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While the human brain still outpaces our personal computers in many cognitive tasks, researchers are now aiming to close that gap by building machines that mimic the brain’s remarkable efficiency.
Industry giants such as IBM and Intel have already introduced neuromorphic chips that accelerate artificial‑intelligence workloads, but their performance is still limited by the difficulty and expense of producing the specialized hardware.
Ohio State University researchers propose a radically cheaper alternative: using the root‑like network of a common mushroom. The mycelium of shiitake fungi forms branching structures that closely resemble neural networks, and like brains, it can exhibit emergent behaviour when its simple units interact.
Lead scientist Dr. John LaRocco, a neural engineer at OSU, assembled a circuit by connecting shiitake mycelium to standard computer wiring and then applied controlled voltage pulses. Across several attachment points, the fungal network transmitted signals at frequencies up to 5.85 kHz—about 5,850 pulses per second—comparable to the earliest silicon‑based memristors. Even more striking, the mycelium adjusted its internal resistance in response to repeated stimuli, effectively learning to optimise signal speed.
Traditional computers rely on transistors—tiny switches that, when combined, process binary data. Transistors, however, lack the intrinsic memory of neurons, which allows biological brains to learn by storing past connections. A device that can remember—known as a memristor—bridges that gap and functions like an artificial neuron.
LaRocco’s team demonstrates that shiitake mycelium can serve as a memristor, delivering signal speeds comparable to early silicon implementations while requiring no rare‑earth metals or complex fabrication steps. The cost savings are significant: producing mycelium‑based chips is far less resource‑intensive than silicon and metal‑based counterparts.
Beyond economics, the fungal approach offers additional advantages. Shiitake mycelium displays radiation resistance, a property that could make it suitable for aerospace applications where conventional silicon devices are vulnerable.
Although still in the experimental stage, these findings illustrate how nature’s own engineering solutions—like fungal networks—can inspire breakthrough computing technologies.
