Perceptual memory drives learning of retinotopic biases for bistable stimuli.

The visual system exploits past experience at multiple timescales to resolve perceptual ambiguity in the retinal image. For example, perception of a bistable stimulus can be biased toward one interpretation over another when preceded by a brief presentation of a disambiguated version of the stimulus (positive priming) or through intermittent presentations of the ambiguous stimulus (stabilization). Similarly, prior presentations of unambiguous stimuli can be used to explicitly "train" a long-lasting association between a percept and a retinal location (perceptual association). These phenonema have typically been regarded as independent processes, with short-term biases attributed to perceptual memory and longer-term biases described as associative learning. Here we tested for interactions between these two forms of experience-dependent perceptual bias and demonstrate that short-term processes strongly influence long-term outcomes. We first demonstrate that the establishment of long-term perceptual contingencies does not require explicit training by unambiguous stimuli, but can arise spontaneously during the periodic presentation of brief, ambiguous stimuli. Using rotating Necker cube stimuli, we observed enduring, retinotopically specific perceptual biases that were expressed from the outset and remained stable for up to 40 min, consistent with the known phenomenon of perceptual stabilization. Further, bias was undiminished after a break period of 5 min, but was readily reset by interposed periods of continuous, as opposed to periodic, ambiguous presentation. Taken together, the results demonstrate that perceptual biases can arise naturally and may principally reflect the brain's tendency to favor recent perceptual interpretation at a given retinal location. Further, they suggest that an association between retinal location and perceptual state, rather than a physical stimulus, is sufficient to generate long-term biases in perceptual organization

Distance-dependent Electron Hopping Conductivity and Nanoscale Lithography of Chemically-linked Gold Monolayer Protected Cluster Films

Films of monolayer protected Au clusters (MPCs) with mixed alkanethiolate and ω-carboxylate alkanethiolate monolayers, linked together by carboxylate–Cu2+–carboxylate bridges, exhibit average edge-to-edge cluster spacings that vary with the numbers of methylene segments in the alkanethiolate ligand as determined by a combined atomic force microscopy (AFM)/UV-Vis spectroscopy method. The electronic conductivity (σEL) of dry films is exponentially dependent on the cluster spacing, consistent with electron tunneling through the alkanethiolate chains and non-bonded contacts between those chains on individual, adjacent MPCs. The calculated electronic coupling factor (β) for tunneling between MPCs is 1.2 Å−1, which is similar to other values obtained for tunneling through hydrocarbon chains. Electron transfer rate constants measured on the films reflect the increased cluster–cluster tunneling distance with increasing chainlength. The MPC films are patterned by scanning the surface with an AFM or scanning tunneling microscopy (STM) tip under appropriate conditions. The patterning mechanism is physical in nature, where the tip scrapes away the film in the scanned region. Large forces are required to pattern films with AFM while normal imaging conditions are sufficient to produce patterns with STM. Patterns with dimensions as small as 100 nm are shown. Subsequent heating (300 °C) of the patterned surfaces leads to a metallic Au film that decreases in thickness and is smoother compared to the MPC film, but retains the initial shape and dimensions of the original pattern

Reducing multiphoton ionization in a linearly polarized microwave field by local control

We present a control procedure to reduce the stochastic ionization of hydrogen atom in a strong microwave field by adding to the original Hamiltonian a comparatively small control term which might consist of an additional set of microwave fields. This modification restores select invariant tori in the dynamics and prevents ionization. We demonstrate the procedure on the one-dimensional model of microwave ionization.Comment: 8 page

Plant roots steer resilience to perturbation of river floodplains

Freshwater ecosystems along river floodplains host among the greatest biodiversity on Earth and are known to respond to anthropic pressure. For water impounded systems, resilience to changes in the natural flow regime is believed to be bi-directional. Whether such resilience prevents the system from returning to pristine conditions after the flow regime changes reverse is as yet unclear, though widely documented. In this work we show that temporal irreversibility of river floodplains to recover their status may be explained by the dynamics of riparian water-tolerant plant roots. Our model is a quantitative tool that will benefit scientists and practitioners in predicting the impact of changing flow regimes on long-term river floodplain dynamics

Reply to Comment on "Criterion that Determines the Foldability of Proteins"

We point out that the correlation between folding times and $\sigma = (T_{\theta } - T_{f})/T_{\theta }$ in protein-like heteropolymer models where $T_{\theta }$ and $T_{f}$ are the collapse and folding transition temperatures was already established in 1993 before the other presumed equivalent criterion (folding times correlating with $T_{f}$ alone) was suggested. We argue that the folding times for these models show no useful correlation with the energy gap even if restricted to the ensemble of compact structures as suggested by Karplus and Shakhnovich (cond-mat/9606037).Comment: 6 pages, Latex, 2 Postscript figures. Plots explicitly showing the lack of correlation between folding time and energy gap are adde

