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1.
Small-World Connections to Induce Firing Activity and Phase Synchronization in Neural Networks 下载免费PDF全文
We investigate how the firing activity and the subsequent phase synchronization of neural networks with smallworld topological connections depend on the probability p of adding-links. Network elements are described by two-dimensional map neurons (2DMNs) in a quiescent original state. Neurons burst for a given coupling strength when the topological randomness p increases, which is absent in a regular-lattice neural network. The bursting activity becomes frequent and synchronization of neurons emerges as topological randomness further increases. The maximal firing frequency and phase synchronization appear at a particular value of p. However, if the randomness p further increases, the firing frequency decreases and synchronization is apparently destroyed. 相似文献
2.
根据实际生物神经网络具有小世界连接和神经元之间的连接强度随时间变化的特点,首先构造了一个以Hodgkin-Huxley方程为节点动力学模型的动态变权小世界生物神经网络模型,然后研究了该模型神经元的兴奋特性、权值变化特点和不同的学习系数对神经元的兴奋统计特性的影响.最有意义的结果是,在同样的网络结构、网络参数及外部刺激信号的条件下,学习系数b存在一个最优值b*,使生物神经网络的兴奋度在b=b*时达到最大.
关键词:
动态变权生物神经网络
小世界网络
Hodgkin-Huxley方程 相似文献
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4.
The harmonic stochastic resonance-enhanced signal detecting in Newman-Watts small-world neural network is studied using the Hodgkin-Huxley dynamical equation with noise.If the connection probability p,coupling strength g syn and noise intensity D matches well,higher order resonance will be found and an optimal signal-to-noise ratio will be obtained.Then,the reasons are given to explain the mechanism of this appearance. 相似文献
5.
D. Q. Wei X. S. Luo Y. L. Zou 《The European Physical Journal B - Condensed Matter and Complex Systems》2008,63(2):279-282
We investigate how firing activity of complex neural
networks depends on the random long-range connections and coupling
strength. Network elements are described by excitable
space-clamped FitzHugh-Nagumo (SCFHN) neurons with the values of
parameters at which no firing activity occurs. It is found that
for a given appropriate coupling strength C, there exists a
critical fraction of random connections (or randomness) p*,
such that if p > p* the firing neurons, which are absent in the
nearest-neighbor network, occur. The firing activity becomes
more frequent as randomness p is
further increased. On the other hand, when the p is smaller,
there are no active neurons in network, no matter what the value
of C is. For a given larger p, there exist optimal coupling
strength levels, where firing activity reaches its maximum. To the
best of our knowledge, this is a novel mechanism for the emergence
of firing activity in neurons. 相似文献
6.
We study the dependence of synchronization transitions in small-world networks of bursting neurons with hybrid electrical–chemical synapses on the information transmission delay, the probability of electrical synapses, and the rewiring probability. It is shown that, irrespective of the probability of electrical synapses, the information transmission delay can always induce synchronization transitions in small-world neuronal networks, i.e., regions of synchronization and nonsynchronization appear intermittently as the delay increases. In particular, all these transitions to burst synchronization occur approximately at integer multiples of the bursting period of individual neurons. In addition, for larger probability of electrical synapses, the intermittent synchronization transition is more profound, due to the stronger synchronization ability of electrical synapses compared with chemical ones. More importantly, chemical and electrical synapses can perform complementary roles in the synchronization of hybrid small-world neuronal networks: the larger the electrical synapse strength is, the smaller the chemical synapse strength needed to achieve burst synchronization. Furthermore, the small-world topology has a significant effect on the synchronization transition in hybrid neuronal networks. It is found that increasing the rewiring probability can always enhance the synchronization of neuronal activity. The results obtained are instructive for understanding the synchronous behavior of neural systems. 相似文献
7.
We investigate how dynamical behaviours of complex motor networks depend on the Newman-Watts small-world (NWSW) connections. Network elements are described by the permanent magnet synchronous motor (PMSM) with the values of parameters at which each individual PMSM is stable. It is found that with the increase of connection probability p, the motor in networks becomes periodic and falls into chaotic motion as p further increases. These phenomena imply that NWSW connections can induce and enhance chaos in motor networks. The possible mechanism behind the action of NWSW connections is addressed based on stability theory. 相似文献
8.
9.
