title: Extracellular space preservation aids the connectomic analysis of neural circuits.
abstract: Dense connectomic mapping of neuronal circuits is limited by the time and effort required to analyze 3D electron microscopy (EM) datasets. Algorithms designed to automate image segmentation suffer from substantial error rates and require significant manual error correction. Any improvement in segmentation error rates would therefore directly reduce the time required to analyze 3D EM data. We explored preserving extracellular space (ECS) during chemical tissue fixation to improve the ability to segment neurites and to identify synaptic contacts. ECS preserved tissue is easier to segment using machine learning algorithms, leading to significantly reduced error rates. In addition, we observed that electrical synapses are readily identified in ECS preserved tissue. Finally, we determined that antibodies penetrate deep into ECS preserved tissue with only minimal permeabilization, thereby enabling correlated light microscopy (LM) and EM studies. We conclude that preservation of ECS benefits multiple aspects of the connectomic analysis of neural circuits.
authors.affiliation: Circuit Dynamics and Connectivity Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, United States.
authors.forename: Marta
authors.identifier: http://orcid.org/0000-0001-7694-0398
authors.initials: M
authors.lastname: Pallotto
authors.affiliation: Circuit Dynamics and Connectivity Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, United States.
authors.forename: Paul V
authors.initials: PV
authors.lastname: Watkins
authors.affiliation: Circuit Dynamics and Connectivity Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, United States.
authors.forename: Boma
authors.initials: B
authors.lastname: Fubara
authors.affiliation: Department of Biology, University of Maryland, College Park, United States.
authors.forename: Joshua H
authors.initials: JH
authors.lastname: Singer
authors.affiliation: Circuit Dynamics and Connectivity Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, United States.|Department of Biomedical Optics, Max Planck Institute for Medical Research, Heidelberg, Germany.
authors.forename: Kevin L
authors.initials: KL
authors.lastname: Briggman
mesh_terms: D000818:Animals; D063132:Connectome / Q000379:methods*; D005110:Extracellular Space; D021621:Imaging, Three-Dimensional / Q000379:methods; D008810:Mice, Inbred C57BL; D013048:Specimen Handling / Q000379:methods*; D014021:Tissue Preservation / Q000379:methods
keywords: connectomics; extracellular space; gap junction; machine learning; mouse; neuroscience; tissue fixation