As a jumping off point for a biological implementation, just imagine that 1) one particular excitatory cell in each column fires every time its column is active and 2) all the cells in a layer receive both basal and distal inputs from their neighbors in the region.
1 is plausible enough, and it certainly doesn’t need to be precisely every time the column fires, just most of the time.
2 is very plausible, in fact I would argue more plausible than assuming that recurrent connections happen magically only on distal segments.
It would just be tweaked slightly if you wanted it to happen e.g. between two different layers.
The intuition for this kind of architecture is that the patterns a region is detecting are partly feedforward and partly temporal, very much analogous to the temporal memory algorithm in HTM. Liquid state machines, echo state networks, LSTMs, they all do this.