Delay Induced Excitability

We analyse the stochastic dynamics of a bistable system under the influence of time-delayed feedback. Assuming an asymmetric potential, we show the existence of a regime in which the systems dynamic displays excitability by calculating the relevant residence time distributions and correlation times. Experimentally we then observe this behaviour in the polarization dynamics of a vertical cavity surface emitting laser with opto-electronic feedback. Extending these observations to two-dimensional systems with dispersive coupling we finally show numerically that delay induced excitability can lead to the appearance of propagating wave-fronts and spirals.Comment: 5 pages, 6 figure

Dynamical mechanism of anticipating synchronization in excitable systems

We analyze the phenomenon of anticipating synchronization of two excitable systems with unidirectional delayed coupling which are subject to the same external forcing. We demonstrate for different paradigms of excitable system that, due to the coupling, the excitability threshold for the slave system is always lower than that for the master. As a consequence the two systems respond to a common external forcing with different response times. This allows to explain in a simple way the mechanism behind the phenomenon of anticipating synchronization.Comment: 4 pages including 7 figures. Submitted for publicatio

Computational inference in systems biology

Parameter inference in mathematical models of biological pathways, expressed as coupled ordinary differential equations (ODEs), is a challenging problem. The computational costs associated with repeatedly solving the ODEs are often high. Aimed at reducing this cost, new concepts using gradient matching have been proposed. This paper combines current adaptive gradient matching approaches, using Gaussian processes, with a parallel tempering scheme, and conducts a comparative evaluation with current methods used for parameter inference in ODEs

Distribution, Abundance, and Age Structure of Red Snapper (Lutjanus campechanus) Caught on Research Longlines in U.S. Gulf of Mexico

Two pilot surveys were conducted in the northern Gulf of Mexico (Gulf) to determine the feasibility of sampling red snapper (Lutjanus campechanus) populations in offshore waters with bottom longline gear. The first pilot survey off Mississippi-Alabama was conducted in May 1999 and yielded a total of seven snapper from 60 stations. The second pilot survey was off Texas in June 2000 and yielded a total of 76 snapper from 44 stations. The catch per unit effort was 0.12 red snapper/100 hook hr [coefficient of variation (CV) = 0.54] in 1999 and 1.73 red snapper/100 hook hr (CV = 0.21) in 2000. Otoliths were removed from all collected red snapper, and ages were assigned with an average percent error of 3.71%. Red snapper from the 1999 survey ranged from 405 to 873 mm total length (TL) (545 mm TL median) and from 3 to 19 yr (median age 5 yr). The red snapper from Texas ranged in size from 380 to 903 mm TL (755 mm TL median) and ranged in age from 3 to 53 yr (median age 11 yr). Based on the results of the pilot surveys, expanded longline surveys targeting red snapper were conducted in 2001 and 2002; these surveys yielded 86 snapper and 75 snapper, respectively. The 2001 snapper ranged from 427 to 950 mm TL (770 mm TL median) and from 3 to 37 yr (median age 12 yr). The 2002 snapper ranged from 409 to 950 mm TL (815 mm TL median) and from 4 to 44 yr (median age 13 yr). Twelve red snapper were captured in the eastern Gulf (east of the Mississippi River), and their ages ranged from 3 to 19 yr (median age 6 yr). The 232 red snapper that were caught in the western Gulf ranged in age from 3 to 53 yr (median age 12 yr). A difference in catch rates by depth was also noted with most red snapper captures occurring in the 55-92 m depth range

Thermal Impact on Spiking Properties in Hodgkin-Huxley Neuron with Synaptic Stimulus

The effect of environmental temperature on neuronal spiking behaviors is investigated by numerically simulating the temperature dependence of spiking threshold of the Hodgkin-Huxley neuron subject to synaptic stimulus. We find that the spiking threshold exhibits a global minimum in a "comfortable temperature" range where spike initiation needs weakest synaptic strength, indicating the occurrence of optimal use of synaptic transmission in neural system. We further explore the biophysical origin of this phenomenon in ion channel gating kinetics and also discuss its possible biological relevance in information processing in neural systems.Comment: 10 pages, 4 figure

