Data from: Extracellular space preservation aids the connectomic analysis of neural circuits

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.