1,341 research outputs found
Superconductivity-Related Insulating Behavior
We present the results of an experimental study of superconducting,
disordered, thin-films of amorphous Indium Oxide. These films can be driven
from the superconducting phase to a reentrant insulating state by the
application of a perpendicular magnetic field (). We find that the high-
insulator exhibits activated transport with a characteristic temperature,
. has a maximum value () that is close to the
superconducting transition temperature () at = 0, suggesting a
possible relation between the conduction mechanisms in the superconducting and
insulating phases. and display opposite dependences on the
disorder strength.Comment: Tex file and 5 figures; Revised version; To appear in Phys. Rev.
Lett. (2004
Clustering and Synchronization of Oscillator Networks
Using a recently described technique for manipulating the clustering
coefficient of a network without changing its degree distribution, we examine
the effect of clustering on the synchronization of phase oscillators on
networks with Poisson and scale-free degree distributions. For both types of
network, increased clustering hinders global synchronization as the network
splits into dynamical clusters that oscillate at different frequencies.
Surprisingly, in scale-free networks, clustering promotes the synchronization
of the most connected nodes (hubs) even though it inhibits global
synchronization. As a result, scale-free networks show an additional, advanced
transition instead of a single synchronization threshold. This cluster-enhanced
synchronization of hubs may be relevant to the brain with its scale-free and
highly clustered structure.Comment: Submitted to Phys. Rev.
Nonlocal mechanism for cluster synchronization in neural circuits
The interplay between the topology of cortical circuits and synchronized
activity modes in distinct cortical areas is a key enigma in neuroscience. We
present a new nonlocal mechanism governing the periodic activity mode: the
greatest common divisor (GCD) of network loops. For a stimulus to one node, the
network splits into GCD-clusters in which cluster neurons are in zero-lag
synchronization. For complex external stimuli, the number of clusters can be
any common divisor. The synchronized mode and the transients to synchronization
pinpoint the type of external stimuli. The findings, supported by an
information mixing argument and simulations of Hodgkin Huxley population
dynamic networks with unidirectional connectivity and synaptic noise, call for
reexamining sources of correlated activity in cortex and shorter information
processing time scales.Comment: 8 pges, 6 figure
Theory of Interaction of Memory Patterns in Layered Associative Networks
A synfire chain is a network that can generate repeated spike patterns with
millisecond precision. Although synfire chains with only one activity
propagation mode have been intensively analyzed with several neuron models,
those with several stable propagation modes have not been thoroughly
investigated. By using the leaky integrate-and-fire neuron model, we
constructed a layered associative network embedded with memory patterns. We
analyzed the network dynamics with the Fokker-Planck equation. First, we
addressed the stability of one memory pattern as a propagating spike volley. We
showed that memory patterns propagate as pulse packets. Second, we investigated
the activity when we activated two different memory patterns. Simultaneous
activation of two memory patterns with the same strength led the propagating
pattern to a mixed state. In contrast, when the activations had different
strengths, the pulse packet converged to a two-peak state. Finally, we studied
the effect of the preceding pulse packet on the following pulse packet. The
following pulse packet was modified from its original activated memory pattern,
and it converged to a two-peak state, mixed state or non-spike state depending
on the time interval
Parity Effects in Stacked Nanoscopic Quantum Rings
The ground state and the dielectric response of stacked quantum rings are
investigated in the presence of an applied magnetic field along the ring axis.
For odd number of rings and an electric field perpendicular to the axis, a
linear Stark effect occurs at distinct values of the magnetic field. At those
fields energy levels cross in the absence of electric field. For even values of
a quadratic Stark effect is expected in all cases, but the induced electric
polarization is discontinuous at those special magnetic fields. Experimental
consequences for related nanostructures are discussed.Comment: typos corrected, to appear Phys. Rev. B (Rapid Communication) 15 Au
Sequence effects in the categorization of tones varying in frequency
In contrast to exemplar and decision-bound categorization models, the memory and contrast models described here do not assume that long-term representations of stimulus magnitudes are available. Instead, stimuli are assumed to be categorized using only their differences from a few recent stimuli. To test this alternative, the authors examined sequential effects in a binary categorization of 10 tones varying in frequency. Stimuli up to 2 trials back in the sequence had a significant effect on the response to the current stimulus. The effects of previous stimuli interacted with one another. A memory and contrast model, according to which only ordinal information about the differences between the current stimulus and recent preceding stimuli is used, best accounted for these dat
Sparse and Dense Encoding in Layered Associative Network of Spiking Neurons
A synfire chain is a simple neural network model which can propagate stable
synchronous spikes called a pulse packet and widely researched. However how
synfire chains coexist in one network remains to be elucidated. We have studied
the activity of a layered associative network of Leaky Integrate-and-Fire
neurons in which connection we embed memory patterns by the Hebbian Learning.
We analyzed their activity by the Fokker-Planck method. In our previous report,
when a half of neurons belongs to each memory pattern (memory pattern rate
), the temporal profiles of the network activity is split into
temporally clustered groups called sublattices under certain input conditions.
In this study, we show that when the network is sparsely connected (),
synchronous firings of the memory pattern are promoted. On the contrary, the
densely connected network () inhibit synchronous firings. The sparseness
and denseness also effect the basin of attraction and the storage capacity of
the embedded memory patterns. We show that the sparsely(densely) connected
networks enlarge(shrink) the basion of attraction and increase(decrease) the
storage capacity
Pulse propagation in discrete excitatory networks of integrate-and-fire neurons
We study the propagation of solitary waves in a discrete excitatory network of integrate-and-fire neurons. We show the existence and the stability of a fast wave and a family of slow waves. Fast waves are similar to those already described in continuum networks. Stable slow waves have not been previously reported in purely excitatory networks and their propagation is particular to the discrete nature of the network. The robustness of our results is studied in the presence of noise
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