Wanner A A, Kirschmann M A, Genoud C
Friedrich Miescher Institute for Biomedical Research, Maulbeerstrasse 66, 4058, Basel, Switzerland.
J Microsc. 2015 Aug;259(2):137-142. doi: 10.1111/jmi.12244. Epub 2015 Apr 23.
Serial block-face scanning electron microscopy (SBEM) is becoming increasingly popular for a wide range of applications in many disciplines from biology to material sciences. This review focuses on applications for circuit reconstruction in neuroscience, which is one of the major driving forces advancing SBEM. Neuronal circuit reconstruction poses exceptional challenges to volume EM in terms of resolution, field of view, acquisition time and sample preparation. Mapping the connections between neurons in the brain is crucial for understanding information flow and information processing in the brain. However, information on the connectivity between hundreds or even thousands of neurons densely packed in neuronal microcircuits is still largely missing. Volume EM techniques such as serial section TEM, automated tape-collecting ultramicrotome, focused ion-beam scanning electron microscopy and SBEM (microtome serial block-face scanning electron microscopy) are the techniques that provide sufficient resolution to resolve ultrastructural details such as synapses and provides sufficient field of view for dense reconstruction of neuronal circuits. While volume EM techniques are advancing, they are generating large data sets on the terabyte scale that require new image processing workflows and analysis tools. In this review, we present the recent advances in SBEM for circuit reconstruction in neuroscience and an overview of existing image processing and analysis pipelines.
连续块面扫描电子显微镜(SBEM)在从生物学到材料科学等众多学科的广泛应用中越来越受欢迎。本综述聚焦于神经科学中用于电路重建的应用,这是推动SBEM发展的主要驱动力之一。神经元电路重建在分辨率、视野、采集时间和样品制备方面对体电子显微镜提出了特殊挑战。绘制大脑中神经元之间的连接对于理解大脑中的信息流和信息处理至关重要。然而,关于紧密排列在神经元微电路中的数百甚至数千个神经元之间连接性的信息仍在很大程度上缺失。诸如连续切片透射电子显微镜、自动胶带收集超薄切片机、聚焦离子束扫描电子显微镜和SBEM(切片机连续块面扫描电子显微镜)等体电子显微镜技术,能够提供足够的分辨率来解析诸如突触等超微结构细节,并为神经元电路的密集重建提供足够的视野。虽然体电子显微镜技术在不断进步,但它们正在生成数TB规模的大数据集,这需要新的图像处理工作流程和分析工具。在本综述中,我们展示了SBEM在神经科学电路重建方面的最新进展以及现有图像处理和分析流程的概述。