431 research outputs found
Intrinsic adaptation in autonomous recurrent neural networks
A massively recurrent neural network responds on one side to input stimuli
and is autonomously active, on the other side, in the absence of sensory
inputs. Stimuli and information processing depends crucially on the qualia of
the autonomous-state dynamics of the ongoing neural activity. This default
neural activity may be dynamically structured in time and space, showing
regular, synchronized, bursting or chaotic activity patterns.
We study the influence of non-synaptic plasticity on the default dynamical
state of recurrent neural networks. The non-synaptic adaption considered acts
on intrinsic neural parameters, such as the threshold and the gain, and is
driven by the optimization of the information entropy. We observe, in the
presence of the intrinsic adaptation processes, three distinct and globally
attracting dynamical regimes, a regular synchronized, an overall chaotic and an
intermittent bursting regime. The intermittent bursting regime is characterized
by intervals of regular flows, which are quite insensitive to external stimuli,
interseeded by chaotic bursts which respond sensitively to input signals. We
discuss these finding in the context of self-organized information processing
and critical brain dynamics.Comment: 24 pages, 8 figure
Spatio-temporal patterns driven by autocatalytic internal reaction noise
The influence that intrinsic local density fluctuations can have on solutions
of mean-field reaction-diffusion models is investigated numerically by means of
the spatial patterns arising from two species that react and diffuse in the
presence of strong internal reaction noise. The dynamics of the Gray-Scott (GS)
model with constant external source is first cast in terms of a continuum field
theory representing the corresponding master equation. We then derive a
Langevin description of the field theory and use these stochastic differential
equations in our simulations. The nature of the multiplicative noise is
specified exactly without recourse to assumptions and turns out to be of the
same order as the reaction itself, and thus cannot be treated as a small
perturbation. Many of the complex patterns obtained in the absence of noise for
the GS model are completely obliterated by these strong internal fluctuations,
but we find novel spatial patterns induced by this reaction noise in regions of
parameter space that otherwise correspond to homogeneous solutions when
fluctuations are not included.Comment: 12 pages, 18 figure
Continuum limit of self-driven particles with orientation interaction
We consider the discrete Couzin-Vicsek algorithm (CVA), which describes the
interactions of individuals among animal societies such as fish schools. In
this article, we propose a kinetic (mean-field) version of the CVA model and
provide its formal macroscopic limit. The final macroscopic model involves a
conservation equation for the density of the individuals and a non conservative
equation for the director of the mean velocity and is proved to be hyperbolic.
The derivation is based on the introduction of a non-conventional concept of a
collisional invariant of a collision operator
Cognitive ability experiment with photosensitive organic molecular thin films
We present an optical experiment which permits to evaluate the information
exchange necessary to self-induce cooperatively a well-organized pattern in a
randomly activated molecular assembly. A low-power coherent beam carrying
polarization and wavelength information is used to organize a surface relief
grating on a photochromic polymer thin film which is photo-activated by a
powerful incoherent beam. We demonstrate experimentally that less than 1% of
the molecules possessing information cooperatively transmit it to the entire
photo-activated polymer film.Comment: 16 pages, 4 figure
Autonomous Motility of Active Filaments due to Spontaneous Flow-Symmetry Breaking
We simulate the nonlocal Stokesian hydrodynamics of an elastic filament which
is active due a permanent distribution of stresslets along its contour. A
bending instability of an initially straight filament spontaneously breaks flow
symmetry and leads to autonomous filament motion which, depending on
conformational symmetry, can be translational or rotational. At high ratios of
activity to elasticity, the linear instability develops into nonlinear
fluctuating states with large amplitude deformations. The dynamics of these
states can be qualitatively understood as a superposition of translational and
rotational motion associated with filament conformational modes of opposite
symmetry. Our results can be tested in molecular-motor filament mixtures,
synthetic chains of autocatalytic particles, or other linearly connected
systems where chemical energy is converted to mechanical energy in a fluid
environment.Comment: 7 pages, 3 figures; contains supplemental text; movies at
http://proofideas.org/rjoy/gallery; published in Physical Review Letter
A well-posedness theory in measures for some kinetic models of collective motion
We present existence, uniqueness and continuous dependence results for some
kinetic equations motivated by models for the collective behavior of large
groups of individuals. Models of this kind have been recently proposed to study
the behavior of large groups of animals, such as flocks of birds, swarms, or
schools of fish. Our aim is to give a well-posedness theory for general models
which possibly include a variety of effects: an interaction through a
potential, such as a short-range repulsion and long-range attraction; a
velocity-averaging effect where individuals try to adapt their own velocity to
that of other individuals in their surroundings; and self-propulsion effects,
which take into account effects on one individual that are independent of the
others. We develop our theory in a space of measures, using mass transportation
distances. As consequences of our theory we show also the convergence of
particle systems to their corresponding kinetic equations, and the
local-in-time convergence to the hydrodynamic limit for one of the models
Stability properties of the collective stationary motion of self-propelling particles with conservative kinematic constraints
In our previous papers we proposed a continuum model for the dynamics of the
systems of self-propelling particles with conservative kinematic constraints on
the velocities. We have determined a class of stationary solutions of this
hydrodynamic model and have shown that two types of stationary flow, linear and
radially symmetric (vortical) flow, are possible. In this paper we consider the
stability properties of these stationary flows. We show, using a linear
stability analysis, that the linear solutions are neutrally stable with respect
to the imposed velocity and density perturbations. A similar analysis of the
stability of the vortical solution is found to be not conclusive.Comment: 13 pages, 3 figure
The Effect of Sensory Blind Zones on Milling Behavior in a Dynamic Self-Propelled Particle Model
Emergent pattern formation in self-propelled particle (SPP) systems is
extensively studied because it addresses a range of swarming phenomena which
occur without leadership. Here we present a dynamic SPP model in which a
sensory blind zone is introduced into each particle's zone of interaction.
Using numerical simulations we discovered that the degradation of milling
patterns with increasing blind zone ranges undergoes two distinct transitions,
including a new, spatially nonhomogeneous transition that involves cessation of
particles' motion caused by broken symmetries in their interaction fields. Our
results also show the necessity of nearly complete panoramic sensory ability
for milling behavior to emerge in dynamic SPP models, suggesting a possible
relationship between collective behavior and sensory systems of biological
organisms.Comment: 12 pages, 4 figure
Collective traffic-like movement of ants on a trail: dynamical phases and phase transitions
The traffic-like collective movement of ants on a trail can be described by a
stochastic cellular automaton model. We have earlier investigated its unusual
flow-density relation by using various mean field approximations and computer
simulations. In this paper, we study the model following an alternative
approach based on the analogy with the zero range process, which is one of the
few known exactly solvable stochastic dynamical models. We show that our theory
can quantitatively account for the unusual non-monotonic dependence of the
average speed of the ants on their density for finite lattices with periodic
boundary conditions. Moreover, we argue that the model exhibits a continuous
phase transition at the critial density only in a limiting case. Furthermore,
we investigate the phase diagram of the model by replacing the periodic
boundary conditions by open boundary conditions.Comment: 8 pages, 6 figure
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