Like many other researchers, we believe that network architecture plays a significant role in generalization.1T. Poggio, J. Mutch, J. Leibo, and A. Tacchetti, “The computational magic of the ventral stream : sketch of a theory (and why some deep architectures work)” Computer Science and Artificial Intelligence Laboratory Technical Report, 2012. Many of our experiments are designed towards the question of uncovering insights related to network micro-architecture. We emphasize parts-based representations and compositionality, similar to several other researchers building grammar-based models. In addition, the organization of cortical micro-circuitry provides rich clues about the nature of potential modifications. Our efforts in this direction have already been very fruitful in discovering a new network architecture that provides tight control for invariance-selectivity tradeoffs.