The members of his committee are as follows:

Reconstructing neural circuitry has the potential to reveal fundamental principles of brain function and intelligence. This work attempts to improve neural circuit reconstruction from electron microscopy (EM), study the resulting data, and release these data to the public for further study.

A major result of this work is the implementation of an automated system for inferring the connectivity between neurons within large scale EM image volumes. This system was used to detect over 300 million synapses in the largest connectivity map extracted using EM to date. These results were also judged to be highly accurate by a team of independent evaluators.

A separate major goal of this work has been the public release of EM reconstructions for study by the scientific community after performing our own computational analyses to illustrate their utility. As one example, we combine the connectivity inference techniques above with an automated reconstruction of neuronal mitochondria to analyze the relationship between input synaptic density and mitochondrial density.

The final chapter will explore an automated system to detect the errors of automated circuit reconstruction within large EM image volumes. In this presentation, I will review all of the work summarized above and consider potential paths forward on this final task.