The presence of internal feedback pathways (IFP) is an ubiquitous yet unexplained phenomenon in the brain. Motivated by experimental observations on 1) motor-related signals in visual areas, and 2) massively distributed processing in the brain, we approach this problem from a sensorimotor standpoint and make use of distributed optimal controllers to explain IFP. We use the System Level Synthesis (SLS) controller to model neuronal phenomena such as signaling delay, local processing, and local reaction. Based on the SLS controller, we make qualitative theoretical predictions about IFP that has strong alignment with experimental and imaging studies. In particular, we introduce a necessary `mesocircuit' for optimal performance with distributed and local processing, and local disturbance rejection; this `mesocircuit' requires extreme amounts of IFP and memory for proper function. This is the first theory that can replicate the massive amounts of IFP in the brain purely from a priori principles, providing a new and promising theoretical basis upon which we can build to better understand the inner workings of the brain.