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Invited Talk

Petascale connectomics and beyond

H. Sebastian Seung

Moderator s: H. Sebastian Seung · Surya Ganguli


A connectome represents brain connectivity as a directed graph in which nodes are neurons and edges are synapses. The connectome of C. elegans was reconstructed from electron microscopic images in the 1970s and 80s, but the manual labor of image analysis was prohibitive. Convolutional nets were applied to automate image analysis starting in the 2000s, and are now the basis of computational systems engineered to handle petascale datasets.

The connectome of the fruit fly Drosophila is expected in 2023. Cubic millimeter volumes of cerebral cortex have also been reconstructed. The explosion of connectomic information is revealing innate structures of nervous systems, and is expected to constrain theories of how brains learn. An exascale project to reconstruct an entire mouse brain connectome is now being planned, and depends on improving the accuracy of automated image analysis by confronting a long tail of failure modes, including diverse kinds of image artifacts.

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