I’ve just read the wikipedia entry on neural darwinism.
The last part of the theory attempts to explain how we experience spatiotemporal consistency in our interaction with environmental stimuli. Edelman proposes a model of reentrant signaling whereby a disjunctive, multimodal sampling of the same stimulus event correlated in time leads to self-organizing intelligence. Put another way, multiple neuronal groups can be used to sample a given stimulus set in parallel and communicate between these disjunctive groups with incurred latency.
The index i in ( hi, Xi ) may be time itself. In this case, the calculation of majority and veto in the Pattern Engine can be done by a simple integrator. When the integrated majority vote is high enough, the result is fed back into storage. A veto or high feedback activity will quench the feedback path.
Update: We may start with some spaces Xi and increase their number by:
The effects of glueing along a temporal index will look like prediction.
The theory of neural darwinism has been criticised on the ground that there is selection but no reproduction in this system ( Wikipedia). This is food for thought.