Yinghang Hao

Multiple resonances with time delays and enhancement by non-Gaussian noise in Newman-Watts networks of Hodgkin-Huxley neurons

In this paper, we study the effect of time delay on the spiking activity in Newman-Watts small-world networks of Hodgkin-Huxley neurons with non-Gaussian noise, and investigate how the non-Gaussian noise affects the delay-induced behaviors. It was found that, as the delay increases, the neuron spiking intermittently performs the most ordered and synchronized behavior when the delay lengths are integer multiples of the spiking periods, which shows multiple temporal resonances and spatial synchronizations, and reveals that the locking between the delay lengths and the spiking periods might be the mechanism behind the behaviors. It was also found that the delay-optimized spiking behaviors could be enhanced when non-Gaussian noises deviation from the Gaussian noise is appropriate. These results show that time delay and non-Gaussian noise would cooperate to play more constructive and efficient roles in the information processing of neural networks.

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.

Influence of time delay and channel blocking on multiple coherence resonance in Hodgkin–Huxley neuron networks

Toxins such as tetraethylammonium (TEA) and tetrodotoxin (TTX) may reduce the number of working potassium and sodium ion channels by poisoning and making them blocked, respectively. In this paper, we study how channel blocking (CB) affects the time delay-induced multiple coherence resonance (MCR), i.e., a phenomenon that the spiking of neuronal networks intermittently reaches the most ordered state, in stochastic Hodgkin-Huxley neuron networks. It is found that potassium and sodium CB have distinct effects. For potassium CB, the MCR occurs more frequently as the CB develops, but for sodium CB the MCR is badly impaired and only the first coherence resonance (CR) holds and, consequently, the MCR evolves into a single CR as sodium CB develops. We found for sodium CB the spiking becomes disordered at larger delay lengths, which may be the reason for the destruction of the MCR. The underlying mechanism is briefly discussed in terms of distinct effects of potassium and sodium CB on the spiking activity. These results show that potassium CB can increase the frequency of MCR with time delay, but sodium CB may suppress and even destroy the delay-induced MCR. These findings may help to understand the joint effects of CB and time delay on the spiking coherence of neuronal networks.

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.

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 NGNs 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.

NON-GAUSSIAN NOISE-INDUCED COHERENCE RESONANCE OF CALCIUM OSCILLATIONS IN BIDIRECTIONALLY COUPLED CELLS

We have studied the effect of a particular kind of non-Gaussian noise (NGN), mainly of its deviation q from Gaussian noise, on the intercellular calcium (Ca2+) oscillations in an array of bidirectionally coupled cells. It is found that as q is increased, the Ca2+ oscillation becomes the most regular at an intermediate optimal q value, representing the occurrence of coherence resonance (CR). This deviation-induced CR behavior shows that the intercellular Ca2+ oscillations of the coupled cells can be enhanced and even optimized by the appropriate NGN. This result provides a new insight into the constructive role of the NGN on the transmission of Ca2+ signaling in coupled cells.

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.