A petascale automated imaging pipeline for mapping neuronal circuits with high-throughput transmission electron microscopy
Wenjing Yin, Derrick Brittain, Jay Borseth, Marie Scott, Derric Williams, Jedediah Perkins, Christopher S. Own, Matthew F. Murfitt, Russel Torres, Daniel Kapner, Gayathri Mahalingam, Adam Bleckert, Daniel Castelli, David Reid, Wei-Chung Allen Lee, Brett J. Graham, Marc Takeno, Daniel J. Bumbarger, Colin Farrell, R. Clay Reid, Nuno Maçarico da Costa
Abstract
Abstract Electron microscopy (EM) is widely used for studying cellular structure and network connectivity in the brain. We have built a parallel imaging pipeline using transmission electron microscopes that scales this technology, implements 24/7 continuous autonomous imaging, and enables the acquisition of petascale datasets. The suitability of this architecture for large-scale imaging was demonstrated by acquiring a volume of more than 1 mm 3 of mouse neocortex, spanning four different visual areas at synaptic resolution, in less than 6 months. Over 26,500 ultrathin tissue sections from the same block were imaged, yielding a dataset of more than 2 petabytes. The combined burst acquisition rate of the pipeline is 3 Gpixel per sec and the net rate is 600 Mpixel per sec with six microscopes running in parallel. This work demonstrates the feasibility of acquiring EM datasets at the scale of cortical microcircuits in multiple brain regions and species.