Department of Anatomy & Neuroscience, School of Medicine, Autónoma de Madrid University, Madrid, Spain.
Department of Biodiversity, ecology and evolution, Biomathematics Unit, Faculty of Biology, Complutense University of Madrid, Madrid, Spain.
PLoS Comput Biol. 2021 Dec 8;17(12):e1009051. doi: 10.1371/journal.pcbi.1009051. eCollection 2021 Dec.
Projection neurons are the commonest neuronal type in the mammalian forebrain and their individual characterization is a crucial step to understand how neural circuitry operates. These cells have an axon whose arborizations extend over long distances, branching in complex patterns and/or in multiple brain regions. Axon length is a principal estimate of the functional impact of the neuron, as it directly correlates with the number of synapses formed by the axon in its target regions; however, its measurement by direct 3D axonal tracing is a slow and labor-intensive method. On the contrary, axon length estimations have been recently proposed as an effective and accessible alternative, allowing a fast approach to the functional significance of the single neuron. Here, we analyze the accuracy and efficiency of the most used length estimation tools-design-based stereology by virtual planes or spheres, and mathematical correction of the 2D projected-axon length-in contrast with direct measurement, to quantify individual axon length. To this end, we computationally simulated each tool, applied them over a dataset of 951 3D-reconstructed axons (from NeuroMorpho.org), and compared the generated length values with their 3D reconstruction counterparts. The evaluated reliability of each axon length estimation method was then balanced with the required human effort, experience and know-how, and economic affordability. Subsequently, computational results were contrasted with measurements performed on actual brain tissue sections. We show that the plane-based stereological method balances acceptable errors (~5%) with robustness to biases, whereas the projection-based method, despite its accuracy, is prone to inherent biases when implemented in the laboratory. This work, therefore, aims to provide a constructive benchmark to help guide the selection of the most efficient method for measuring specific axonal morphologies according to the particular circumstances of the conducted research.
投射神经元是哺乳动物前脑中最常见的神经元类型，其个体特征是理解神经回路如何运作的关键步骤。这些细胞具有轴突，其分支延伸到长距离，以复杂的模式分支和/或在多个脑区分支。轴突长度是神经元功能影响的主要估计量，因为它与轴突在其靶区形成的突触数量直接相关；然而，通过直接 3D 轴突追踪进行测量是一种缓慢且劳动密集型的方法。相反，最近提出了轴突长度估计作为一种有效且易于使用的替代方法，允许快速了解单个神经元的功能意义。在这里，我们分析了最常用的长度估计工具的准确性和效率——基于虚拟平面或球体的设计立体学，以及 2D 投影轴突长度的数学校正——与直接测量相比，用于量化单个轴突长度。为此，我们通过计算模拟了每个工具，将它们应用于 951 个 3D 重建轴突的数据集（来自 NeuroMorpho.org），并将生成的长度值与它们的 3D 重建值进行比较。然后，根据所需的人力、经验和专业知识以及经济承受能力，平衡每种轴突长度估计方法的可靠性。随后，将计算结果与实际脑组织切片上的测量结果进行对比。我们表明，基于平面的立体学方法在稳健性方面平衡了可接受的误差（~5%）和偏差，而基于投影的方法尽管准确，但在实验室中实施时容易出现固有偏差。因此，这项工作旨在提供一个建设性的基准，帮助根据所进行研究的具体情况，选择最有效的方法来测量特定的轴突形态。
