Based on our theory & methods for community detection and community comparison in graphs (Lyzinski et al. 2015),
we formulate a model selection procedure for deciding whether
a hierarchical stochastic blockmodel graph supports the hypothesis of repeated motifs.
Such a graph inference procedure provides a framework for addressing a fundamental outstanding question
regarding the atoms of neural computation (Marcus et al. 2014).