This sounds like an excellent analysis project.
I have been thinking about three different lines that may give you some things to think about.
I think think that at the most basic level the older brain structures are the initiating force that drives behavior. A baby is mostly a bundle of uncoordinated instincts that drive actions before the cortex is trained to deal with the world.
As the encoding/learning progresses islands of learning form in the various maps and are refined as you continue to experience the world and are “surprised” by things that are different than the previously learned items.
Please look at the Calvin references at the bottom of this post. HTM neurons with Mexican hat connection distribution/sampling are perfect for forming the hex patterns described as a basic unit of organization:
The popular school of thought on distributed/deep learning usually starts from the intuitive approach that the meanings in each map forms automatically which cascades up through the layers to build up to higher level representations. This paper makes a compelling case for the opposite approach - the high-level representation is pushed down through the layers. While this paper focuses on the vision system I can see the concepts described being appropriate throughout the cortex. If you think of this with the lizard brain as the driver for the top-down trainer suddenly a whole bunch of things fall into place:
Deep Predictive Learning: A Comprehensive Model of Three Visual Streams
Randall C. O’Reilly, Dean R. Wyatte, and John Rohrlich