QUANTAL MEASUREMENT AND ANALYSIS-METHODS COMPARED FOR CRAYFISH AND DROSOPHILA NEUROMUSCULAR-JUNCTIONS, AND RAT HIPPOCAMPUS

Citation
Rl. Cooper et al., QUANTAL MEASUREMENT AND ANALYSIS-METHODS COMPARED FOR CRAYFISH AND DROSOPHILA NEUROMUSCULAR-JUNCTIONS, AND RAT HIPPOCAMPUS, Journal of neuroscience methods, 61(1-2), 1995, pp. 67-78
Citations number
39
Categorie Soggetti
Neurosciences
ISSN journal
01650270
Volume
61
Issue
1-2
Year of publication
1995
Pages
67 - 78
Database
ISI
SICI code
0165-0270(1995)61:1-2<67:QMAACF>2.0.ZU;2-A
Abstract
Quantal content of transmission was estimated for three synaptic syste ms (crayfish and Drosophila neuromuscular junctions, and rat dentate g yrus neurons) with three different methods of measurement: direct coun ts of released quanta, amplitude measurements of evoked and spontaneou s events, and charge measurements of evoked and spontaneous events. At the crayfish neuromuscular junction, comparison of the three methods showed that estimates from charge measurements were closer to estimate s from direct counts, since amplitude measurements were more seriously affected by variable latency in evoked release of quantal units. Thus , charge measurements are better for estimating quantal content when d irect counts cannot be made, as in crayfish at high frequency of stimu lation or in the dentate gyrus neurons. At the Drosophila neuromuscula r junction, there is almost no latency variation of quantal release in realistic physiological solutions, and the methods based upon amplitu des and charge give similar results. Distributions of evoked synaptic quantal events obtained by direct counts at the crayfish neuromuscular junction were compared to statistical distributions obtained by best fits. Binomial distributions with uniform or non-uniform probabilities of release generally provided good fits to the observations. From bes t fit distributions, the quantal parameters n (number of release sites ) and p (their probability of release) can be calculated. We used two algorithms to estimate n and p: one allows for non-uniform probability of release and uses a modified chi-square (chi(2)) criterion, and the second assumes uniform probability of release and derives parameters from maximum likelihood estimation (MLE). The bootstrap estimate of st andard errors is used to determine the accuracy of n and p estimates.