Mixture estimation and the neurophysiological quantal hypothesis

Quantal release models provide a mechanistic description of the process by which neurotransmitter is released from the nerve cell. The usual such model assumes that the quantity of transmitter released after nerve depolarization follows a finite mixture distribution with an unknown number of components, and with constraints on component means and variances. General procedures for estimating the dimension of a finite mixture model are discussed, and applied to the analysis of a quantal release data set.