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Cerebral Cortex, Vol. 9, No. 7, 722-732, October 1999
© 1999 Oxford University Press

Estimation of the Number of Synapses in the Cerebral Cortex: Methodological Considerations

Javier DeFelipe1, Pilar Marco1, Ignacio Busturia2 and Angel Merchán-Pérez1,2

1 Instituto Cajal (CSIC), 28002 Madrid and , 2 Universidad Europea de Madrid, Villaviciosa de Odón, 28670 Madrid, Spain

In the present work we discuss several sampling procedures commonly used for counting synapses in the cerebral cortex. We compare, within the same tissue, two frequently used sterereological methods for determining the numerical density of synapses per unit volume, using as an example the estimation of the number of types of synapses by layers in the neuropil of the adult human temporal neocortex. These two methods are a size–frequency method (formula NA/d) and the disector method ({Sigma}Q/a x h). Since the size–frequency method is assumption-based and the disector method is considered to be an unbiased method, the latter is often recommended for the quantification of synapses and other objects. We obtained, however, similar estimates for the numerical density of the different types of synapses using both methods, although they presented different technical difficulties and statistical properties. In addition, we show that the size–frequency method is more efficient and easier to apply than the disector method. Nevertheless, there are other methods for quantification which may also be valid, depending on the aim of the research; but the data reported in many articles are often complicated, which makes it very difficult for the reader to follow all the steps of the calculation. If certain basic information were given, this would facilitate the interpretation and sharing of important information with other laboratories, regardless of the method used for quantification. Finally, based on our present results and previous literature, we propose a simple general protocol for estimating the numerical synaptic density by volume in the neuropil of the cerebral cortex.


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