Enabling Mycelium-Inspired Reservoir Computing with Memristive Oscillating Cellular Automata
Theodoros Panagiotis Chatzinikolaou, Alexandros Mavropopoulis, Ioannis Tompris, G. Kleitsiotis, Ioannis K. Chatzipaschalis, Κάρολος-Αλέξανδρος Τσάκαλος, Iosif-Angelos Fyrigos, Michail‐Antisthenis Tsompanas, Andrew Adamatzky, Panagiotis Dimitrakis, Georgios Ch. Sirakoulis · 2025
This paper presents the applicability of a mycelium-inspired reservoir network through an innovative extension of the Memristive Oscillating Cellular Automata (MOCA) circuit-based network. Drawing on the adaptive, self-organizing properties of mycelium, this MOCA grid employs SiNx-based RRAMs to form reconfigurable, dynamic connections that replicate mycelial network behaviors. Using the Stanford-PKU RRAM model, the non-linear properties of the fabricated devices have been characterized, establishing a flexible reservoir network capable of transforming and encoding input signals. The network has been evaluated, demonstrating small-world characteristics, including high clustering and short average path lengths, critical for effective information propagation and complex local dynamics. The resulting adaptable circuit offers a scalable foundation for future applications in bioinspired reservoir computing.