Output layer as described in "A Theory of How Columns in the Neocortex Enable Learning the Structure of the World"

Reading through the paper it seems obvious to me (please correct me if I am wrong) that that the structure of the Input Layer of a column is equivalent to the (mini)Column, Cells, Connections, etc. objects of the NUPIC library and are acted on by the standard SP and TM algorithms:

In the first set of simulations the input layer of each column consists of 150 mini-columns, with 16 cells per mini-column, for a total of 2,400 cells.

I do not see, though, a corresponding data structure/algorithm for the Output layer of the column as described in the paper in the NUPIC code:

The output layer of each column consists of 4,096 cells, which are not arranged in mini-columns.

Is there code for this paper that illustrates the Output Layer? If not, is there any guidance/psuedo code for connecting the Output Layer to the Input Layer and for growing/removing connections to other Output cells in the column or other columns?

Thanks.

4 posts were merged into an existing topic: A Theory of How Columns in the Neocortex Enable Learning the Structure of the World