A systematic random sampling scheme optimized to detect the proportion of rare synapses in the neuropil

Abstract

Synapses can only be morphologically identified by electron microscopy and this is often a very labor intensive and time consuming task. When quantitative estimates are required for pathways that contribute a small proportion of synapses to the neuropil, the problems of accurate sampling are particularly severe and the total time required may become prohibitive. Here we present a sampling method devised to count the percentage of rarely-occurring synapses in the neuropil using a large sample (~1000 sampling sites), with the strong constraint of doing it in reasonable time. The strategy, which uses the unbiased physical disector technique, resembles that used in particle physics to detect rare events.
We validated our method in the primary visual cortex of the cat, where we used Biotinylated Dextran-amine to label thalamic afferents and measured the density of their synapses using the physical disector method. Our results show that we could obtain accurate counts of the labeled synapses, even when they represented only 0.2% of all the synapses in the neuropil.