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Recent studies have suggested that endogenous electric fields can not only be considered as an observation window of neural activities but also form a feedback on membranes of adjacent cells which implies it may play an important role in network dynamic behaviors. However, the role of endogenous field feedback in the detectability of external weak signal is still unknown. In this study, we introduced...
This paper means to explore the application of input-output feedback linearization method to control the model-based firing behavior. The Pinsky-Rinzel (PR) model is used to develop the feedback controller. The epileptiform behavior is modeled by the high frequency burst of 29 Hz and the normal desired behavior is modeled by the periodic firing of 6 Hz. The epilepsy treatment is formulated as a classic...
In this paper, we investigate the effects of the network amplification on stochastic resonance in a randomly connected neural network. The network consists of excitatory and inhibitory neurons with similar ratio as that in the mammalian neocortex and the axonal conduction delays between neurons are also considered. Numerical results elucidate that the resonance in the neural network is just the expression...
The ISAR (inverse synthetic aperture radar) imaging technology is an important tool for the ballistic missile midcourse target recognitions. Considering the rotationally symmetric targets, the sparse representation model of the ballistic midcourse targets with micro-motion is established. The sparse recovery algorithm named SBL (Sparse Bayesian Learning) is analyzed, which can provide a much sparser...
Nerve cells communicate by generating and transmitting action potentials. Annihilation of neural oscillation by functional electrical stimulation is a promising treatment modality in neural diseases. In this paper, a robust adaptive fuzzy tracking control is proposed for stochastic Hodgkin-Huxley (HH) neuron systems to generate a desired reference response in spite of environmental noises, uncertain...
This paper addresses the problem of simultaneous estimation of the topological structure and unknown parameters of uncertain general complex networks from noisy time series. Usually the complex networks consist of known node models with some unknown parameters and uncertain topological structure. At the same time, only partial states with heavy noise can be observed in real-world complex networks...
This paper investigated propagation of firing rate in multi-layer feedforward network (FFN) based on FitzHugh-Nagumo (FHN) neuron model. It is found that the signal propagate in the multi-layer FFN almost linearity by synchronized firing. Noise and high-frequency stimuli can improve the linearity, especially for the low input rate. High frequency signal plays an important role in signal propagation...
How much influence could noise take in FHN neuron which is exposed to a weak periodic signal is deeply affected by its bifurcation parameter. By a series of simulations, the authors derive the effective region of the bifurcation parameter, in which system could be influenced by noise apparently. Ulteriorly, it is divided into three part, namely, suprathreshold, subthreshold and canard effective region...
We study the nonlinear response of the HodgkinHuxley model without external periodic signal to Gaussian white noise (GWN) and Ornstein-Uhlenbeck noise (OUN) as synaptic current respectively near the saddle-node bifurcation of limit cycles. The coherence of the system, estimated from the Coefficient of Variation of interspike interval of membrane potentials and spike trains, is minimal at certain noise...
In this paper, a hybrid control strategy, variable universe adaptive fuzzy sliding mode control, is proposed to realize the chaos synchronization of two gap junction coupled FitzHugh-Nagumo (FHN) neurons under external electrical stimulation. According to the Lyapunov stability theory, the stability of the closed error system is guaranteed. The control scheme is robust to the uncertainties such as...
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