22,183 research outputs found
Death and rebirth of neural activity in sparse inhibitory networks
In this paper, we clarify the mechanisms underlying a general phenomenon
present in pulse-coupled heterogeneous inhibitory networks: inhibition can
induce not only suppression of the neural activity, as expected, but it can
also promote neural reactivation. In particular, for globally coupled systems,
the number of firing neurons monotonically reduces upon increasing the strength
of inhibition (neurons' death). However, the random pruning of the connections
is able to reverse the action of inhibition, i.e. in a sparse network a
sufficiently strong synaptic strength can surprisingly promote, rather than
depress, the activity of the neurons (neurons' rebirth). Thus the number of
firing neurons reveals a minimum at some intermediate synaptic strength. We
show that this minimum signals a transition from a regime dominated by the
neurons with higher firing activity to a phase where all neurons are
effectively sub-threshold and their irregular firing is driven by current
fluctuations. We explain the origin of the transition by deriving an analytic
mean field formulation of the problem able to provide the fraction of active
neurons as well as the first two moments of their firing statistics. The
introduction of a synaptic time scale does not modify the main aspects of the
reported phenomenon. However, for sufficiently slow synapses the transition
becomes dramatic, the system passes from a perfectly regular evolution to an
irregular bursting dynamics. In this latter regime the model provides
predictions consistent with experimental findings for a specific class of
neurons, namely the medium spiny neurons in the striatum.Comment: 19 pages, 10 figures, submitted to NJ
Design and development of a multipurpose, boresighted star tracker
Design and development of boresighted star tracke
Interplay of plasma-induced and fast thermal nonlinearities in a GaAs-based photonic crystal nanocavity
We investigate the nonlinear response of GaAs-based photonic crystal cavities
at time scales which are much faster than the typical thermal relaxation rate
in photonic devices. We demonstrate a strong interplay between thermal and
carrier induced nonlinear effects. We have introduced a dynamical model
entailing two thermal relaxation constants which is in very good agreement with
experiments. These results will be very important for Photonic Crystal-based
nonlinear devices intended to deal with practical high repetition rate optical
signals.Comment: 10 pages, 8 figures, Phys Rev A (accepted
Characterization of Large Volume 3.5 x 8 inches LaBr3:Ce Detectors
The properties of large volume cylindrical 3.5 x 8 inches (89 mm x 203 mm)
LaBr3:Ce scintillation detectors coupled to the Hamamatsu R10233-100SEL
photo-multiplier tube were investigated. These crystals are among the largest
ones ever produced and still need to be fully characterized to determine how
these detectors can be utilized and in which applications. We tested the
detectors using monochromatic gamma-ray sources and in-beam reactions producing
gamma rays up to 22.6 MeV; we acquired PMT signal pulses and calculated
detector energy resolution and response linearity as a function of gamma-ray
energy. Two different voltage dividers were coupled to the Hamamatsu
R10233-100SEL PMT: the Hamamatsu E1198-26, based on straightforward resistive
network design, and the LABRVD, specifically designed for our large volume
LaBr3:Ce scintillation detectors, which also includes active semiconductor
devices. Because of the extremely high light yield of LaBr3:Ce crystals we
observed that, depending on the choice of PMT, voltage divider and applied
voltage, some significant deviation from the ideally proportional response of
the detector and some pulse shape deformation appear. In addition, crystal
non-homogeneities and PMT gain drifts affect the (measured) energy resolution
especially in case of high-energy gamma rays. We also measured the time
resolution of detectors with different sizes (from 1x1 inches up to 3.5x8
inches), correlating the results with both the intrinsic properties of PMTs and
GEANT simulations of the scintillation light collection process. The detector
absolute full energy efficiency was measured and simulated up to gamma-rays of
30 Me
Performance of dynamical decoupling in bosonic environments and under pulse-timing fluctuations
We study the suppression of qubit dephasing through Uhrig dynamical
decoupling (UDD) in nontrivial environments modeled within the spin-boson
formalism. In particular, we address the case of (i) a qubit coupled to a
bosonic bath with power-law spectral density, and (ii) a qubit coupled to a
single harmonic oscillator that dissipates energy into a bosonic bath, which
embodies an example of a structured bath for the qubit. We then model the
influence of random time jitter in the UDD protocol by sorting
pulse-application times from Gaussian distributions centered at appropriate
values dictated by the optimal protocol. In case (i) we find that, when few
pulses are applied and a sharp cutoff is considered, longer coherence times and
robust UDD performances (against random timing errors) are achieved for a
super-Ohmic bath. On the other hand, when an exponential cutoff is considered a
super-Ohmic bath is undesirable. In case (ii) the best scenario is obtained for
an overdamped harmonic motion. Our study provides relevant information for the
implementation of optimized schemes for the protection of quantum states from
decoherence.Comment: 8 pages, 5 figure
Statistical-Mechanical Measure of Stochastic Spiking Coherence in A Population of Inhibitory Subthreshold Neurons
By varying the noise intensity, we study stochastic spiking coherence (i.e.,
collective coherence between noise-induced neural spikings) in an inhibitory
population of subthreshold neurons (which cannot fire spontaneously without
noise). This stochastic spiking coherence may be well visualized in the raster
plot of neural spikes. For a coherent case, partially-occupied "stripes"
(composed of spikes and indicating collective coherence) are formed in the
raster plot. This partial occupation occurs due to "stochastic spike skipping"
which is well shown in the multi-peaked interspike interval histogram. The main
purpose of our work is to quantitatively measure the degree of stochastic
spiking coherence seen in the raster plot. We introduce a new spike-based
coherence measure by considering the occupation pattern and the pacing
pattern of spikes in the stripes. In particular, the pacing degree between
spikes is determined in a statistical-mechanical way by quantifying the average
contribution of (microscopic) individual spikes to the (macroscopic)
ensemble-averaged global potential. This "statistical-mechanical" measure
is in contrast to the conventional measures such as the "thermodynamic" order
parameter (which concerns the time-averaged fluctuations of the macroscopic
global potential), the "microscopic" correlation-based measure (based on the
cross-correlation between the microscopic individual potentials), and the
measures of precise spike timing (based on the peri-stimulus time histogram).
In terms of , we quantitatively characterize the stochastic spiking
coherence, and find that reflects the degree of collective spiking
coherence seen in the raster plot very well. Hence, the
"statistical-mechanical" spike-based measure may be used usefully to
quantify the degree of stochastic spiking coherence in a statistical-mechanical
way.Comment: 16 pages, 5 figures, to appear in the J. Comput. Neurosc
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