Craig R. Forest, Ph.D., School of Mechanical Engineering, Georgia Institute of Technology
R. Clay Reid, M.D., Ph.D., Allen Institute for Brain Science
Machelle T. Pardue, Ph.D., School of Biomedical Engineering, Georgia Institute of Technology
Peter J. Yunker, Ph.D., School of Physics, Georgia Institute of Technology
Todd A. Sulchek, Ph.D., School of Mechanical Engineering, Georgia Institute of Technology
Batch processing of brain tissue sections for millimeter-scale serial section transmission electron microscopy connectomics
The field of connectomics has emerged a promising approach for exploring the nature of neural circuits. A millimeter-scale connectome—a neuron-to-neuron wiring diagram of a neural circuit—potentially contains significant information regarding information processing and memory. The field is held back, however, by the difficulty in consistently and rapidly collecting neuroanatomical datasets with serial section transmission electron microscopy (ssTEM). In the cerebral cortex, for instance, a local circuit is contained in a cubic millimeter, but single sections—obtained by cutting brain samples with a diamond knife—must be “ultrathin” (< 40 nanometers), thus requiring 25,000 consecutive sections to be processed. Currently, the processing of ultrathin sections remains an unsolved problem that is necessary for the advancement of ssTEM connectomics. In this work, I (1) design, model, and test a novel device that uses hydrodynamic forces and curvature-induced capillary interactions for the transport and trapping of ultrathin sections, (2) design, implement, and characterize batch processing of single sections to enable reliable processing of thousands of serial sections, and (3) design, test, and characterize automated batched section processing, enabling high-throughput and reliable section processing. In total, this work outlines a novel platform for section processing for millimeter-scale ssTEM connectomics studies.