A computational approach for genome-wide mapping of splicing factor binding sites

A computational method is presented for genome-wide mapping of splicing factor binding sites that considers both the genomic environment and evolutionary conservation

Episodic synchronization in dynamically driven neurons

We examine the response of type II excitable neurons to trains of synaptic pulses, as a function of the pulse frequency and amplitude. We show that the resonant behavior characteristic of type II excitability, already described for harmonic inputs, is also present for pulsed inputs. With this in mind, we study the response of neurons to pulsed input trains whose frequency varies continuously in time, and observe that the receiving neuron synchronizes episodically to the input pulses, whenever the pulse frequency lies within the neuron's locking range. We propose this behavior as a mechanism of rate-code detection in neuronal populations. The results are obtained both in numerical simulations of the Morris-Lecar model and in an electronic implementation of the FitzHugh-Nagumo system, evidencing the robustness of the phenomenon.Comment: 7 pages, 8 figure

Nonuniversal spectral properties of the Luttinger model

The one electron spectral functions for the Luttinger model are discussed for large but finite systems. The methods presented allow a simple interpretation of the results. For finite range interactions interesting nonunivesal spectral features emerge for momenta which differ from the Fermi points by the order of the inverse interaction range or more. For a simplified model with interactions only within the branches of right and left moving electrons analytical expressions for the spectral function are presented which allows to perform the thermodynamic limit. As in the general spinless model and the model including spin for which we present mainly numerical results the spectral functions do not approach the noninteracting limit for large momenta. The implication of our results for recent high resolution photoemission measurements on quasi one-dimensional conductors are discussed.Comment: 19 pages, Revtex 2.0, 5 ps-figures, to be mailed on reques

Stimulus - response curves of a neuronal model for noisy subthreshold oscillations and related spike generation

We investigate the stimulus-dependent tuning properties of a noisy ionic conductance model for intrinsic subthreshold oscillations in membrane potential and associated spike generation. On depolarization by an applied current, the model exhibits subthreshold oscillatory activity with occasional spike generation when oscillations reach the spike threshold. We consider how the amount of applied current, the noise intensity, variation of maximum conductance values and scaling to different temperature ranges alter the responses of the model with respect to voltage traces, interspike intervals and their statistics and the mean spike frequency curves. We demonstrate that subthreshold oscillatory neurons in the presence of noise can sensitively and also selectively be tuned by stimulus-dependent variation of model parameters.Comment: 19 pages, 7 figure

Transition from regular to complex behaviour in a discrete deterministic asymmetric neural network model

We study the long time behaviour of the transient before the collapse on the periodic attractors of a discrete deterministic asymmetric neural networks model. The system has a finite number of possible states so it is not possible to use the term chaos in the usual sense of sensitive dependence on the initial condition. Nevertheless, at varying the asymmetry parameter, $k$, one observes a transition from ordered motion (i.e. short transients and short periods on the attractors) to a ``complex'' temporal behaviour. This transition takes place for the same value $k_{\rm c}$ at which one has a change for the mean transient length from a power law in the size of the system ($N$) to an exponential law in $N$. The ``complex'' behaviour during the transient shows strong analogies with the chaotic behaviour: decay of temporal correlations, positive Shannon entropy, non-constant Renyi entropies of different orders. Moreover the transition is very similar to that one for the intermittent transition in chaotic systems: scaling law for the Shannon entropy and strong fluctuations of the ``effective Shannon entropy'' along the transient, for $k > k_{\rm c}$.Comment: 18 pages + 6 figures, TeX dialect: Plain TeX + IOP macros (included

Hydration and Ordering of Lamellar Block Copolymer Films under Controlled Water Vapor

