Search results for "Neural"
showing 10 items of 2783 documents
Endothelial NT-3 Delivered by Vasculature and CSF Promotes Quiescence of Subependymal Neural Stem Cells through Nitric Oxide Induction
2014
SummaryInteractions of adult neural stem cells (NSCs) with supportive vasculature appear critical for their maintenance and function, although the molecular details are still under investigation. Neurotrophin (NT)-3 belongs to the NT family of trophic factors, best known for their effects in promoting neuronal survival. Here we show that NT-3 produced and secreted by endothelial cells of brain and choroid plexus capillaries is required for the quiescence and long-term maintenance of NSCs in the mouse subependymal niche. Uptake of NT-3 from irrigating vasculature and cerebrospinal fluid (CSF) induces the rapid phosphorylation of endothelial nitric oxide (NO) synthase present in the NSCs, lea…
Oligodendrocyte ablation triggers central pain independently of innate or adaptive immune responses in mice.
2014
Mechanisms underlying central neuropathic pain are poorly understood. Although glial dysfunction has been functionally linked with neuropathic pain, very little is known about modulation of pain by oligodendrocytes. Here we report that genetic ablation of oligodendrocytes rapidly triggers a pattern of sensory changes that closely resemble central neuropathic pain, which are manifest before overt demyelination. Primary oligodendrocyte loss is not associated with autoreactive T- and B-cell infiltration in the spinal cord and neither activation of microglia nor reactive astrogliosis contribute functionally to central pain evoked by ablation of oligodendrocytes. Instead, light and electron micr…
Role of noise in a market model with stochastic volatility
2006
We study a generalization of the Heston model, which consists of two coupled stochastic differential equations, one for the stock price and the other one for the volatility. We consider a cubic nonlinearity in the first equation and a correlation between the two Wiener processes, which model the two white noise sources. This model can be useful to describe the market dynamics characterized by different regimes corresponding to normal and extreme days. We analyze the effect of the noise on the statistical properties of the escape time with reference to the noise enhanced stability (NES) phenomenon, that is the noise induced enhancement of the lifetime of a metastable state. We observe NES ef…
A “Noise Gene” for Econets
1993
Genetically controlled noise is applied to the weights of neural networks trained with a genetic algorithm. Networks simulate simple organisms living in an environment Reproduction is based on the ability of each network, during its life, to respond to sensory information from the environment with appropriate motor action. Each network has an amount of noise which is genetically inherited (in the ‘noise gene’) with mutations and it varies interindividually. Noise modifies the value of a weight differently for each spreading of the activation through the network. Such noise has a positive effect on the evolutionary increase in fitness and it makes fitness less dependent on the initial choice…
A Physiological Approach for Minimizing Dead Reckoning Velocity Readings Drifts
2018
The evolution of the geo-positioning methods made Dead Reckoning (DR) one of the most important concern due to its performance in indoor pedestrian localization systems. This paper focuses on implementing an approach that relies on physiological parameters to minimize additive velocity error due to noise in pedestrian DR system.
Quantification of melanin and hemoglobin in humain skin from multispectral image acquisition: use of a neuronal network combined to a non-negative ma…
2012
International audience; This article presents a multispectral imaging system which, coupled with a neural network-based algorithm, reconstructs reflectance cubes. The reflectance spectra are obtained using artificial neural-netwok reconstruction which generates reflectance cubes from acquired multispectral images. Then, a blind source separation algorithm based on Non-negative Matrix Factorization is used for the decomposition of human skin absorption spectra in its main pigments: melanin and hemoglobin. The analysis is performed on reflectance spectra. The implemented source separation algorithm is based on a multiplicative coefficient upload. The goal is to represent a given spectrum as t…
Spiking patterns emerging from wave instabilities in a one-dimensional neural lattice.
2003
The dynamics of a one-dimensional lattice (chain) of electrically coupled neurons modeled by the FitzHugh-Nagumo excitable system with modified nonlinearity is investigated. We have found that for certain conditions the lattice exhibits a countable set of pulselike wave solutions. The analysis of homoclinic and heteroclinic bifurcations is given. Corresponding bifurcation sets have the shapes of spirals twisting to the same center. The appearance of chaotic spiking patterns emerging from wave instabilities is discussed.
Data-based modeling of vehicle collisions by nonlinear autoregressive model and feedforward neural network
2013
Vehicle crash test is the most direct and common method to assess vehicle crashworthiness. Visual inspection and obtained measurements, such as car acceleration, are used, e.g. to examine impact severity of an occupant or to assess overall car safety. However, those experiments are complex, time-consuming, and expensive. We propose a method to reproduce car kinematics during a collision using nonlinear autoregressive (NAR) model which parameters are estimated by the use of feedforward neural network. NAR model presented in this study is derived from the more general one - nonlinear autoregressive with moving average (NARMA). Suitability of autoregressive systems for data-based modeling was …
Advances in photonic reservoir computing
2017
We review a novel paradigm that has emerged in analogue neuromorphic optical computing. The goal is to implement a reservoir computer in optics, where information is encoded in the intensity and phase of the optical field. Reservoir computing is a bio-inspired approach especially suited for processing time-dependent information. The reservoir’s complex and high-dimensional transient response to the input signal is capable of universal computation. The reservoir does not need to be trained, which makes it very well suited for optics. As such, much of the promise of photonic reservoirs lies in their minimal hardware requirements, a tremendous advantage over other hardware-intensive neural net…
Exponential synchronization of master-slave neural networks with time-delays
2009
This paper establishes an exponential H ∞ synchronization method for a class of master and slave neural networks (MSNNs) with mixed time-delays, where the delays comprise different neutral, discrete and distributed time-delays and the class covers the Lipschitz-type nonlinearity case. By introducing a novel discretized Lyapunov-Krasovskii functional in order to minimize the conservatism in the stability problem of the system and also using some free weighting matrices, new delay-dependent sufficient conditions are derived for designing a delayed state-feedback control as a synchronization law in terms of linear matrix inequalities (LMIs). The controller guarantees the exponential H ∞ synchr…