Schmitz C, Hof P R
Department of Anatomy and Cell Biology, RWTH University of Aachen, Pauwelsstrasse/Wendlingweg 2, 52057, Aachen, Germany.
J Chem Neuroanat. 2000 Oct;20(1):93-114. doi: 10.1016/s0891-0618(00)00066-1.
Any investigation of the total number of neurons in a given brain region must first address the following questions. What is the best method for estimating the total number of neurons? What are the validity and the expected precision of the obtained data? What precision must the estimates attain with respect to the scientific question? In the present study, these questions were addressed using a computer simulation. Virtual brain regions with various spatial distributions of virtual neurons were modeled. The total numbers of virtual neurons in the modeled brain regions were repeatedly estimated by simulation of modern design-based stereology, either by using the 'fractionator' method or by the established method based on the product of estimated neuron density and estimated volume of the reference space. We show that estimates of total numbers of neurons obtained using the fractionator are from a statistical and economical standpoint more efficient than corresponding estimates obtained using the density/volume procedure. Furthermore, the use of two simple prediction methods (one for homogeneous and the other for clustered neuron distributions) permits satisfactory predictions about the variation of presumably any estimates of total numbers of neurons obtained using the fractionator. Finally, we show that assessing the reliability of estimates of mean total neuronal numbers using the ratio between the mean of the squared coefficients of error of the estimates and the squared coefficient of variation of the estimated total neuronal numbers, a frequently employed method in stereological studies, is neither useful nor informative. The present results may constitute a new set of recommendations for the rigorous usage of design-based stereology. In particular, we strongly recommend counting considerably more neurons than is currently done in the literature when estimating total neuronal numbers using design-based stereology.
对给定脑区中神经元总数的任何研究都必须首先解决以下问题。估计神经元总数的最佳方法是什么？所获数据的有效性和预期精度如何？就科学问题而言，估计需要达到何种精度？在本研究中，通过计算机模拟解决了这些问题。对具有不同空间分布虚拟神经元的虚拟脑区进行建模。通过现代基于设计的体视学模拟，使用“分数法”或基于估计神经元密度与参考空间估计体积乘积的既定方法，反复估计建模脑区中虚拟神经元的总数。我们表明，从统计和经济角度来看，使用分数法获得的神经元总数估计比使用密度/体积法获得的相应估计更有效。此外，使用两种简单的预测方法（一种用于均匀分布的神经元，另一种用于聚集分布的神经元）可以对使用分数法获得的大概任何神经元总数估计的变化做出令人满意的预测。最后，我们表明，使用估计值的误差平方系数均值与估计的总神经元数的变异系数平方之比来评估平均总神经元数估计的可靠性，这是体视学研究中常用的方法，既无用也无信息价值。本研究结果可能构成一套关于严格使用基于设计的体视学的新建议。特别是，我们强烈建议在使用基于设计的体视学估计总神经元数时，计数的神经元数量要比目前文献中的做法多得多。
