28,201 research outputs found
In-phase and anti-phase synchronization in noisy Hodgkin-Huxley neurons
We numerically investigate the influence of intrinsic channel noise on the
dynamical response of delay-coupling in neuronal systems. The stochastic
dynamics of the spiking is modeled within a stochastic modification of the
standard Hodgkin-Huxley model wherein the delay-coupling accounts for the
finite propagation time of an action potential along the neuronal axon. We
quantify this delay-coupling of the Pyragas-type in terms of the difference
between corresponding presynaptic and postsynaptic membrane potentials. For an
elementary neuronal network consisting of two coupled neurons we detect
characteristic stochastic synchronization patterns which exhibit multiple
phase-flip bifurcations: The phase-flip bifurcations occur in form of alternate
transitions from an in-phase spiking activity towards an anti-phase spiking
activity. Interestingly, these phase-flips remain robust in strong channel
noise and in turn cause a striking stabilization of the spiking frequency
Efficient synchronization of structurally adaptive coupled Hindmarsh-Rose neurons
The use of spikes to carry information between brain areas implies complete
or partial synchronization of the neurons involved. The degree of
synchronization reached by two coupled systems and the energy cost of
maintaining their synchronized behaviour is highly dependent on the nature of
the systems. For non-identical systems the maintenance of a synchronized regime
is energetically a costly process. In this work, we study conditions under
which two non-identical electrically coupled neurons can reach an efficient
regime of synchronization at low energy cost. We show that the energy
consumption required to keep the synchronized regime can be spontaneously
reduced if the receiving neuron has adaptive mechanisms able to bring its
biological parameters closer in value to the corresponding ones in the sending
neuron
New Solutions to the Firing Squad Synchronization Problems for Neural and Hyperdag P Systems
We propose two uniform solutions to an open question: the Firing Squad
Synchronization Problem (FSSP), for hyperdag and symmetric neural P systems,
with anonymous cells. Our solutions take e_c+5 and 6e_c+7 steps, respectively,
where e_c is the eccentricity of the commander cell of the dag or digraph
underlying these P systems. The first and fast solution is based on a novel
proposal, which dynamically extends P systems with mobile channels. The second
solution is substantially longer, but is solely based on classical rules and
static channels. In contrast to the previous solutions, which work for
tree-based P systems, our solutions synchronize to any subset of the underlying
digraph; and do not require membrane polarizations or conditional rules, but
require states, as typically used in hyperdag and neural P systems
Synchronous Behavior of Two Coupled Electronic Neurons
We report on experimental studies of synchronization phenomena in a pair of
analog electronic neurons (ENs). The ENs were designed to reproduce the
observed membrane voltage oscillations of isolated biological neurons from the
stomatogastric ganglion of the California spiny lobster Panulirus interruptus.
The ENs are simple analog circuits which integrate four dimensional
differential equations representing fast and slow subcellular mechanisms that
produce the characteristic regular/chaotic spiking-bursting behavior of these
cells. In this paper we study their dynamical behavior as we couple them in the
same configurations as we have done for their counterpart biological neurons.
The interconnections we use for these neural oscillators are both direct
electrical connections and excitatory and inhibitory chemical connections: each
realized by analog circuitry and suggested by biological examples. We provide
here quantitative evidence that the ENs and the biological neurons behave
similarly when coupled in the same manner. They each display well defined
bifurcations in their mutual synchronization and regularization. We report
briefly on an experiment on coupled biological neurons and four dimensional ENs
which provides further ground for testing the validity of our numerical and
electronic models of individual neural behavior. Our experiments as a whole
present interesting new examples of regularization and synchronization in
coupled nonlinear oscillators.Comment: 26 pages, 10 figure
Enhancement of synchronization in a hybrid neural circuit by spike timing dependent plasticity
Synchronization of neural activity is fundamental for many functions of the brain. We demonstrate that spike-timing dependent plasticity (STDP) enhances synchronization (entrainment) in a hybrid circuit composed of a spike generator, a dynamic clamp emulating an excitatory plastic synapse, and a chemically isolated neuron from the Aplysia abdominal ganglion. Fixed-phase entrainment of the Aplysia neuron to the spike generator is possible for a much wider range of frequency ratios and is more precise and more robust with the plastic synapse than with a nonplastic synapse of comparable strength. Further analysis in a computational model of HodgkinHuxley-type neurons reveals the mechanism behind this significant enhancement in synchronization. The experimentally observed STDP plasticity curve appears to be designed to adjust synaptic strength to a value suitable for stable entrainment of the postsynaptic neuron. One functional role of STDP might therefore be to facilitate synchronization or entrainment of nonidentical neurons
On the role of chemical synapses in coupled neurons with noise
We examine the behavior in the presence of noise of an array of Morris-Lecar
neurons coupled via chemical synapses. Special attention is devoted to
comparing this behavior with the better known case of electrical coupling
arising via gap junctions. In particular, our numerical simulations show that
chemical synapses are more efficient than gap junctions in enhancing coherence
at an optimal noise (what is known as array-enhanced coherence resonance): in
the case of (nonlinear) chemical coupling, we observe a substantial increase in
the stochastic coherence of the system, in comparison with (linear) electrical
coupling. We interpret this qualitative difference between both types of
coupling as arising from the fact that chemical synapses only act while the
presynaptic neuron is spiking, whereas gap junctions connect the voltage of the
two neurons at all times. This leads in the electrical coupling case to larger
correlations during interspike time intervals which are detrimental to the
array-enhanced coherence effect. Finally, we report on the existence of a
system-size coherence resonance in this locally coupled system, exhibited by
the average membrane potential of the array.Comment: 7 pages, 7 figure
Mechanisms of Zero-Lag Synchronization in Cortical Motifs
Zero-lag synchronization between distant cortical areas has been observed in
a diversity of experimental data sets and between many different regions of the
brain. Several computational mechanisms have been proposed to account for such
isochronous synchronization in the presence of long conduction delays: Of
these, the phenomenon of "dynamical relaying" - a mechanism that relies on a
specific network motif - has proven to be the most robust with respect to
parameter mismatch and system noise. Surprisingly, despite a contrary belief in
the community, the common driving motif is an unreliable means of establishing
zero-lag synchrony. Although dynamical relaying has been validated in empirical
and computational studies, the deeper dynamical mechanisms and comparison to
dynamics on other motifs is lacking. By systematically comparing
synchronization on a variety of small motifs, we establish that the presence of
a single reciprocally connected pair - a "resonance pair" - plays a crucial
role in disambiguating those motifs that foster zero-lag synchrony in the
presence of conduction delays (such as dynamical relaying) from those that do
not (such as the common driving triad). Remarkably, minor structural changes to
the common driving motif that incorporate a reciprocal pair recover robust
zero-lag synchrony. The findings are observed in computational models of
spiking neurons, populations of spiking neurons and neural mass models, and
arise whether the oscillatory systems are periodic, chaotic, noise-free or
driven by stochastic inputs. The influence of the resonance pair is also robust
to parameter mismatch and asymmetrical time delays amongst the elements of the
motif. We call this manner of facilitating zero-lag synchrony resonance-induced
synchronization, outline the conditions for its occurrence, and propose that it
may be a general mechanism to promote zero-lag synchrony in the brain.Comment: 41 pages, 12 figures, and 11 supplementary figure
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