On identification of Na+ channel gating schemes using moving-average filtered hidden Markov models

Transitions between distinct kinetic states of an ion channel are described by a Markov process. Hidden Markov models (HMM) have been successfully app lied in the analysis of single ion channel recordings with a small signal-t o-noise ratio. However, we have recently shown that the anti-aliasing low-p ass filter misleads parameter estimation. Here, we show for the case of a N a+ channel recording that the standard HMM do neither allow parameter estim ation nor a correct identification of the gating scheme. In particular, the number of closed and open states is determined incorrectly, whereas a modi fied HMM considering the anti-aliasing filter (moving-average filtered HMM) is able to reproduce the characteristic properties of the time series and to perform gating scheme identification.