We derive an exact representation of the topological effect on the dynamics of sequence processing neural networks within signal-to-noise analysis. A new network structure parameter, loopiness coefficient, is introduced to quantitatively study the loop effect on network dynamics. A large loopiness coefficient means a high probability of finding loops in the networks. We develop recursive equations for the overlap parameters of neural networks in terms of their loopiness. It was found that a large loopiness increases the correlation among the network states at different times and eventually reduces the performance of neural networks. The theory is applied to several network topological structures, including fully-connected, densely-connected random, densely-connected regular and densely-connected small-world, where encouraging results are obtained. 相似文献
10.
We investigate how firing activity
of globally coupled neural network depends on the coupling strength C and system size N. Network elements are described by space-clamped FitzHugh-Nagumo (SCFHN) neurons with the values
of parameters at which no firing activity occurs. It is found that for a given appropriate coupling strength, there is an intermediate range of system size where the firing activity of
globally coupled SCFHN neural network is induced and enhanced. On the other hand, for a given intermediate system size level, there exists an optimal value of coupling strength such that the intensity of firing activity reaches its maximum. These phenomena
imply that the coupling strength and system size play a vital role
in firing activity of neural network. 相似文献
11.
We study the phenomenon of stochastic resonance on Newman-Watts small-world networks consisting of biophysically realistic Hodgkin-Huxley neurons with a tunable intensity of intrinsic noise via voltage-gated ion channels embedded in neuronal membranes. Importantly thereby, the subthreshold periodic driving is introduced to a single neuron of the network, thus acting as a pacemaker trying to impose its rhythm on the whole ensemble. We show that there exists an optimal intensity of intrinsic ion channel noise by which the outreach of the pacemaker extends optimally across the whole network. This stochastic resonance phenomenon can be further amplified via fine-tuning of the small-world network structure, and depends significantly also on the coupling strength among neurons and the driving frequency of the pacemaker. In particular, we demonstrate that the noise-induced transmission of weak localized rhythmic activity peaks when the pacemaker frequency matches the intrinsic frequency of subthreshold oscillations. The implications of our findings for weak signal detection and information propagation across neural networks are discussed. 相似文献
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13.
Complete and phase synchronization in a heterogeneous small-world neuronal network 总被引:1,自引:0,他引:1 下载免费PDF全文
Synchronous firing of neurons is thought to be important for
information communication in neuronal networks. This paper
investigates the complete and phase synchronization in a
heterogeneous small-world chaotic Hindmarsh--Rose neuronal network.
The effects of various network parameters on synchronization
behaviour are discussed with some biological explanations. Complete
synchronization of small-world neuronal networks is studied
theoretically by the master stability function method. It is shown
that the coupling strength necessary for complete or phase
synchronization decreases with the neuron number, the node degree
and the connection density are increased. The effect of
heterogeneity of neuronal networks is also considered and it is
found that the network heterogeneity has an adverse effect on
synchrony. 相似文献
14.
Eva Koscielny-Bunde 《Journal of statistical physics》1990,58(5-6):1257-1266
The effect of damage on the pattern recognition in the Hopfield-model of neural networks is studied. It is assumed that in a damaged network the synaptic efficaciesJ
i,j=Jj,i, between pairs of neuronsS
i andS
j follow the Hebb rule with probability (1–p) and are equal to zero with probabilityp. Numerical simulations are performed for a net consisting of 400 neurons. It is investigated in detail how the retrieval of noisy patterns and the storage capacity of the net depends, for varying initial noise, on the concentrationp of the damaged synaptic efficacies. 相似文献
15.
C. Grabow S. Grosskinsky M. Timme 《The European Physical Journal B - Condensed Matter and Complex Systems》2011,84(4):613-626
Synchrony is one of the most common dynamical states emerging on networks. The speed of
convergence towards synchrony provides a fundamental collective time scale for
synchronizing systems. Here we study the asymptotic synchronization times for directed
networks with topologies ranging from completely ordered, grid-like, to completely
disordered, random, including intermediate, partially disordered topologies. We extend the
approach of master stability functions to quantify synchronization times. We find that the
synchronization times strongly and systematically depend on the network topology. In
particular, at fixed in-degree, stronger topological randomness induces faster
synchronization, whereas at fixed path length, synchronization is slowest for intermediate
randomness in the small-world regime. Randomly rewiring real-world neural, social and
transport networks confirms this picture. 相似文献
16.
