Computational Processes that Appear to Model Human Long-term Memory

This paper presents two computable functions, ω and ε, that map networks into networks. If all cognition occurs as an active neural network, then it is thought that ω models long-term memory consolidation and ε models memory recall. A derived, intermediate network form, consisting of chordless cycles, could be the structural substrate of long-term memory; just as the double helix is the necessary substrate for genomic memory.