Delay-induced coherence bi-resonance-like behavior in stochastic Hodgkin-Huxley neuron networks

In this paper,we study how information transmission delays affect the spiking behavior of electrically coupled stochastic Hodgkin-Huxley (HH) neurons on Newman-Watts networks.It is found that the spiking behavior becomes the most regular at an optimal time delay,indicating the occurrence of delay-induced coherence resonance-like (CR-like) behavior.Interestingly,there are different CR-like types,depending on the membrane patch size of the neuron.For a smaller patch size,only single CR-like behavior occurs;while for a larger patch size,coherence bi-resonance-like (CBR) behavior appears.These findings show that the delay-induced CR-like behavior is closely related to the channel noise strength,and the coupled neurons may exhibit different spiking behaviors under the interplay of the channel noise and time delay.Therefore,the channel noise should be taken into account in the study of time delay-related spiking activity in stochastic HH neurons.This work provides new insight into the role of channel noise and information transmission delays in realistic neural systems.

多稳态动力系统中随机共振的研究进展

非线性随机动力学是力学、数学、工程等多个领域关注的热点,在航空航天、机械工程、生物生态等领域有广泛的应用.多稳态动力系统作为其最重要的研究对象,在随机扰动下具有丰富的动力学行为,如随机分岔、随机共振等,尤其是随机共振,已经被应用于机械故障诊断、微弱信号检测和振动能量俘获等工程实际问题中.本文主要综述了多稳态动力系统中的随机共振理论、方法及工程应用.首先,通过几类典型的非线性随机动力学系统,介绍了随机共振的经典理论和度量指标;其次,重点阐述了多稳态动力学系统,尤其是三稳态和周期势系统,在各类噪声激励下的随机共振现象,分析了其诱发机理、演化规律和研究方法;最后,介绍了多稳态动力系统中随机共振的几类应用实例,并进一步给出了随机共振当前面临的难题和未来的发展趋势等开放性问题.

有限大小神经元细胞膜动作电位的温度效应

研究了温度对有限大小神经元细胞膜动作电位的影响.发现随着温度的增加,在相同的时间内神经元产生的脉冲数目有先增加再降低的变化.在中等面积下,平均脉冲间间隔有类似于共振的先降低,达到最小值,再增加的现象.通过计算功率谱以及由功率谱定义的β因子,很清楚地看到β在某些温度时达到了最大值,产生了相干共振.

Amplified Signal Response by Neuronal Diversity on Complex Networks

The effect of diversity on dynamics of coupled FitzHugh-Nagumo neurons on complex networks is numerically investigated, where each neuron is subjected to an external subthreshold signal. With the diversity the network is a mixture of excitable and oscillatory neurons, and the diversity is determined by the variance of the system＇s parameter. The complex network is constructed by randomly adding long-range connections （shortcuts） on a nearest-neighbouring coupled one-dimensional chain. Numerical results show that external signals are maximally magnified at an intermediate value of the diversity, as in the case of well-known stochastic resonance, burthermore, the effects of the number of shortcuts and coupled strength on the diversity-induced phenomena are also discussed. These findings exhibit that the diversity may play a constructive role in response to external signal, and highlight the importance of the diversity on such complex networks.

化学体系随机共振现象的理论研究

化学体系中随机共振现象的特性、机理、本质和应用的研究是非常重要的前沿课题。综述中国科学技术大学非线性化学实验室，在化学体系随机共振现象的理论研究中，所取得的主要成果，并阐述化学体系随机共振现象研究中所提出来的若干重要问题：非均相化学体系中随机共振；化学体系中内信号随机共振；化学体系中多重随机共振；化学体系中随机共振的调制；化学体系中色噪声作用下的随机共振；化学体系中时空随机共振；耦合化学体系中随机共振；化学体系中双参量随机共振。

Neural Signal Tuned by Random Long-range Connections in Coupled FitzHugh-Nagumo Neurons Systems

We investigate the effect of random long-range connections on signal propagation in an array of coupled FitzHugh- Nagumo （FHN） neurons. The neural network can be obtained by randomly adding a small fraction of shortcuts in an originally locally coupled one-dimensional chain. It is shown that when the first neuron is subjected to external stimuli, it fires and excites its connected neighbours, such that the neural signal may propagate along the chain favoured by the shortcuts. Moreover, there exists an optimal number of shortcuts which can lead to the most synchronous behaviour. In addition, how the region of the fraction of shortcuts varies with the coupling strength is also discussed. These results suggest that topological disorder in the neural network may play a vital role in helping information processing in living systems.

