Nature CommunicationsNeurosciencePeer-reviewed journal article
A Petascale Automated Imaging Pipeline for Mapping Neuronal Circuits with High-throughput Transmission Electron Microscopy
Wenjing YiniD, Derrick BrittainiD, Jay Borseth, Marie E. ScottiD, Derric Williams, Jedediah Perkins, Christopher S. Own, Matthew F. Murfitt, Russel TorresiD, Daniel Kapner, Gayathri MahalingamiD, Adam BleckertiD, Daniel Castelli, David ReidiD, Wei-Chung Allen LeeiD, Brett J. GrahamiD, Marc M. TakenoiD, Daniel J. BumbargeriD, Colin FarrelliD, R. Clay ReidiD, Nuno Maçarico da CostaiD
Abstract
Serial-section electron microscopy is the method of choice for studying cellular structure and network connectivity in the brain. We have built a pipeline of parallel imaging using transmission electron automated microscopes (piTEAM) that scales this technology and enables the acquisition of petascale datasets containing local cortical microcircuits. The distributed platform is composed of multiple transmission electron microscopes that image, in parallel, different sections from the same block of tissue, all under control of a custom acquisition software (pyTEM) that implements 24/7 continuous autonomous imaging. The suitability of this architecture for large scale electron microscopy imaging was demonstrated by acquiring a volume of more than 1 mm3 of mouse neocortex spanning four different visual areas. Over 26,500 ultrathin tissue sections were imaged, yielding a dataset of more than 2 petabytes. Our current burst imaging rate is 500 Mpixel/s (image capture only) per microscope and net imaging rate is 100 Mpixel/s (including stage movement, image capture, quality control, and post processing). This brings the combined burst acquisition rate of the pipeline to 3 Gpixel/s and the net rate to 600 Mpixel/s with six microscopes running acquisition in parallel, which allowed imaging a cubic millimeter of mouse visual cortex at synaptic resolution in less than 6 months.
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