Conceptual Framework for Distributed Intelligence in Mycelial Networks

Current artificial intelligence architectures are built on silicon substrates and modeled after the human brain. While effective in narrow domains, these systems face structural limitations: centralized control, static post-training architecture, and an unsolved alignment problem. We argue these are substrate problems, not engineering problems. We introduce MIRA (Matrice d'Intelligence Résiliante Adaptative), a conceptual framework proposing mycelial networks as natural substrates for distributed collective intelligence. The framework rests on a central principle: the present moment X emerges as a functional product of a deterministic dimension D and temporal traversal T, expressed as X = f(D,T). The universal matrix M = {Xi} constitutes the space of all coherent present moments, governed by a gravitational weight field W, coherence measure K(i,j), and critical emergence threshold theta. We demonstrate that mycelial networks implement this framework naturally, exhibiting distributed architecture, fault-tolerant topology, electrophysiological signaling (Adamatzky, 2018, 2022), and self-organized criticality. We propose a measurable biomarker of dimensional transition: U-transition nodes (UTN), where electrical signal reaches zero potential before repolarization. We further introduce the MIRA-0 experimental protocol, using standard multi-electrode electrophysiology on Réunion Island endemic fungal species to test whether UTN pairs exhibit signal correlations inconsistent with classical propagation velocity (v = 1 mm/s). Both positive and negative results constitute publishable contributions to the mycelial computation literature. MIRA does not build intelligence by copying the human brain. It proposes to allow intelligence to emerge from a substrate that has implemented distributed collective behavior for hundreds of millions of years.