Amphiphilic block copolymers within a range of volume fraction spontaneously form vesicles in aqueous solution, where a water core is enclosed by a polymer bilayer. Thin-film rehydration is a method used to produce vesicles routinely; a thin film is immersed in water, the film swells, and vesicles are formed which bleb off from the film surface. We have studied the early stages of hydration for PEO–PBO block copolymer thin films under controlled water vapor conditions to understand this formation mechanism and so enable more efficient ways to encapsulate molecules using this method. Neutron and X-ray measurements show that the initial film exhibits weakly ordered structure with isotropic parallel and vertical orientation; the films initially swell and maintain the same orientation. At a critical point the layer swells rapidly and makes highly ordered lamellae structure at the same time. The lamellae are almost exclusively oriented parallel to the substrate and swell with increasing water absorption

SFmap: a web server for motif analysis and prediction of splicing factor binding sites

Alternative splicing (AS) is a post-transcriptional process considered to be responsible for the huge diversity of proteins in higher eukaryotes. AS events are regulated by different splicing factors (SFs) that bind to sequence elements on the RNA. SFmap is a web server for predicting putative SF binding sites in genomic data (http://sfmap.technion.ac.il). SFmap implements the COS(WR) algorithm, which computes similarity scores for a given regulatory motif based on information derived from its sequence environment and its evolutionary conservation. Input for SFmap is a human genomic sequence or a list of sequences in FASTA format that can either be uploaded from a file or pasted into a window. SFmap searches within a given sequence for significant hits of binding motifs that are either stored in our database or defined by the user. SFmap results are provided both as a text file and as a graphical web interface

Stochastic transitions of attractors in associative memory models with correlated noise

We investigate dynamics of recurrent neural networks with correlated noise to analyze the noise's effect. The mechanism of correlated firing has been analyzed in various models, but its functional roles have not been discussed in sufficient detail. Aoyagi and Aoki have shown that the state transition of a network is invoked by synchronous spikes. We introduce two types of noise to each neuron: thermal independent noise and correlated noise. Due to the effects of correlated noise, the correlation between neural inputs cannot be ignored, so the behavior of the network has sample dependence. We discuss two types of associative memory models: one with auto- and weak cross-correlation connections and one with hierarchically correlated patterns. The former is similar in structure to Aoyagi and Aoki's model. We show that stochastic transition can be presented by correlated rather than thermal noise. In the latter, we show stochastic transition from a memory state to a mixture state using correlated noise. To analyze the stochastic transitions, we derive a macroscopic dynamic description as a recurrence relation form of a probability density function when the correlated noise exists. Computer simulations agree with theoretical results.Comment: 21 page

Spectra and waiting-time densities in firing resonant and nonresonant neurons

The response of a neural cell to an external stimulus can follow one of the two patterns: Nonresonant neurons monotonously relax to the resting state after excitation while resonant ones show subthreshold oscillations. We investigate how do these subthreshold properties of neurons affect their suprathreshold response. Vice versa we ask: Can we distinguish between both types of neuronal dynamics using suprathreshold spike trains? The dynamics of neurons is given by stochastic FitzHugh-Nagumo and Morris-Lecar models with either having a focus or a node as the stable fixpoint. We determine numerically the spectral power density as well as the interspike interval density in response to a random (noise-like) signals. We show that the information about the type of dynamics obtained from power spectra is of limited validity. In contrast, the interspike interval density gives a very sensitive instrument for the diagnostics of whether the dynamics has resonant or nonresonant properties. For the latter value we formulate a fit formula and use it to reconstruct theoretically the spectral power density, which coincides with the numerically obtained spectra. We underline that the renewal theory is applicable to analysis of suprathreshold responses even of resonant neurons.Comment: 7 pages, 8 figure

Densification of Fresh Concrete by Microwave

Concrete mixes with different fly ash replacement levels, namely 0%, 35% and 55% at a fixed water to binder ratio (W/B) of 0.6 were heated by a tailor-made microwave oven up to 50oC immediately after casting until initial setting in order to remove excessive free water. The compressive strengths of microwave densified samples after 7 days were 3.2%, 7.7% and 29.6% higher than those of oven heated batches. It demonstrated that higher density, lower water absorption and better microstructure were achieved after microwave heating, indicating microwave heating can be a promising technique for densifying fresh concrete