. This comparison demonstrates that allowance for heterogeneous stacking considerably improves the agreement between theory and experiment. The values of invariants have proved to be small. This confirms the previous conclusion that heterogeneous stacking interactions produce only small corrections to the major effect of the difference in the mean stabilities of AT and GC pairs. Some discrepancy between theory and experiment that remains after the allowance for heterogeneous stacking is probably due to even finer effects of long-range interactions.
Base Composition↗
Foundations for a theory of collective decisions.
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Decision Making↗
Pathophysiology of the migraine aura. The spreading depression theory.
The characteristic form and development of sensory disturbances during migraine auras suggests that the underlying mechanism is a disturbance of the cerebral cortex, probably the cortical spreading depression (CSD) of Leão. The demonstration of unique changes of brain blood flow during attacks of migraine with aura, which have been replicated in animal experiments during CSD, constitutes another important line of support for the 'spreading depression' theory, which may be a key to an understanding of the migraine attack. Cortical spreading depression is a short-lasting depolarization wave that moves across the cortex at a rate of 3-5 mm/min. A brief phase of excitation heralds the reaction which is immediately followed by prolonged nerve cell depression synchronously with a dramatic failure of brain ion homeostasis, efflux of excitatory amino acids from nerve cells and enhanced energy metabolism. Recent experimental work has shown that CSD in the neocortex of a variety of species including man is dependent on activation of a single receptor, the N-methyl-D-aspartate receptor, one of the three subtypes of glutamate receptors. The combined experimental and clinical studies point to fruitful areas in which to look for migraine treatments of the future and provide a framework within which important aspects of the migraine attack can be modelled.
Cerebral Cortex↗
The changes in genetic and environmental variance with inbreeding in Drosophila melanogaster.
We performed a large-scale experiment on the effects of inbreeding and population bottlenecks on the additive genetic and environmental variance for morphological traits in Drosophila melanogaster. Fifty-two inbred lines were created from the progeny of single pairs, and 90 parent-offspring families on average were measured in each of these lines for six wing size and shape traits, as well as 1945 families from the outbred population from which the lines were derived. The amount of additive genetic variance has been observed to increase after such population bottlenecks in other studies; in contrast here the mean change in additive genetic variance was in very good agreement with classical additive theory, decreasing proportionally to the inbreeding coefficient of the lines. The residual, probably environmental, variance increased on average after inbreeding. Both components of variance were highly variable among inbred lines, with increases and decreases recorded for both. The variance among lines in the residual variance provides some evidence for a genetic basis of developmental stability. Changes in the phenotypic variance of these traits are largely due to changes in the genetic variance.
Animals↗
Self-complexity and the persistence of depression.
Self-complexity, a measure of the structure of cognition involving the self, was used to predict the persistence of depression in patients diagnosed with major depression. Self-descriptions offered by depressed patients were analyzed using a clustering algorithm to model cognitive structure. Indices of positive and negative self-complexity, derived from the resulting models, were used to predict depressive symptomatology 9 months after the onset of a major depression. Negative self-complexity uniquely predicted subsequent levels of depression even after the effects of initial levels of depression, self-evaluation, and dysfunctional attitudes were statistically removed. Highly complex negative self-representation appears to be associated with poor recovery from a major depressive episode. Future studies examining the relationship between cognition and psychopathology should investigate, in addition to its content, the formal and structural properties of cognition.
Adult↗
Anesthesia and the porphyrias.
A simplified classification of the porphyrias is given which is thought to be advantageous to the anesthesiologist in determining those patients who are predisposed to acute attacks. These acute attacks may be precipitated by the administration of barbiturates, but may also be spontaneous. The current theory for the precipitation of the acute attack is described, with the probable mechanism being a decrease in uroporphyrinogen synthetase levels and the resultant interference in heme production. Increased formation of cytochrome P-450 with barbiturates also produces increased levels of delta aminolevulinic acid, which may be a cause of the acute attack. The significance in anesthesia and suggested means of anesthetic management are discussed.
5-Aminolevulinate Synthetase↗
Defense against nuclear weapons: a decision analysis.
Response to the public health threat posed by nuclear weapons is a medical imperative. The United States, in contrast to other nations, has chosen a course that assures maximal casualties in the event of a nuclear attack, on the theory that prevention of the attack is incompatible with preventive measures against its consequences, such as blast injuries and radiation sickness. A decision analysis approach clarifies the risks and benefits of a change to a strategy of preparedness.
Civil Defense↗
Symbolic dynamics of event-related brain potentials.
We apply symbolic dynamics techniques such as word statistics and measures of complexity to nonstationary and noisy multivariate time series of electroencephalograms (EEG) in order to estimate event-related brain potentials (ERP). Their significance against surrogate data as well as between different experimental conditions is tested. These methods are validated by simulations using stochastic dynamical systems with time-dependent control parameters and compared with traditional ERP-analysis techniques. Continuous EEG data are cut into epochs according to stimuli events presented to the subjects. These ensembles of time series can be considered as ensembles of trajectories given by some dynamical systems. We employ a statistical mechanics approach motivated by the Frobenius-Perron equation and apply it to coarse-grained symbolic descriptions of the dynamics. We develop time-dependent measures of complexity founded on running cylinder sets and show that these quantities are able to distinguish simulated data obtained by different control parameters as well as experimental data between different experimental conditions. As a first finding, our approach restores the well-known ERP components and it reveals additionally qualitative changes in the EEG that cannot be detected by means of the traditional techniques. We criticize the prerequisites of the traditional approach to ERP analysis and propose to consider ERP instead in terms of dynamical system theory and information theory.
Brain↗
Statistics of soliton-bearing systems with additive noise.
We present a consistent method to calculate the probability distribution of soliton parameters in systems with additive noise. Even though the noise is weak, we are interested in probabilities of large fluctuations (generally non-Gaussian) which are beyond perturbation theory. Our method is a development of the instanton formalism (method of optimal fluctuation) based on a saddle-point approximation in the path integral. We first solve a fundamental problem of soliton statistics governed by a noisy nonlinear Schrödinger equation. We then apply our method to optical soliton transmission systems using signal control elements (filters and amplitude and phase modulators).
Journal Article↗
Stochastic dynamics in a two-dimensional oscillator near a saddle-node bifurcation.
We study the oscillator equations describing a particular class of nonlinear amplifier, exemplified in this work by a two-junction superconducting quantum interference device. This class of dynamic system is described by a potential energy function that can admit minima (corresponding to stable solutions of the dynamic equations), or "running states" wherein the system is biased so that the potential minima disappear and the solutions display spontaneous oscillations. Just beyond the onset of the spontaneous oscillations, the system is known to show significantly enhanced sensitivity to very weak magnetic signals. The global phase space structure allows us to apply a center manifold technique to approximate analytically the oscillatory behavior just past the (saddle-node) bifurcation and compute the oscillation period, which obeys standard scaling laws. In this regime, the dynamics can be represented by an "integrate-fire" model drawn from the computational neuroscience repertoire; in fact, we obtain an "interspike interval" probability density function and an associated power spectral density (computed via Renewal theory) that agree very well with the results obtained via numerical simulations. Notably, driving the system with one or more time sinusoids produces a noise-lowering injection locking effect and/or heterodyning.
Journal Article↗