The effect of parallel static and microwave electric fields on excited hydrogen atoms

Motivated by recent experiments we analyse the classical dynamics of a hydrogen atom in parallel static and microwave electric fields. Using an appropriate representation and averaging approximations we show that resonant ionisation is controlled by a separatrix, and provide necessary conditions for a dynamical resonance to affect the ionisation probability. The position of the dynamical resonance is computed using a high-order perturbation series, and estimate its radius of convergence. We show that the position of the dynamical resonance does not coincide precisely with the ionisation maxima, and that the field switch-on time can dramatically affect the ionisation signal which, for long switch times, reflects the shape of an incipient homoclinic. Similarly, the resonance ionisation time can reflect the time-scale of the separatrix motion, which is therefore longer than conventional static field Stark ionisation. We explain why these effects should be observed in the quantum dynamics. PACs: 32.80.Rm, 33.40.+f, 34.10.+x, 05.45.Ac, 05.45.MtComment: 47 pages, 20 figure

Ideally embedded space-times

Due to the growing interest in embeddings of space-time in higher-dimensional spaces we consider a specific type of embedding. After proving an inequality between intrinsically defined curvature invariants and the squared mean curvature, we extend the notion of ideal embeddings from Riemannian geometry to the indefinite case. Ideal embeddings are such that the embedded manifold receives the least amount of tension from the surrounding space. Then it is shown that the de Sitter spaces, a Robertson-Walker space-time and some anisotropic perfect fluid metrics can be ideally embedded in a five-dimensional pseudo-Euclidean space.Comment: layout changed and typos corrected; uses revtex

Folding, Design and Determination of Interaction Potentials Using Off-Lattice Dynamics of Model Heteropolymers

We present the results of a self-consistent, unified molecular dynamics study of simple model heteropolymers in the continuum with emphasis on folding, sequence design and the determination of the interaction parameters of the effective potential between the amino acids from the knowledge of the native states of the designed sequences.Comment: 8 pages, 3 Postscript figures, uses RevTeX. Submitted to Physical Review Letter

Geometry of River Networks I: Scaling, Fluctuations, and Deviations

This article is the first in a series of three papers investigating the detailed geometry of river networks. Large-scale river networks mark an important class of two-dimensional branching networks, being not only of intrinsic interest but also a pervasive natural phenomenon. In the description of river network structure, scaling laws are uniformly observed. Reported values of scaling exponents vary suggesting that no unique set of scaling exponents exists. To improve this current understanding of scaling in river networks and to provide a fuller description of branching network structure, we report here a theoretical and empirical study of fluctuations about and deviations from scaling. We examine data for continent-scale river networks such as the Mississippi and the Amazon and draw inspiration from a simple model of directed, random networks. We center our investigations on the scaling of the length of sub-basin's dominant stream with its area, a characterization of basin shape known as Hack's law. We generalize this relationship to a joint probability density and show that fluctuations about scaling are substantial. We find strong deviations from scaling at small scales which can be explained by the existence of linear network structure. At intermediate scales, we find slow drifts in exponent values indicating that scaling is only approximately obeyed and that universality remains indeterminate. At large scales, we observe a breakdown in scaling due to decreasing sample space and correlations with overall basin shape. The extent of approximate scaling is significantly restricted by these deviations and will not be improved by increases in network resolution.Comment: 16 pages, 13 figures, Revtex4, submitted to PR

Geometry of River Networks II: Distributions of Component Size and Number

The structure of a river network may be seen as a discrete set of nested sub-networks built out of individual stream segments. These network components are assigned an integral stream order via a hierarchical and discrete ordering method. Exponential relationships, known as Horton's laws, between stream order and ensemble-averaged quantities pertaining to network components are observed. We extend these observations to incorporate fluctuations and all higher moments by developing functional relationships between distributions. The relationships determined are drawn from a combination of theoretical analysis, analysis of real river networks including the Mississippi, Amazon and Nile, and numerical simulations on a model of directed, random networks. Underlying distributions of stream segment lengths are identified as exponential. Combinations of these distributions form single-humped distributions with exponential tails, the sums of which are in turn shown to give power law distributions of stream lengths. Distributions of basin area and stream segment frequency are also addressed. The calculations identify a single length-scale as a measure of size fluctuations in network components. This article is the second in a series of three addressing the geometry of river networks.Comment: 16 pages, 13 figures, 4 tables, Revtex4, submitted to PR