Correlated noise induced spatiotemporal coherence resonance in a square lattice network

Sun, Xiaojuan; Lu, Qishao; Kurths, Jüergen

doi:10.1016/j.physa.2008.08.027

Cited by 32 publications

(15 citation statements)

References 36 publications

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“…Until recently, some studies have provided further insight into the important roles of SR and CR, such as the encoding and processing of information in the nervous system, the amplification of information transfer in excitable systems, controlling spontaneous spiking regularity via channel blocking on Hodgkin-Huxley (HH) neuron networks, spatial CR in neuronal media with discrete local dynamics and neuronal networks, as well as spatiotemporal CR in other neuronal networks. [30][31][32][33][34][35][36][37][38][39][40][41][42][43][44] It is known that information transmission in neural systems is fulfilled by coupled neurons and neuronal network, and the brain functional networks have character of small-world (SW) topology. SW networks comprise Watts-Strogatz 45 and Newman-Watts model.…”

Section: Introductionmentioning

confidence: 99%

Multiple coherence resonance induced by time-periodic coupling in stochastic Hodgkin–Huxley neuronal networks

Lin

Gong²,

Wang³

2011

Chaos: An Interdisciplinary Journal of Nonlinear Science

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In this paper, we study the effect of time-periodic coupling strength (TPCS) on the spiking coherence of Newman-Watts small-world networks of stochastic Hodgkin-Huxley (HH) neurons and investigate the relations between the coupling strength and channel noise when coherence resonance (CR) occurs. It is found that, when the amplitude of TPCS is varied, the spiking induced by channel noise can exhibit CR and coherence bi-resonance (CBR), and the CR moves to a smaller patch area (bigger channel noise) when the amplitude increases; when the frequency of TPCS is varied, the intrinsic spiking can exhibit CBR and multiple CR, and the CR always occurs when the frequency is equal to or multiple of the spiking period, manifesting as the locking between the frequencies of the intrinsic spiking and the coupling strength. These results show that TPCS can greatly enhance and optimize the intrinsic spiking coherence, and favors the spiking with bigger channel noise to exhibit CR. This implies that, compared to constant coupling strength, TPCS may play a more efficient role for improving the time precision of the information processing in stochastic neuronal networks.

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Section: Introductionmentioning

confidence: 99%

Multiple coherence resonance induced by time-periodic coupling in stochastic Hodgkin–Huxley neuronal networks

Lin

Gong²,

Wang³

2011

Chaos: An Interdisciplinary Journal of Nonlinear Science

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“…4,5,10,11 Of particular interest for the present work, due to the usage of the same mathematical model of neuronal dynamics, multiple resonances in the Rulkov neuronal model 12 have also been observed and reported. 13 Effects of correlated noise on the dynamics of coupled neurons have also been investigated thoroughly, 14,15,16,17,18 whereby the importance of different temporal and spatial correlation lengths has been firmly established.…”

Section: Introductionmentioning

confidence: 99%

Delay-induced multiple stochastic resonances on scale-free neuronal networks

Wang

Perc

Duan

et al. 2009

Chaos: An Interdisciplinary Journal of Nonlinear Science

241

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We study the effects of periodic subthreshold pacemaker activity and time-delayed coupling on stochastic resonance over scale-free neuronal networks. As the two extreme options, we introduce the pacemaker respectively to the neuron with the highest degree and to one of the neurons with the lowest degree within the network, but we also consider the case when all neurons are exposed to the periodic forcing. In the absence of delay, we show that an intermediate intensity of noise is able to optimally assist the pacemaker in imposing its rhythm on the whole ensemble, irrespective to its placing, thus providing evidences for stochastic resonance on the scale-free neuronal networks. Interestingly thereby, if the forcing in form of a periodic pulse train is introduced to all neurons forming the network, the stochastic resonance decreases as compared to the case when only a single neuron is paced. Moreover, we show that finite delays in coupling can significantly affect the stochastic resonance on scale-free neuronal networks. In particular, appropriately tuned delays can induce multiple stochastic resonances independently of the placing of the pacemaker, but they can also altogether destroy stochastic resonance. Delay-induced multiple stochastic resonances manifest as well-expressed maxima of the correlation measure, appearing at every multiple of the pacemaker period. We argue that fine-tuned delays and locally active pacemakers are vital for assuring optimal conditions for stochastic resonance on complex neuronal networks. It is well known that noise can play a constructive role in different types of nonlinear dynamical systems, and stochastic resonance is perhaps the most prominent example of this fact. The objective of this article is to extend the scope of stochastic resonance to complex networks, whereby the deterministic periodic input is not only limited in its strength but also its outreach. More precisely, scale-free neuronal networks are studied on which the subthreshold periodic forcing is introduced only to a single neuron of the network, thus acting as a pacemaker. We want to determine to what extent the complex scale-free topology can aid the pacemaker to entrain the complete neuronal ensemble with the help of fine-tuned additive noise. Moreover, the new findings are compared with results obtained via the more traditional setup where every neuron of the network is subjected to a weak periodic forcing. It is found that scale-free topologies are very efficient in propagating noise-supported localized weak rhythmic activities. Also, it is found that these paced networks are superior to globally forced networks in that stochastic resonance is better expressed on the former. Importantly, since time delays are inherent to the nervous system we take this explicitly into account via time-delayed coupling. We report on the occurrence of delay-induced multiple stochastic resonances on scale-free neuronal networks, which appear due to the locking between the delay length and the oscillation period of the pacemaker.

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“…For instance, Gaussian white noise can induce spike coherence in FitzHugh-Nagumo and Hodgkin-Huxley neuronal models; 5-7 the effects of correlated noise on spike coherence and spike firing rate of coupled neurons have also been investigated thoroughly. [8][9][10] Furthermore, small-world topology can induce synchronization and spike coherence in coupled Hodgkin-Huxley neuronal networks, 11,12 diversity of the neurons can enhance spike coherence in coupled Rulkov-map neuronal models, 13 and so on.…”

Section: Introductionmentioning

confidence: 99%

Delay-enhanced spatiotemporal order in coupled neuronal systems

Hou

Xin

2010

Chaos: An Interdisciplinary Journal of Nonlinear Science

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In a network of noisy neuron oscillators with time-delayed coupling, we uncover a phenomenon of delay-enhanced spatiotemporal order. We find that time delay in the coupling can dramatically enhance the temporal coherence and spatial synchrony of the noise-induced spike trains. In addition, if the delay time is tuned to nearly match the intrinsic spiking period of the neuronal network, both the coherence and the synchrony reach maximum levels, demonstrating an interesting type of resonance phenomenon with delay. Such findings are shown to be robust to the change of the noise intensity and the rewiring probability of small-world network.

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Correlated noise induced spatiotemporal coherence resonance in a square lattice network

Cited by 32 publications

References 36 publications

Multiple coherence resonance induced by time-periodic coupling in stochastic Hodgkin–Huxley neuronal networks

Multiple coherence resonance induced by time-periodic coupling in stochastic Hodgkin–Huxley neuronal networks

Delay-induced multiple stochastic resonances on scale-free neuronal networks

Delay-enhanced spatiotemporal order in coupled neuronal systems

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