  The presence of internal feedback pathways (IFPs) is a prevalent 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 IFPs. We
use the System Level Synthesis (SLS) controller to model neural phenomena such
as signaling delay, local processing, and local reaction. Based on the SLS
controller, we make qualitative predictions about IFPs that strongly align with
existing experimental observations. We introduce a `mesocircuit' for optimal
performance with distributed and local processing, and local disturbance
rejection; this mesocircuit requires extreme amounts of IFPs and memory for
proper function. This is the first theory that replicates the massive amounts
of IFPs in the brain purely from a priori principles, providing a new
theoretical basis upon which we can build to better understand the inner
workings of the brain.
