When neuroscientists reconstruct brain networks, they often do not know how to index the neurons in order reveal the underlying structure of the connections between neurons. How can a mathematician help in this case? It turns out that by studying the eigenvalues of the connectivity matrix, we can in fact derive a metric that classifies small-world networks using information from the spectrum. This is yet one more case in which we see the beauty and usefulness of eigenvalues.