Calverley R K, Bedi K S, Jones D G
Department of Anatomy, University of Otago Medical School, Dunedin, New Zealand.
J Neurosci Methods. 1988 Apr;23(3):195-205. doi: 10.1016/0165-0270(88)90003-9.
The numerical density of synapses in the molecular layer of the parietal cortex of normal 28-day-old rats has been estimated by using two stereological methods, namely an unfolding technique and the disector method. For the unfolding technique it was assumed that the synapses formed a polydispersed population of disc-shaped particles. The technique also relies upon various assumptions regarding the size, shape and projection of synapses in the plane of section, these assumptions producing a result that is biased to an unknown extent. Such simplifying assumptions are unnecessary for the disector method. The mean +/- S.E.M. numerical density of synapses was found to be 2.16 +/- 0.14 x 10(9)/mm3 using the disector method. This was not significantly different (paired t-test; P less than 0.05) from the value of 2.41 +/- 0.22 x 10(9)/mm3 obtained using the unfolding technique with correction for truncation ('lost caps'). When the unfolding method was used without a correction for lost caps the numerical density was 1.98 +/- 0.10 x 10(9)/mm3, a value also not significantly different from that obtained using the disector method. The mean projected height (Hs) of the synaptic particles was also determined using both procedures; the results were not significantly different. When the variances of the final estimates and the time taken to carry out the procedures described were taken into account, it was estimated that the disector method was about 86% more efficient than the unfolding method with capping correction. Although the unfolding method can give essentially similar values for the numerical density of synapses to those obtained by the disector method, it is biased and much less efficient. It is concluded, therefore, that the disector method is the superior method for the estimation of the number and size of particles such as synapses, particularly when they have complex spatial configurations.