In this paper, we investigate the effect of a high-frequency driving on the dynamical response of excitable neuronal systems to a subthreshold low-frequency signal by numerical simulation. We demonstrate the occurrence of vibrational resonance in spatially extended neuronal networks. Different network topologies from single small-world networks to modular networks of small-world subnetworks are considered. It is shown that an optimal amplitude of high-frequency driving enhances the response of neuron populations to a low-frequency signal. This effect of vibrational resonance of neuronal systems depends extensively on the network structure and parameters, such as the coupling strength between neurons, network size, and rewiring probability of single small-world networks, as well as the number of links between different subnetworks and the number of subnetworks in the modular networks. All these parameters play a key role in determining the ability of the network to enhance the outreach of the localized subthreshold low-frequency signal. Considering that two-frequency signals are ubiquity in brain dynamics, we expect the presented results could have important implications for the weak signal detection and information propagation across neuronal systems. 相似文献
17.
L. Yuan L. L. Xiang Y. H. Kong M. W. Lu Z. J. Lan A. H. Zeng Z. Y. Wang 《The European Physical Journal B - Condensed Matter and Complex Systems》2012,85(1):8
In this paper, we study the effect of time-periodic coupling strength (TPCS) and network
connection degree ⟨k⟩ on the temporal coherence of the chaotic
bursting of the scale-free networks of thermo-sensitive neurons. It is found that the
chaotic bursting becomes ordered and can exhibit coherence resonance (CR) when TPCS
amplitude ε
0 or the network connection
degree ⟨k⟩ is varied. In particular, the neuronal bursting may
exhibit multiple CR (MCR) behavior when TPCS frequency ω is varied. It is
also found that, as ⟨k⟩ is increased, the value
of ε
0 for the MCR decreases, but the frequency for the MCR
almost keeps unchanged. These results show that the chaotic bursting can be tamed and the
bursting temporal coherence can be enhanced and even optimized by TPCS and network
connection degree. Furthermore, TPCS can repetitively enhance and even optimize the
temporal coherence of the neuronal bursting behavior. These findings may help to better
understand the roles of TPCS and network connection degree for improving the time
precision of the information processing in neuronal networks. 相似文献
18.
We study the stochastic resonance (SR) in Hodgkin-Huxley (HH) neural systems with small-world (SW) connections under the noise synaptic current and periodic stimulus, focusing on the dependence of properties of SR on coupling strength c. It is found that there exists a critical coupling strength c^* such that if c 〈 c^*, then the SR can appear on the SW neural network. Especially, dependence of the critical coupling strength c^* on the number of neurons N shows the monotonic even almost linear increase of c^* as N increases and c^* on the SW network is smaller than that on the random network. For the effect of the SW network on the phenomenon of SR, we show that decreasing the connection-rewiring probability p of the network topology leads to an enhancement of SR. This indicates that the SR on the SW network is more prominent than that on the random network (p = 1.0). In addition, it is noted that the effect becomes remarkable as coupling strength increases. Moreover, it is found that the SR weakens but resonance range becomes wider with the increase of c on the SW neural network. 相似文献
19.
The effect of small-world connection and noise on the formation and transitionof spiral wave in the networks of Hodgkin-Huxley neurons are investigated in detail. Some interesting results are found in our numerical studies. i) The quiescent neurons are activated to propagate electric signal to others by generating and developing spiral wave from spiral seed in small area. ii) A statistical factor is defined to describe the collective properties and phase transition induced by the topology of networks and noise. iii) Stable rotating spiral wave can be generated and keeps robust when the rewiring probability is below certain threshold, otherwise, spiral wave can not be developed from the spiral seed and spiral wave breakup occurs for a stable rotating spiral wave. iv) Gaussian white noise is introduced on the membrane of neuronsto study the noise-induced phase transition on spiral wave in small-world networks of neurons. It is confirmed that Gaussian white noise plays active role in supporting and developing spiral wave in the networks of neurons, and appearance of smaller factor of synchronization indicates high possibility to induce spiral wave. 相似文献
20.
WEI Du-Qu LUO Xiao-Shu 《理论物理通讯》2007,48(4):759-762
In this paper, we investigate coherence resonance (CR) and noise-induced synchronization in Hindmarsh- Rose (HR) neural network with three different types of topologies: regular, random, and small-world. It is found that the additive noise can induce CR in HR neural network with different topologies and its coherence is optimized by a proper noise level. It is also found that as coupling strength increases the plateau in the measure of coherence curve becomes broadened and the effects of network topology is more pronounced simultaneously. Moreover, we find that increasing the probability p of the network topology leads to an enhancement of noise-induced synchronization in HR neurons network. 相似文献