title: Mixture estimation and the neurophysiological quantal hypothesis.
abstract: 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.
authors.affiliation: Department of Mathematics, Statistics and Computing Science, Dalhousie University, Halifax, Nova Scotia, Canada.
authors.forename: B R
authors.initials: BR
authors.lastname: Smith
mesh_terms: D000200:Action Potentials; D000818:Animals; D003400:Astacoidea; D004558:Electric Stimulation; D008433:Mathematics; D008959:Models, Neurological; D015233:Models, Statistical; D009462:Neurology / Q000379:methods*; D009469:Neuromuscular Junction / Q000502:physiology; D011336:Probability; D013569:Synapses / Q000502:physiology