NON-GAUSSIAN NOISE- AND COUPLING-INDUCED FIRING TRANSITIONS OF NEWMAN-WATTS NEURONAL NETWORKS

In this Letter, we study firing transitions induced by a particular kind of non-Gaussian noise (NGN) and coupling in Newman-Watts small-world neuronal networks. It is found that chaotic bursting can be tamed by the coupling and evolves to regular spiking or bursting behavior as the coupling increases. As the NGN's deviation from Gaussian noise changes, the neurons exhibit firing transitions from irregular spiking to regular bursting, and the number of spikes inside per burst varies with the change of the deviation. These results show that the NGN and the coupling play crucial roles in the firing activity of the neurons, and hence are of great importance to the information processing and transmission in the neuronal networks.

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NON-GAUSSIAN NOISE-INDUCED FIRING TRANSITIONS AND ORDERED BURSTING IN A THERMO-SENSITIVE NEURON

Fluctuation and Noise Letters ◽

10.1142/s0219477510000216 ◽

2010 ◽

Vol 09 (03) ◽

pp. 289-299 ◽

Cited By ~ 2

Author(s):

YUBING GONG ◽

XIU LIN ◽

YINGHANG HAO ◽

YANHANG XIE ◽

XIAOGUANG MA

Keyword(s):

Information Processing ◽

Gaussian Noise ◽

Correlation Time ◽

Colored Noise ◽

Firing Activity ◽

Firing Behavior ◽

Gaussian Colored Noise ◽

Non Gaussian

In this letter, we investigate how a particular kind of non-Gaussian colored noise (NGN), especially the correlation time τ and the departure q from Gaussian noise, affects the chaotic firing behavior in a thermo-sensitive neuron. It is found that transitions between spiking and bursting occur with changing τ or q, and ordered bursting appears when τ is optimal. As τ is increased, the neuron alternately exhibits spiking and bursting when q < 1, but always bursts when q > 1, and chaotic bursts may become ordered at an optimal τ. As q is increased, the neuron also exhibits transitions between spiking and bursting. These findings provide a new mechanism for the firing transitions in the neuron and present the constructive role of the NGN in the firing activity in the neuron. This reveals that the NGN would play subtle roles in the communication and information processing in the neurons.

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ENHANCEMENT OF INTRINSIC SPIKING COHERENCE BY EXTERNAL NON-GAUSSIAN NOISE IN A STOCHASTIC HODGKIN–HUXLEY NEURON

Fluctuation and Noise Letters ◽

10.1142/s0219477511000624 ◽

2011 ◽

Vol 10 (04) ◽

pp. 359-369 ◽

Cited By ~ 1

Author(s):

LI WANG ◽

YUBING GONG ◽

XIU LIN

Keyword(s):

Information Processing ◽

Gaussian Distribution ◽

Gaussian Noise ◽

Correlation Time ◽

Temporal Coherence ◽

Channel Noise ◽

Coherence Resonance ◽

Non Gaussian ◽

Proper Values ◽

Membrane Patch

In this paper, we study the effect of external non-Gaussian noise on the temporal coherence of the intrinsic spiking induced by the channel noise in a stochastic Hodgkin–Huxley neuron. It is found that, for a sufficiently large membrane patch, the intrinsic spiking coherence can be enhanced by the proper values of non-Gaussian noise's strength, correlation time, or deviation from Gaussian distribution. And that the intrinsic spiking can exhibit coherence resonance when the noise's strength is optimal. This implies that the channel noise-induced intrinsic spiking may become more or the most ordered in time with the assistance of the external non-Gaussian noise. These results show that the external non-Gaussian noise can play a constructive role for improving the time precision of information processing in stochastic neurons.

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Effects of autapse and ion channel block on the collective firing activity of Newman–Watts small-world neuronal networks

Physica A Statistical Mechanics and its Applications ◽

10.1016/j.physa.2017.05.049 ◽

2017 ◽

Vol 486 ◽

pp. 386-396 ◽

Cited By ~ 7

Author(s):

Rukiye Uzun ◽

Ergin Yilmaz ◽

Mahmut Ozer

Keyword(s):

Ion Channel ◽

Neuronal Networks ◽

Small World ◽

Channel Block ◽

Firing Activity

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CONSTRUCTIVE ACTION OF ADDITIVE NOISE IN OPTIMAL DETECTION

International Journal of Bifurcation and Chaos ◽

10.1142/s0218127405013824 ◽

2005 ◽

Vol 15 (09) ◽

pp. 2985-2994 ◽

Cited By ~ 14

Author(s):

FRANÇOIS CHAPEAU-BLONDEAU ◽

DAVID ROUSSEAU

Keyword(s):

Information Processing ◽

White Noise ◽

Stochastic Resonance ◽

Gaussian Noise ◽

Additive Noise ◽

Optimal Detection ◽

Processing Conditions ◽

Noise Optimization ◽

Additive White Noise ◽

Non Gaussian

The optimal detection of a signal of known form hidden in additive white noise is examined in the framework of stochastic resonance and noise-aided information processing. Conditions are exhibited where the performance in the optimal detection increases when the level of the additive (non-Gaussian bimodal) noise is raised. On the additive signal–noise mixture, when a threshold quantization is performed prior to the optimal detection, another form of improvement by noise can be obtained, with subthreshold signals and Gaussian noise. Optimization of the quantization threshold shows that even in symmetric detection settings, the optimal threshold can be away from the center of symmetry and in subthreshold configuration of the signals. These properties concerning non-Gaussian noise and nonlinear preprocessing in optimal detection, are meaningful to the current exploration of the various modalities and potentialities of stochastic resonance.

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PERIODIC COUPLING STRENGTH-ENHANCED COHERENCE RESONANCE INDUCED BY A PARTICULAR KIND OF NON-GAUSSIAN NOISE IN NEURONAL NETWORKS

Fluctuation and Noise Letters ◽

10.1142/s0219477512500290 ◽

2012 ◽

Vol 11 (04) ◽

pp. 1250029

Author(s):

YUBING GONG ◽

LI WANG ◽

BO XU

Keyword(s):

Complex Networks ◽

Coupling Strength ◽

Gaussian Noise ◽

Refractory Period ◽

Neuronal Networks ◽

Coherence Resonance ◽

Non Gaussian ◽

Time Periodic ◽

Spiking Activity

In this Letter, we study the effect of time-periodic coupling strength (TPCS) on the coherence resonance (CR) of spiking behavior induced by a particular kind of non-Gaussian noise in Newman–Watts networks of Hodgkin–Huxley neurons. It is found that the CR by the non-Gaussian noise can be enhanced by TPCS when TPCS frequency is equal to or multiple of the inverse of the refractory period, and can occur in networks with more random shortcuts for TPCS than for constant coupling strength. Furthermore, the CR by the non-Gaussian noise can occur at smaller TPCS frequency when network randomness increases. These results show that the CR by the non-Gaussian noise can be enhanced by TPCS and can occur in more complex networks in case of TPCS. These findings may help to better understand the joint roles of the non-Gaussian noise and TPCS in the spiking activity of the neuronal networks.

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