Greenhouse gas balance over thaw-freeze cycles in discontinuous zone permafrost

Peat in the discontinuous permafrost zone contains a globally significant reservoir of carbon that has undergone multiple permafrost-thaw cycles since the end of the mid-Holocene (~3700 years before present). Periods of thaw increase C decomposition rates which leads to the release of CO2 and CH4 to the atmosphere creating potential climate feedback. To determine the magnitude and direction of such feedback, we measured CO2 and CH4 emissions and modeled C accumulation rates and radiative fluxes from measurements of two radioactive tracers with differing lifetimes to describe the C balance of the peatland over multiple permafrost-thaw cycles since the initiation of permafrost at the site. At thaw features, the balance between increased primary production and higher CH4 emission stimulated by warmer temperatures and wetter conditions favors C sequestration and enhanced peat accumulation. Flux measurements suggest that frozen plateaus may intermittently (order of years to decades) act as CO2 sources depending on temperature and net ecosystem respiration rates, but modeling results suggest that—despite brief periods of net C loss to the atmosphere at the initiation of thaw—integrated over millennia, these sites have acted as net C sinks via peat accumulation. In greenhouse gas terms, the transition from frozen permafrost to thawed wetland is accompanied by increasing CO2 uptake that is partially offset by increasing CH4 emissions. In the short-term (decadal time scale) the net effect of this transition is likely enhanced warming via increased radiative C emissions, while in the long-term (centuries) net C deposition provides a negative feedback to climate warming

Dynamics of lattice spins as a model of arrhythmia

We consider evolution of initial disturbances in spatially extended systems with autonomous rhythmic activity, such as the heart. We consider the case when the activity is stable with respect to very smooth (changing little across the medium) disturbances and construct lattice models for description of not-so-smooth disturbances, in particular, topological defects; these models are modifications of the diffusive XY model. We find that when the activity on each lattice site is very rigid in maintaining its form, the topological defects - vortices or spirals - nucleate a transition to a disordered, turbulent state.Comment: 17 pages, revtex, 3 figure

Noise Induced Coherence in Neural Networks

We investigate numerically the dynamics of large networks of $N$ globally pulse-coupled integrate and fire neurons in a noise-induced synchronized state. The powerspectrum of an individual element within the network is shown to exhibit in the thermodynamic limit ($N\to \infty$) a broadband peak and an additional delta-function peak that is absent from the powerspectrum of an isolated element. The powerspectrum of the mean output signal only exhibits the delta-function peak. These results are explained analytically in an exactly soluble oscillator model with global phase coupling.Comment: 4 pages ReVTeX and 3 postscript figure

Limits and dynamics of stochastic neuronal networks with random heterogeneous delays

Realistic networks display heterogeneous transmission delays. We analyze here the limits of large stochastic multi-populations networks with stochastic coupling and random interconnection delays. We show that depending on the nature of the delays distributions, a quenched or averaged propagation of chaos takes place in these networks, and that the network equations converge towards a delayed McKean-Vlasov equation with distributed delays. Our approach is mostly fitted to neuroscience applications. We instantiate in particular a classical neuronal model, the Wilson and Cowan system, and show that the obtained limit equations have Gaussian solutions whose mean and standard deviation satisfy a closed set of coupled delay differential equations in which the distribution of delays and the noise levels appear as parameters. This allows to uncover precisely the effects of noise, delays and coupling on the dynamics of such heterogeneous networks, in particular their role in the emergence of synchronized oscillations. We show in several examples that not only the averaged delay, but also the dispersion, govern the dynamics of such networks.Comment: Corrected misprint (useless stopping time) in proof of Lemma 1 and clarified a regularity hypothesis (remark 1

A propensity criterion for networking in an array of coupled chaotic systems

We examine the mutual synchronization of a one dimensional chain of chaotic identical objects in the presence of a stimulus applied to the first site. We first describe the characteristics of the local elements, and then the process whereby a global nontrivial behaviour emerges. A propensity criterion for networking is introduced, consisting in the coexistence within the attractor of a localized chaotic region, which displays high sensitivity to external stimuli,and an island of stability, which provides a reliable coupling signal to the neighbors in the chain. Based on this criterion we compare homoclinic chaos, recently explored in lasers and conjectured to be typical of a single neuron, with Lorenz chaos.Comment: 4 pages, 3 figure