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Title

Non-Markovian stochastic resonance: Three-state model of ion channel gating

AuthorsGoychuk, Igor; Hänggi, Peter; Vega, J. L.; Miret-Artés, Salvador
Issue Date2005
PublisherAmerican Physical Society
CitationPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics 71: 1-11 (2005)
AbstractStochastic resonance in single voltage-dependent ion channels is investigated within a three-state non-Markovian modeling of the ion channel conformational dynamics. In contrast to a two-state description one assumes the presence of an additional closed state for the ion channel which mimics the manifold of voltage-independent closed subconformations (inactivated >state>). The conformational transition into the open state occurs through a domain of voltage-dependent closed subconformations (closed >state>). At distinct variance with the standard two-state and also the three-state Markovian approach, the inactivated state is characterized by a broad, nonexponential probability distribution of corresponding residence times. The linear response to a periodic voltage signal is determined for arbitrary distributions of the channel's recovery times. Analytical results are obtained for the spectral amplification of the applied signal and the corresponding signal-to-noise ratio. Alternatively, these results are also derived by use of a corresponding two-state non-Markovian theory which is based on driven integral renewal equations [I. Goychuk and P. Hänggi, Phys. Rev. E 69, 021104 (2004)]. The non-Markovian features of stochastic resonance are studied for a power law distribution of the residence time intervals in the inactivated state which exhibits a large variance. A comparison with the case of biexponentially distributed residence times possessing the same mean value, i.e., the simplest non-Markovian two-state description, is also presented. © 2005 The American Physical Society.
URIhttp://hdl.handle.net/10261/75767
DOI10.1103/PhysRevE.71.061906
Identifiersdoi: 10.1103/PhysRevE.71.061906
issn: 1539-3755
Appears in Collections:(CFMAC-IFF) Artículos
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