基于随机共振的大频率信号相干接收误码率研究

针对信道环境恶劣条件下的大频率数字信号相干接收问题,提出了一种基于调参随机共振系统降低数字信号相干接收误码率(BER)的方法。从时域、频域及误码率三个方面对大频率二进制相移键控(BPSK)信号的随机共振相干接收方法进行了研究。首先,通过调整系数R改变非线性随机共振系统的参数a、b,将其共振频率提高R倍,从而实现大频率信号的随机共振,提高信号的信噪比(SNR);然后,对通过随机共振系统后的信号进行相干解调,并计算误码率。试验结果表明,与传统解调方法相比,该方法的误码率在低信噪比情况下有明显降低,当SNR=-14 d B时,较传统解调系统误码率可降低25.28%。随机共振系统提高了信号相干接收性能。随机共振理论在信号接收解调及信号处理等方面存在优势。

Control of stochastic spike motion in an excitable system via recycled noise

The control effect of recycled noise,generated by the superposition of a primary Gaussian noise source and a secondary source with a constant delay,has been studied in an excitable FitzHugh-Nagumo system.We mainly focus on the performance of noise-induced spike and coherence resonance in a parameter region sub-threshold to supercritical Hopf bifurcation.For fixed noise intensity,simulations show that the coherence(quantitatively measured by R,which is defined as the mean value of the spike interval time T normalized to its mean square root) and the emission velocity of the noise-induced spikes exhibit damped oscillations with the variation of delay time,demonstrating a new kind of multi-resonance phenomenon.Furthermore,the optimal delay times for resonance and the fast emission velocity are related to the inherent frequency of the system.It seems that there are some synchronization effects between the dynamic character of the system and the delay time of recycled noise.Our results give clear information about how one can control the coherence and emission velocity of the noise-induced spike in a rather effective way,by deliberately adjusting the delay time and the fraction of the secondary noise.

Enhancement of spike coherence by the departure from Gaussian noise in a Hodgkin-Huxley neuron

Experimental study has shown that non-Gaussian noise exists in sensory systems like neurons.The departure from Gaussian behavior is a characteristic parameter of non-Gaussian noise.In this paper,we have numerically studied the effect of a particular kind of non-Gaussian colored noise(NGN),especially its departure q from Gaussian noise(q = 1),on the spiking activity in a deterministic Hodgkin-Huxley(HH) neuron driven by sub-threshold periodic stimulus.Simulation results show that the departure q can affect the spiking activity induced by noise intensity D.For smaller q values,the minimum in the variation coefficient(CV) as a function of noise intensity(D) becomes smaller,showing that D-induced stochastic resonance(SR) becomes strengthened.Meanwhile,depending on the value of D,q can either enhance or reduce the spiking regularity.Interestingly,CV changes non-monotonously with varying q and passes through a minimum at an intermediate q,representing the presence of "departure-induced SR".This result shows that appropriate departures of the NGN can enhance the spike coherence in the HH neuron.Since the departure of the NGN determines the probability distribution and hence may denote the type of the noise,"departure-induced SR" shows that different types of noise can enhance the spike coherence,and hence may improve the timing precision of sub-threshold signal encoding in the HH neuron.

Non-Gaussian noise-enhanced stochastic rate oscillations in CO oxidation on nanometer-sized Pd particles

The effect of non-Gaussian colored noise(NGN),mainly its departure q from the Gaussian noise,on the optimal ISRO of CO oxidation on nanometer-sized Pd particles was studied.It was found that the ISRO in the absence of external noise can still be enhanced when the NGN is applied.Specifically,the ISRO varies with changing q and becomes more regular at an appropriate q value,and when q is optimal,the ISRO becomes the most regular.Because the departure q from the Gaussian noise determines the probability distribution function and hence may denote the types of noise,this result shows that different types of external noise can enhance the ISRO of CO oxidation,and non-Gaussian noise may enhance the ISRO more greatly than the Gaussian noise.Therefore,non-Gaussian noise could play more effective roles in the catalytic process of CO oxidation on nanometer-sized Pd particles.

双稳态系统中随机共振和相干共振的相关性

研究了加性噪声和乘性噪声共同驱动的双稳态系统中的随机共振和相干共振现象.针对加性噪声和乘性噪声之间不存在关联性和存在关联性两种情形,引入一种适当的能同时表征随机共振和相干共振的指标,应用一阶欧拉方法,通过数值模拟对系统的随机共振和相干共振现象进行研究.结果表明在弱噪声驱动下,随着加性噪声强度的增加,当系统出现相干共振时,如果给系统外加一个弱周期驱动力,几乎在同一时刻,系统也出现了随机共振现象;但随着乘性噪声强度的增加,仅当加性噪声和乘性噪声之间相关时,此结论成立.并且系统参数对相干共振和随机共振的影响是一致的.

映射神经元前馈环网络基元中的随机共振和相干共振

采用映射神经元模型,通过数值模拟方法研究了由3个神经元组成的前馈环(Feed-Forward-Loop,FFL)网络基元中噪声对体系非线性动力学行为的影响.由3个神经元组成的前馈环网络基元,因神经元本身分为兴奋和抑制两种类型,共有8种不同的形式.通过对不同类型前馈环网络基元的数值模拟,在多种类型的前馈环中发现了随机共振及相干共振现象.在对不同前馈类型及不同耦合强度下的结果进行比较后,发现不同的前馈形式及耦合强度对体系的动力学行为有着非常重要的影响.