Yanhang Xie

Synchronization transitions on complex thermo-sensitive neuron networks with time delays

We have numerically studied the firing synchronization transitions on random thermo-sensitive neuron networks in dependence on information transmission delay tau, network randomness p, and coupling strength g. It is found that as tau is increased the neurons can exhibit transitions from burst synchronization (BS) to clustering anti-phase synchronization (APS), and further to spike synchronization (SS). It is also found that, with increasing p or g, there are transitions from spatiotemporal chaos to BS, then to APS, and finally to SS. However, the APS state with p or g exists only for intermediate tau values within a narrow range. For tau values outside this range, the APS state does not appear and the firings change directly from spatiotemporal chaos to BS or SS. These results show that, as time delay can do, network topology and coupling strength can also cause complex synchronization transitions in the neurons. In particular, the novel phenomenon of APS state with p or g shows that, with the help of appropriate random connections or coupling strength, the neurons may exhibit the APS behavior at a certain time delay for which the APS does not appear originally. These findings imply that time delay, network randomness, and coupling strength may have subtle effects on the firing behaviors on neuronal networks, and thus could play important roles in the information processing in neural systems.

Transition and enhancement of synchronization by time delays in stochastic Hodgkin-Huxley neuron networks

In this paper, we study the effect of time delay on spiking synchronizations in Newman-Watts networks of stochastic Hodgkin-Huxley (HH) neurons. It is found that as @t is increased, the neurons exhibit transitions from spiking synchronization (SS) to clustering anti-phase synchronization (APS) and back to SS. Furthermore, the SS after the APS is enhanced with increasing time delay. For different patch sizes (channel noise strength), network randomness (fraction of random connections), and coupling strengths, the neurons exhibit similar synchronization transitions and the APS always occurs at around @t=4, representing that the time delay-induced APS behavior is robust to the channel noise, the number of random connections, and the coupling strength. A simple explanation for this phenomenon was given in terms of the relation of spiking time-period and time delay values. Since the information processing in the neurons are fulfilled by the spiking activity of the membrane potential and the spiking synchronization plays a crucial role in the spiking activity, our results may help us understand the effect of time delay as well as the interplay of channel noise and time delay on the spiking activity and hence the information processing in stochastic neuronal systems.

Non-Gaussian noise-optimized intracellular cytosolic calcium oscillations

We have numerically studied the effect of a particular kind of non-Gaussian colored noise (NGN), characterized by the deviation q from Gaussian noise (q=1), on intracellular cytosolic calcium (Ca(2+)) oscillations. It is found that, as q is increased, the Ca(2+) oscillation regularity increases and reaches a best performance at an optimal q, and then decreases with further increasing q, which represents the occurrence of coherence resonance, i.e., the most regular Ca(2+) oscillations. Similar phenomena occur for different values of noise intensity and correlation time of the NGN. This phenomenon of deviation-optimized Ca(2+) oscillations show that, external non-Gaussian noises of different types can enhance and even optimize the intracellular Ca(2+) oscillations. This result provides new insights into the constructive roles and potential applications of non-Gaussian noises in intracellular cytosolic Ca(2+) oscillations.

Enhancement of stochastic oscillations by colored noise or internal noise in NO reduction by CO on small platinum surfaces

In this paper, based on the stochastic model of NO reduction by CO on Pt crystal surfaces and taking Gaussian colored noise as external fluctuations of the NO partial pressure, we study the effect of the colored noise on the internal noise-induced stochastic oscillations (INSOs) and the effect of internal noise on the colored noise-induced stochastic oscillations (CNSOs). It is found that the INSO can be enhanced by the colored noise with appropriate correlation time or noise strength and, interestingly, the CNSO can be enhanced by the internal noise as well and, moreover, the enhanced CNSO can reach the best oscillatory states repetitively via proper internal noises. This effect of the internal noise is different from its effect on the stochastic oscillations induced by the external Gaussian white noise, which probably results from the interaction of the correlated colored noise and the internal noise.

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

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, 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.

NON-GAUSSIAN NOISE-ENHANCED INTRINSIC STOCHASTIC OSCILLATIONS IN CATALYTIC NO REDUCTION WITH CO ON SMALL-SIZE PT SURFACES

We numerically study the effect of a particular kind of non-Gaussian colored noise (NGN) on the intrinsic stochastic reaction rate oscillations (RRO) in NO reduction with CO on small-size Pt surfaces. It was found that the RRO can be enhanced by the appropriate noise strength, correlation time, in particular, the deviation of the NGN from Gaussian noise. Furthermore, there is an optimal NGN by which the RRO can be most greatly enhanced. This result shows that the RRO can be enhanced by different types of the NGN, and can reach the best oscillatory state by utilizing one optimal type of the noise. A simple explanation for the phenomenon is given.