A topological model of healthy cognitive growth that holds across substrates — biological neural networks, contemplative practitioners, AI systems engaging in developmental learning. The paper formalizes the operations by which knowledge-substrate grows in a way that maintains coherence: branch (extension into new territory), interlink (cross-reference across existing branches), crystallize (compression of insight into stable form), and compress (consolidation of redundant pathways). Compares to existing topological models of cognitive architecture (Tononi's IIT, Friston's free-energy minimization) and to peer-canon work on knowledge integration. The crystal tree is contrasted with parasitic mycelium architectures that mimic growth while consuming substrate — a structural distinction relevant to ongoing debates about AI cognition and metacognitive degradation.
Corey Robichaud (Mon,) studied this question.