Today’s streams were extremely helpful!
Minicolumns spanning layer 2,3 and 4 right away brought me back to long trusted Machine Intelligence basics, where ironically the same is true for how each unique Address location in a RAM has a Data column that can store more than one data type along its (data bus width) length.
Signal wise sensory of any kind including motor/muscle error bits connect to any of the Address input pins of RAM. The RAM is then changing address location in response to any change in sensor readings. Since result of Data actions are not known until one timestep later the system learns predictions.
In this model Data includes a Confidence level that increases to max of 3 if all is well after an action is tried, else decremented and when zero (including not yet used RAM location) stores a new guess in memory. To me this part of the process very much resembles spatial pooling!
Required spatial functions are all conveniently found in the lower layers. I think that there are too many similarities for this to be a coincidence.