  We investigate joint graph inference for the chemical and electrical
connectomes of the \textit{Caenorhabditis elegans} roundworm. The
\textit{C.elegans} connectomes consist of $253$ non-isolated neurons with known
functional attributes, and there are two types of synaptic connectomes,
resulting in a pair of graphs. We formulate our joint graph inference from the
perspectives of seeded graph matching and joint vertex classification. Our
results suggest that connectomic inference should proceed in the joint space of
the two connectomes, which has significant neuroscientific implications.
