MODEL PROPERTIES UNDERLYING NON-IDENTIFIABILITY IN SINGLE-CHANNEL INFERENCE

Models of ion channel kinetics subserve inferential methods applied to patch clamp data. For Markov models the density function of a sojourn time in a class of states is a mixture of exponentials. Determination of kinetic parameters from density functions may be complicated by no n-uniqueness of solutions. This non-identifiability is investigated an alytically for a class of two states, assuming detailed balance; relat ions between model properties, observable density parameters, and non- uniqueness are presented. The results are further developed in terms o f similarity transform methods. Additional information provided by joi nt distributions is discussed. An example is given where identifiabili ty of a model can be demonstrated explicitly. Attention is drawn to in stances where the number of components in a density function may be mi sleading when used to infer the number of underlying states.