14 research outputs found
Evolution of avalanche conducting states in electrorheological liquids
Charge transport in electrorheological fluids is studied experimentally under
strongly nonequlibrium conditions. By injecting an electrical current into a
suspension of conducting nanoparticles we are able to initiate a process of
self-organization which leads, in certain cases, to formation of a stable
pattern which consists of continuous conducting chains of particles. The
evolution of the dissipative state in such system is a complex process. It
starts as an avalanche process characterized by nucleation, growth, and thermal
destruction of such dissipative elements as continuous conducting chains of
particles as well as electroconvective vortices. A power-law distribution of
avalanche sizes and durations, observed at this stage of the evolution,
indicates that the system is in a self-organized critical state. A sharp
transition into an avalanche-free state with a stable pattern of conducting
chains is observed when the power dissipated in the fluid reaches its maximum.
We propose a simple evolution model which obeys the maximum power condition and
also shows a power-law distribution of the avalanche sizes.Comment: 15 pages, 6 figure
On Synchronization in a Lattice Model of Pulse-Coupled Oscillators
We analyze the collective behavior of a lattice model of pulse-coupled
oscillators. By means of computer simulations we find the relation between the
intrinsic dynamics of each member of the population and their mutual
interaction that ensures, in a general context, the existence of a fully
synchronized regime. This condition turns out to be the same than the obtained
for the globally coupled population. When the condition is not completely
satisfied we find different spatial structures. This also gives some hints
about self-organized criticality.Comment: 4 pages, RevTex, 1 PostScript available upon request, To appear in
Phys. Rev. Let
Dynamic instabilities induced by asymmetric influence: Prisoners' dilemma game on small-world networks
A two-dimensional small-world type network, subject to spatial prisoners'
dilemma dynamics and containing an influential node defined as a special node
with a finite density of directed random links to the other nodes in the
network, is numerically investigated. It is shown that the degree of
cooperation does not remain at a steady state level but displays a punctuated
equilibrium type behavior manifested by the existence of sudden breakdowns of
cooperation. The breakdown of cooperation is linked to an imitation of a
successful selfish strategy of the influential node. It is also found that
while the breakdown of cooperation occurs suddenly, the recovery of it requires
longer time. This recovery time may, depending on the degree of steady state
cooperation, either increase or decrease with an increasing number of long
range connections.Comment: 5 pages, 6 figure
How spiking neurons give rise to a temporal-feature map
A temporal-feature map is a topographic neuronal representation of temporal attributes of phenomena or objects that occur in the outside world. We explain the evolution of such maps by means of a spike-based Hebbian learning rule in conjunction with a presynaptically unspecific contribution in that, if a synapse changes, then all other synapses connected to the same axon change by a small fraction as well. The learning equation is solved for the case of an array of Poisson neurons. We discuss the evolution of a temporal-feature map and the synchronization of the single cells’ synaptic structures, in dependence upon the strength of presynaptic unspecific learning. We also give an upper bound for the magnitude of the presynaptic interaction by estimating its impact on the noise level of synaptic growth. Finally, we compare the results with those obtained from a learning equation for nonlinear neurons and show that synaptic structure formation may profit
from the nonlinearity
Subthreshold Membrane-Potential Resonances Shape Spike-Train Patterns in the Entorhinal Cortex
Many neurons exhibit subthreshold membrane-potential resonances, such that the largest voltage responses occur at preferred stimulation frequencies. Because subthreshold resonances are known to influence the rhythmic activity at the network level, it is vital to understand how they affect spike generation on the single-cell level. We therefore investigated both resonant and nonresonant neurons of rat entorhinal cortex. A minimal resonate-and-fire type model based on measured physiological parameters captures fundamental properties of neuronal firing statistics surprisingly well and helps to shed light on the mechanisms that shape spike patterns: 1) subthreshold resonance together with a spike-induced reset of subthreshold oscillations leads to spike clustering and 2) spike-induced dynamics influence the fine structure of interspike interval (ISI) distributions and are responsible for ISI correlations appearing at higher firing rates (≥3 Hz). Both mechanisms are likely to account for the specific discharge characteristics of various cell types