Biomaterial Database

Multiple coherence resonance induced by time-periodic coupling in stochastic Hodgkin-Huxley neuronal networks. 2011

Xiu Lin, and Yubing Gong, and Li Wang

School of Physics, Ludong University, Yantai, Shandong 264025, China.

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.

UI	MeSH Term	Description	Entries
D008959	Models, Neurological	Theoretical representations that simulate the behavior or activity of the neurological system, processes or phenomena; includes the use of mathematical equations, computers, and other electronic equipment.	Neurologic Models,Model, Neurological,Neurologic Model,Neurological Model,Neurological Models,Model, Neurologic,Models, Neurologic
D009415	Nerve Net	A meshlike structure composed of interconnecting nerve cells that are separated at the synaptic junction or joined to one another by cytoplasmic processes. In invertebrates, for example, the nerve net allows nerve impulses to spread over a wide area of the net because synapses can pass information in any direction.	Neural Networks (Anatomic),Nerve Nets,Net, Nerve,Nets, Nerve,Network, Neural (Anatomic),Networks, Neural (Anatomic),Neural Network (Anatomic)
D009474	Neurons	The basic cellular units of nervous tissue. Each neuron consists of a body, an axon, and dendrites. Their purpose is to receive, conduct, and transmit impulses in the NERVOUS SYSTEM.	Nerve Cells,Cell, Nerve,Cells, Nerve,Nerve Cell,Neuron
D002462	Cell Membrane	The lipid- and protein-containing, selectively permeable membrane that surrounds the cytoplasm in prokaryotic and eukaryotic cells.	Plasma Membrane,Cytoplasmic Membrane,Cell Membranes,Cytoplasmic Membranes,Membrane, Cell,Membrane, Cytoplasmic,Membrane, Plasma,Membranes, Cell,Membranes, Cytoplasmic,Membranes, Plasma,Plasma Membranes
D003198	Computer Simulation	Computer-based representation of physical systems and phenomena such as chemical processes.	Computational Modeling,Computational Modelling,Computer Models,In silico Modeling,In silico Models,In silico Simulation,Models, Computer,Computerized Models,Computer Model,Computer Simulations,Computerized Model,In silico Model,Model, Computer,Model, Computerized,Model, In silico,Modeling, Computational,Modeling, In silico,Modelling, Computational,Simulation, Computer,Simulation, In silico,Simulations, Computer
D006801	Humans	Members of the species Homo sapiens.	Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000200	Action Potentials	Abrupt changes in the membrane potential that sweep along the CELL MEMBRANE of excitable cells in response to excitation stimuli.	Spike Potentials,Nerve Impulses,Action Potential,Impulse, Nerve,Impulses, Nerve,Nerve Impulse,Potential, Action,Potential, Spike,Potentials, Action,Potentials, Spike,Spike Potential
D001683	Biological Clocks	The physiological mechanisms that govern the rhythmic occurrence of certain biochemical, physiological, and behavioral phenomena.	Biological Oscillators,Oscillators, Endogenous,Pacemakers, Biological,Biologic Clock,Biologic Oscillator,Biological Pacemakers,Clock, Biologic,Clocks, Biological,Oscillator, Biologic,Oscillators, Biological,Pacemaker, Biologic,Pacemakers, Biologic,Biologic Clocks,Biologic Oscillators,Biologic Pacemaker,Biologic Pacemakers,Biological Clock,Biological Oscillator,Biological Pacemaker,Clock, Biological,Clocks, Biologic,Endogenous Oscillator,Endogenous Oscillators,Oscillator, Biological,Oscillator, Endogenous,Oscillators, Biologic,Pacemaker, Biological
D015233	Models, Statistical	Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc.	Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model
D059629	Signal-To-Noise Ratio	The comparison of the quantity of meaningful data to the irrelevant or incorrect data.	Ratio, Signal-To-Noise,Ratios, Signal-To-Noise,Signal To Noise Ratio,Signal-To-Noise Ratios