AUTHOR=Nguyen Huy Bang , Thai Truc Quynh , Sui Yang , Azuma Morio , Fujiwara Ken , Ohno Nobuhiko TITLE=Methodological Improvements With Conductive Materials for Volume Imaging of Neural Circuits by Electron Microscopy JOURNAL=Frontiers in Neural Circuits VOLUME=12 YEAR=2018 URL=https://www.frontiersin.org/journals/neural-circuits/articles/10.3389/fncir.2018.00108 DOI=10.3389/fncir.2018.00108 ISSN=1662-5110 ABSTRACT=

Recent advancements in electron microscope volume imaging, such as serial imaging using scanning electron microscopy (SEM), have facilitated the acquisition of three-dimensional ultrastructural information of biological samples. These advancements help build a comprehensive understanding of the functional structures in entire organelles, cells, organs and organisms, including large-scale wiring maps of neural circuitry in various species. Advanced volume imaging of biological specimens has often been limited by artifacts and insufficient contrast, which are partly caused by problems in staining, serial sectioning and electron beam irradiation. To address these issues, methods of sample preparation have been modified and improved in order to achieve better resolution and higher signal-to-noise ratios (SNRs) in large tissue volumes. These improvements include the development of new embedding media for electron microscope imaging that have desirable physical properties such as less deformation in the electron beam and higher stability for sectioning. The optimization of embedding media involves multiple resins and filler materials including biological tissues, metallic particles and conductive carbon black. These materials alter the physical properties of the embedding media, such as conductivity, which reduces specimen charge, ameliorates damage to sections, reduces image deformation and results in better ultrastructural data. These improvements and further studies to improve electron microscope volume imaging methods provide options for better scale, quality and throughput in the three-dimensional ultrastructural analyses of biological samples. These efforts will enable a deeper understanding of neuronal circuitry and the structural foundation of basic and higher brain functions.