934 research outputs found
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
Modeling rhythmic patterns in the hippocampus
We investigate different dynamical regimes of neuronal network in the CA3
area of the hippocampus. The proposed neuronal circuit includes two fast- and
two slowly-spiking cells which are interconnected by means of dynamical
synapses. On the individual level, each neuron is modeled by FitzHugh-Nagumo
equations. Three basic rhythmic patterns are observed: gamma-rhythm in which
the fast neurons are uniformly spiking, theta-rhythm in which the individual
spikes are separated by quiet epochs, and theta/gamma rhythm with repeated
patches of spikes. We analyze the influence of asymmetry of synaptic strengths
on the synchronization in the network and demonstrate that strong asymmetry
reduces the variety of available dynamical states. The model network exhibits
multistability; this results in occurrence of hysteresis in dependence on the
conductances of individual connections. We show that switching between
different rhythmic patterns in the network depends on the degree of
synchronization between the slow cells.Comment: 10 pages, 9 figure
Excitability in autonomous Boolean networks
We demonstrate theoretically and experimentally that excitable systems can be
built with autonomous Boolean networks. Their experimental implementation is
realized with asynchronous logic gates on a reconfigurabe chip. When these
excitable systems are assembled into time-delay networks, their dynamics
display nanosecond time-scale spike synchronization patterns that are
controllable in period and phase.Comment: 6 pages, 5 figures, accepted in Europhysics Letters
(epljournal.edpsciences.org
Emergent global oscillations in heterogeneous excitable media: The example of pancreatic beta cells
Using the standard van der Pol-FitzHugh-Nagumo excitable medium model I
demonstrate a novel generic mechanism, diversity, that provokes the emergence
of global oscillations from individually quiescent elements in heterogeneous
excitable media. This mechanism may be operating in the mammalian pancreas,
where excitable beta cells, quiescent when isolated, are found to oscillate
when coupled despite the absence of a pacemaker region.Comment: See home page http://lec.ugr.es/~julya
Noise Induced Coherence in Neural Networks
We investigate numerically the dynamics of large networks of 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 () 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
Heterogeneous Delays in Neural Networks
We investigate heterogeneous coupling delays in complex networks of excitable
elements described by the FitzHugh-Nagumo model. The effects of discrete as
well as of uni- and bimodal continuous distributions are studied with a focus
on different topologies, i.e., regular, small-world, and random networks. In
the case of two discrete delay times resonance effects play a major role:
Depending on the ratio of the delay times, various characteristic spiking
scenarios, such as coherent or asynchronous spiking, arise. For continuous
delay distributions different dynamical patterns emerge depending on the width
of the distribution. For small distribution widths, we find highly synchronized
spiking, while for intermediate widths only spiking with low degree of
synchrony persists, which is associated with traveling disruptions, partial
amplitude death, or subnetwork synchronization, depending sensitively on the
network topology. If the inhomogeneity of the coupling delays becomes too
large, global amplitude death is induced
The Shapes of Flux Domains in the Intermediate State of Type-I Superconductors
In the intermediate state of a thin type-I superconductor magnetic flux
penetrates in a disordered set of highly branched and fingered macroscopic
domains. To understand these shapes, we study in detail a recently proposed
"current-loop" (CL) model that models the intermediate state as a collection of
tense current ribbons flowing along the superconducting-normal interfaces and
subject to the constraint of global flux conservation. The validity of this
model is tested through a detailed reanalysis of Landau's original conformal
mapping treatment of the laminar state, in which the superconductor-normal
interfaces are flared within the slab, and of a closely-related straight-lamina
model. A simplified dynamical model is described that elucidates the nature of
possible shape instabilities of flux stripes and stripe arrays, and numerical
studies of the highly nonlinear regime of those instabilities demonstrate
patterns like those seen experimentally. Of particular interest is the buckling
instability commonly seen in the intermediate state. The free-boundary approach
further allows for a calculation of the elastic properties of the laminar
state, which closely resembles that of smectic liquid crystals. We suggest
several new experiments to explore of flux domain shape instabilities,
including an Eckhaus instability induced by changing the out-of-plane magnetic
field, and an analog of the Helfrich-Hurault instability of smectics induced by
an in-plane field.Comment: 23 pages, 22 bitmapped postscript figures, RevTex 3.0, submitted to
Phys. Rev. B. Higher resolution figures may be obtained by contacting the
author
Numerical Solution of Differential Equations by the Parker-Sochacki Method
A tutorial is presented which demonstrates the theory and usage of the
Parker-Sochacki method of numerically solving systems of differential
equations. Solutions are demonstrated for the case of projectile motion in air,
and for the classical Newtonian N-body problem with mutual gravitational
attraction.Comment: Added in July 2010: This tutorial has been posted since 1998 on a
university web site, but has now been cited and praised in one or more
refereed journals. I am therefore submitting it to the Cornell arXiv so that
it may be read in response to its citations. See "Spiking neural network
simulation: numerical integration with the Parker-Sochacki method:" J. Comput
Neurosci, Robert D. Stewart & Wyeth Bair and
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2717378
Associative memory storing an extensive number of patterns based on a network of oscillators with distributed natural frequencies in the presence of external white noise
We study associative memory based on temporal coding in which successful
retrieval is realized as an entrainment in a network of simple phase
oscillators with distributed natural frequencies under the influence of white
noise. The memory patterns are assumed to be given by uniformly distributed
random numbers on so that the patterns encode the phase differences
of the oscillators. To derive the macroscopic order parameter equations for the
network with an extensive number of stored patterns, we introduce the effective
transfer function by assuming the fixed-point equation of the form of the TAP
equation, which describes the time-averaged output as a function of the
effective time-averaged local field. Properties of the networks associated with
synchronization phenomena for a discrete symmetric natural frequency
distribution with three frequency components are studied based on the order
parameter equations, and are shown to be in good agreement with the results of
numerical simulations. Two types of retrieval states are found to occur with
respect to the degree of synchronization, when the size of the width of the
natural frequency distribution is changed.Comment: published in Phys. Rev.
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