Provided the network can successfully represent input sentences with words in novel syntactic positions, the model can be said to have achieved the cognitive goal - that of semantic systematicity. Memory Obviously the model needs to retain the structure of the current sentence. Additionally, the model must retain information on the general apparent structure of sentences. Clearly the memory for the bindings of words and concepts is realized in the form of the strengths of connections between the input and semantic layers. The case of recalling general sentence sequence is less clear.
Bindings take place between the most active unbound concept and thematic role nodes.
The most active role node is that which is unbound and receives the largest boost from the p-node core. That is, the node with the strongest connection with the p-node core. When a concept is activated it will attempt to bind to the most active site node. As the sequence of input is always constant a word presented in a novel position will be bound according to the expected role in the sequence. One final point to be made, regarding memory for concepts.