Channel noise and synchronization in excitable membranes

DOI10.1016/S0378-4371(03)00195-XzbMath1026.92012arXivphysics/0601063OpenAlexW3105772356WikidataQ59461299 ScholiaQ59461299MaRDI QIDQ1394649

Igor Goychuk, Gerhard Schmid, Peter Hänggi

Publication date: 23 June 2003

Published in: Physica A (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/physics/0601063

zbMATH Keywords

stochastic Hodgkin-Huxley modelexternally applied periodic signalspiking activity

Mathematics Subject Classification ID

Neural biology (92C20)

Related Items (14)

Stochastic resonance, coherence resonance, and spike timing reliability of Hodgkin-Huxley neurons with ion-channel noise ⋮ Robust stabilization design of nonlinear stochastic partial differential systems: fuzzy approach ⋮ Intrinsic coherence resonance in excitable membrane patches ⋮ Collective temporal coherence for subthreshold signal encoding on a stochastic small-world Hodgkin-Huxley neuronal network ⋮ The dynamics of small excitable ion channel clusters ⋮ Stochastic resonance on Newman-Watts networks of Hodgkin-Huxley neurons with local periodic driving ⋮ Synchronized firing of FitzHugh–Nagumo neurons by noise ⋮ Noise induced complexity: From subthreshold oscillations to spiking in coupled excitable systems ⋮ Optimal network size for Hodgkin-Huxley neurons ⋮ Effect of channel noise on the time-course of recovery from inactivation of sodium channels ⋮ Control of noise-induced oscillations by delayed feedback ⋮ Noise-induced synchronization in a lattice Hodgkin-Huxley neural network ⋮ Unnamed Item ⋮ Multiple coherence resonance induced by time-periodic coupling in stochastic Hodgkin–Huxley neuronal networks

Cites Work

• Unnamed Item
• Chaotic states in a random world: Relationship between the nonlinear differential equations of excitability and the stochastic properties of ion channels
• Characterization of the anticipated synchronization regime in the coupled FitzHugh-Nagumo model for neurons
• Frequency and phase synchronization in stochastic systems
• Nonlinear dynamics of chaotic and stochastic systems. Tutorial and modern developments

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