Abstract
A typical task in the application of aggregated Markov models to ion channel data is the estimation of the transition rates between the states. Realistic models for ion channel data often have one or more loops. We show that the transition rates of a model with loops are not identifiable if the model has either equal open or closed dwell times. This non-identifiability of the transition rates also has an effect on the estimation of the transition rates for models which are not subject to the constraint of either equal open or closed dwell times. If a model with loops has nearly equal dwell times, the Hessian matrix of its likelihood function will be ill-conditioned and the standard deviations of the estimated transition rates become extraordinarily large for a number of data points which are typically recorded in experiments.
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- Albertsen A., Hansen U. P. Estimation of kinetic rate constants from multi-channel recordings by a direct fit of the time series. Biophys J. 1994 Oct;67(4):1393–1403. doi: 10.1016/S0006-3495(94)80613-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Ball F. G., Sansom M. S. Ion-channel gating mechanisms: model identification and parameter estimation from single channel recordings. Proc R Soc Lond B Biol Sci. 1989 May 22;236(1285):385–416. doi: 10.1098/rspb.1989.0029. [DOI] [PubMed] [Google Scholar]
- Ball F. G., Yeo G. F., Milne R. K., Edeson R. O., Madsen B. W., Sansom M. S. Single ion channel models incorporating aggregation and time interval omission. Biophys J. 1993 Feb;64(2):357–374. doi: 10.1016/S0006-3495(93)81375-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Bates S. E., Sansom M. S., Ball F. G., Ramsey R. L., Usherwood P. N. Glutamate receptor-channel gating. Maximum likelihood analysis of gigaohm seal recordings from locust muscle. Biophys J. 1990 Jul;58(1):219–229. doi: 10.1016/S0006-3495(90)82367-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Chung S. H., Krishnamurthy V., Moore J. B. Adaptive processing techniques based on hidden Markov models for characterizing very small channel currents buried in noise and deterministic interferences. Philos Trans R Soc Lond B Biol Sci. 1991 Dec 30;334(1271):357–384. doi: 10.1098/rstb.1991.0122. [DOI] [PubMed] [Google Scholar]
- Chung S. H., Moore J. B., Xia L. G., Premkumar L. S., Gage P. W. Characterization of single channel currents using digital signal processing techniques based on Hidden Markov Models. Philos Trans R Soc Lond B Biol Sci. 1990 Sep 29;329(1254):265–285. doi: 10.1098/rstb.1990.0170. [DOI] [PubMed] [Google Scholar]
- Colquhoun D., Hawkes A. G. On the stochastic properties of single ion channels. Proc R Soc Lond B Biol Sci. 1981 Mar 6;211(1183):205–235. doi: 10.1098/rspb.1981.0003. [DOI] [PubMed] [Google Scholar]
- Colquhoun D., Hawkes A. G. Relaxation and fluctuations of membrane currents that flow through drug-operated channels. Proc R Soc Lond B Biol Sci. 1977 Nov 14;199(1135):231–262. doi: 10.1098/rspb.1977.0137. [DOI] [PubMed] [Google Scholar]
- Edeson R. O., Ball F. G., Yeo G. F., Milne R. K., Davies S. S. Model properties underlying non-identifiability in single channel inference. Proc Biol Sci. 1994 Jan 22;255(1342):21–29. doi: 10.1098/rspb.1994.0004. [DOI] [PubMed] [Google Scholar]
- Fredkin D. R., Rice J. A. Maximum likelihood estimation and identification directly from single-channel recordings. Proc Biol Sci. 1992 Aug 22;249(1325):125–132. doi: 10.1098/rspb.1992.0094. [DOI] [PubMed] [Google Scholar]
- Hamill O. P., Marty A., Neher E., Sakmann B., Sigworth F. J. Improved patch-clamp techniques for high-resolution current recording from cells and cell-free membrane patches. Pflugers Arch. 1981 Aug;391(2):85–100. doi: 10.1007/BF00656997. [DOI] [PubMed] [Google Scholar]
- Horn R., Lange K. Estimating kinetic constants from single channel data. Biophys J. 1983 Aug;43(2):207–223. doi: 10.1016/S0006-3495(83)84341-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Kienker P. Equivalence of aggregated Markov models of ion-channel gating. Proc R Soc Lond B Biol Sci. 1989 Apr 22;236(1284):269–309. doi: 10.1098/rspb.1989.0024. [DOI] [PubMed] [Google Scholar]
- Neher E., Sakmann B. Single-channel currents recorded from membrane of denervated frog muscle fibres. Nature. 1976 Apr 29;260(5554):799–802. doi: 10.1038/260799a0. [DOI] [PubMed] [Google Scholar]
- Song L., Magleby K. L. Testing for microscopic reversibility in the gating of maxi K+ channels using two-dimensional dwell-time distributions. Biophys J. 1994 Jul;67(1):91–104. doi: 10.1016/S0006-3495(94)80458-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Vandenberg C. A., Bezanilla F. A sodium channel gating model based on single channel, macroscopic ionic, and gating currents in the squid giant axon. Biophys J. 1991 Dec;60(6):1511–1533. doi: 10.1016/S0006-3495(91)82186-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Zimmer B. D., Bickel P., Dittrich A. Changes of simple somatic parameters by delta-9-trans-tetrahydrocannabinol (delta-9-THC) in a double-blind-study. Short communication. Arzneimittelforschung. 1976;26(8):1614–1616. [PubMed] [Google Scholar]