206 research outputs found
Representational capacity of a set of independent neurons
The capacity with which a system of independent neuron-like units represents
a given set of stimuli is studied by calculating the mutual information between
the stimuli and the neural responses. Both discrete noiseless and continuous
noisy neurons are analyzed. In both cases, the information grows monotonically
with the number of neurons considered. Under the assumption that neurons are
independent, the mutual information rises linearly from zero, and approaches
exponentially its maximum value. We find the dependence of the initial slope on
the number of stimuli and on the sparseness of the representation.Comment: 19 pages, 6 figures, Phys. Rev. E, vol 63, 11910 - 11924 (2000
Network information and connected correlations
Entropy and information provide natural measures of correlation among
elements in a network. We construct here the information theoretic analog of
connected correlation functions: irreducible --point correlation is measured
by a decrease in entropy for the joint distribution of variables relative
to the maximum entropy allowed by all the observed variable
distributions. We calculate the ``connected information'' terms for several
examples, and show that it also enables the decomposition of the information
that is carried by a population of elements about an outside source.Comment: 4 pages, 3 figure
Spike latency and response properties of an excitable micropillar laser
We present experimental measurements concerning the response of an excitable micropillar laser with saturable absorber to incoherent as well as coherent perturbations. The excitable response is similar to the behavior of spiking neurons but with much faster time scales. It is accompanied by a subnanosecond nonlinear delay that is measured for different bias pump values. This mechanism provides a natural scheme for encoding the strength of an ultrafast stimulus in the response delay of excitable spikes (temporal coding). Moreover, we demonstrate coherent and incoherent perturbations techniques applied to the micropillar with perturbation thresholds in the range of a few femtojoules. Responses to coherent perturbations assess the cascadability of the system. We discuss the physical origin of the responses to single and double perturbations with the help of numerical simulations of the Yamada model and, in particular, unveil possibilities to control the relative refractory period that we recently evidenced in this system. Experimental measurements are compared to both numerical simulations of the Yamada model and analytic expressions obtained in the framework of singular perturbation techniques. This system is thus a good candidate to perform photonic spike processing tasks in the framework of novel neuroinspired computing systems.SCOPUS: ar.jinfo:eu-repo/semantics/publishe
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
Generalized Fisher information matrix in nonextensive systems with spatial correlation
By using the -Gaussian distribution derived by the maximum entropy method
for spatially-correlated -unit nonextensive systems, we have calculated the
generalized Fisher information matrix of for
, ), where ,
and denote the mean, variance and degree of spatial
correlation, respectively, for a given entropic index . It has been shown
from the Cram\'{e}r-Rao theorem that (1) an accuracy of an unbiased estimate of
is improved (degraded) by a negative (positive) correlation , (2)
that of is worsen with increasing , and (3) that of is much
improved for or though it is worst at . Our calculation provides a clear insight to the long-standing
controversy whether the spatial correlation is beneficial or detrimental to
decoding in neuronal ensembles. We discuss also a calculation of the
-Gaussian distribution, applying the superstatistics to the Langevin model
subjected to spatially-correlated inputs.Comment: 18 pages, 3 figures: revised version accepted in Phys. Rev.
Functional Clustering Drives Encoding Improvement in a Developing Brain Network during Awake Visual Learning
Sensory experience drives dramatic structural and functional plasticity in developing neurons. However, for single-neuron plasticity to optimally improve whole-network encoding of sensory information, changes must be coordinated between neurons to ensure a full range of stimuli is efficiently represented. Using two-photon calcium imaging to monitor evoked activity in over 100 neurons simultaneously, we investigate network-level changes in the developing Xenopus laevis tectum during visual training with motion stimuli. Training causes stimulus-specific changes in neuronal responses and interactions, resulting in improved population encoding. This plasticity is spatially structured, increasing tuning curve similarity and interactions among nearby neurons, and decreasing interactions among distant neurons. Training does not improve encoding by single clusters of similarly responding neurons, but improves encoding across clusters, indicating coordinated plasticity across the network. NMDA receptor blockade prevents coordinated plasticity, reduces clustering, and abolishes whole-network encoding improvement. We conclude that NMDA receptors support experience-dependent network self-organization, allowing efficient population coding of a diverse range of stimuli.Canadian Institutes of Health Researc
On-Orbit Performance of the Far Ultraviolet Spectroscopic Explorer (FUSE) Satellite
Launch of the Far Ultraviolet Spectroscopic Explorer (FUSE) has been followed
by an extensive period of calibration and characterization as part of the
preparation for normal satellite operations. Major tasks carried out during
this period include initial coalignment, focusing and characterization of the
four instrument channels, and a preliminary measurement of the resolution and
throughput performance of the instrument. We describe the results from this
test program, and present preliminary estimates of the on-orbit performance of
the FUSE satellite based on a combination of this data and prelaunch laboratory
measurements.Comment: 8 pages, including 3 figures. This paper will appear in the FUSE
special issue of ApJ Letter
- …