Neuromorphic computing, inspired by the structure of the brain, offers advantages in parallel processing, memory storage, and energy efficiency. However, current semiconductor-based neuromorphic chips require rare-earth materials and costly fabrication processes, whereas neural organoids need complex bioreactor maintenance. In this study, we explored shiitake (Lentinula edodes) fungi as a robust, sustainable alternative, exploiting its adaptive electrical signaling, which is akin to neuronal spiking. We demonstrate fungal computing via mycelial networks interfaced with electrodes, showing that fungal memristors can be grown, trained, and preserved through dehydration, retaining functionality at frequencies up to 5.85 kHz, with an accuracy of 90 ± 1%. Notably, shiitake has exhibited radiation resistance, suggesting its viability for aerospace applications. Our findings show that fungal computers can provide scalable, eco-friendly platforms for neuromorphic tasks, bridging bioelectronics and unconventional computing.
Funding: Authors J.S. and J.H. were supported by Honda Research Institute (grant AWD-118684). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Copyright: © 2025 LaRocco et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Background
Overview The development of neuromorphic hardware relies on memristive devices capable of emulating synaptic behavior, with potential applications in energy-efficient computing and artificial intelligence1. Recent work has explored natural, biodegradable substrates as sustainable alternatives to conventional inorganic memristors [1]. In this study, we investigated the potential of the edible fungus Lentinula edodes (shiitake mushroom) as a platform for memristor fabrication. By examining the electrical response of mushroom-derived materials under repeated voltage cycling, we explored stable memristive switching behavior, retention, and endurance. Shiitake-based devices not only demonstrate reproducible memory effects, but also highlight the potential for scalable, low-cost, and environmentally friendly neuromorphic components.
Memristors Memristor devices offer substantial advantages in robotic, industrial, and transport applications due to their unique electrical properties and ability to mimic neural functions. They can enhance various control systems, facilitate efficient information processing, and ultimately improve the overall performance of autonomous systems. One of the key strengths of memristors is their capacity for efficient and self-adaptive in situ learning, which is critical for applications in robotics and autonomous vehicles. In memristor-based neural networks, the devices can adjust their resistance based on previous inputs, allowing for a form of analog learning that closely resembles the synaptic behavior in biological systems [1]. This capability enables robots and autonomous vehicles to learn from their environment and adapt in real time, enhancing their ability to navigate complex situations effectively. It has been found that such systems can achieve low-latency responses, which are essential for high-speed decision-making in dynamic environments [2]. Memristors also have the advantage of integrating memory and processing capabilities into a single device, enabling a simplified architecture for autonomous control systems [3]. For instance, in autonomous vehicles, trajectory-tracking and path-following tasks can be performed using memristor-based controllers that allow for rapid calculations and real-time adjustments to control variables [4]. This integration, especially with parallelization, helps to address the challenges posed by separate memory and processing units, which can lead to delays and increased power consumption in traditional control systems [4]. Additionally, the resilience of memristor devices against environmental changes, and their ability to operate under varying conditions, make them particularly suitable for autonomous applications, such as spacecraft electronics or vehicles operating in unpredictable road environments [4]. This is complemented by the precision in control that memristor-based systems can offer, which is significant for maintaining stability and performance while following desired trajectories [5]. Moreover, the low power consumption of memristors is particularly beneficial in robotics and autonomous vehicles, where energy efficiency is paramount. Hybrid analog–digital memristor systems can minimize power usage during processing without sacrificing responsiveness, which can prolong operational times by reducing the frequency at which recharging or battery replacement is required, enhancing the feasibility of deploying such systems in mobile applications [2]. Ultimately, the potential of memristors to emulate human-like decision-making and learning processes could be exploited to endow robotic systems and autonomous vehicles with functionalities not found in conventional control systems. The ability of memristors to perform complex computations efficiently, learn adaptively, and integrate both memory and processing into a unified approach make them a cornerstone technology for the future development of intelligent autonomous systems. However, the production of memristors often requires rare-earth minerals and expensive semiconductor foundries.
Fungal electronics Fungi possess innate abilities to adapt to various environmental conditions and efficiently process information through their interconnected network of hyphae. These characteristics make fungi an ideal candidate for developing sustainable computing systems from. Our aim was to design and implement a novel fungal memristor-based computing architecture that could significantly reduce energy consumption and minimize electronic waste. We approached this using substantially simpler bioreactors and nutrient cultures than those required for conventional neurons and neural organoids. The unique advantages of fungal memristors stem from the biological properties of fungal materials, which distinguish them from typical inorganic or polymer alternatives [6,7]. First, one of the main benefits of fungal memristors is their environmentally sustainable and biodegradable nature. Conventional memristors often contain transition metal oxides or silicon-based structures, the production or disposal of which can pose environmental challenges [6,7]. By contrast, fungal materials are derived from organic biomass, making them both sustainable and significantly less harmful to the environment. This aligns with increasing efforts toward developing greener electronic materials, as highlighted in previous work emphasizing the importance of sustainability in technology development [8]. Second, fungal memristors exhibit remarkable adaptability in their electrical properties. The structural composition of fungal materials often allows for a range of conductive pathways that can form dynamically under the influence of electrical stimuli, similar to the conductive filaments formed in conventional memristors [9,10]. This adaptability can lead to enhanced performance in neuromorphic applications through the facilitation of variable resistance states that mimic synaptic behaviors more closely than traditional memristive materials, which often have static crystalline structures that can lead to variability problems or performance limitations at the nanoscale [11]. Furthermore, fungal memristors may consume less power than traditional materials due to their unique electrochemical properties. It has been claimed that some organic materials, including those derived from fungi, can operate effectively at lower voltages while maintaining stable switching characteristics––a trait that is crucial for developing energy-efficient devices for portable electronics and Internet of Things applications [12]. This can significantly extend battery life and reduce energy costs in processing and memory applications, which have become focal points in the research into neuromorphic systems [13]. Finally, the natural composition and multicellularity of fungal materials can lead to more naturalistic models for neural networks. Because these materials are subject to biological processes, they may inherently incorporate characteristics that resemble biological neuronal networks, including plasticity and memory capabilities that could evolve with usage. This biological mimicry could strengthen the development of more advanced artificial neural networks, enabling applications such as adaptive learning systems and intelligent sensor networks [14].
Fungus types The potential use of common food mushrooms, such as shiitake and button mushrooms (Agaricus bisporus), as organic memristors is an emerging area of research that exploits the unique properties of these fungi [6,7,13]. Memristors, which are non-volatile memory devices that retain information even without power, can benefit from the porous structures and electrical properties of the organic materials derived from mushrooms. Shiitake mushrooms have been shown to possess a hierarchically porous carbon structure when activated. This porous structure can enhance the electrochemical performance of devices, making them suitable candidates for use in energy storage systems, including supercapacitors and, potentially, memristors [15]. Highly conductive carbon materials have been created from shiitake, suggesting that these materials could be engineered to exhibit memristive behavior [16]. Shiitake-derived carbon is a sustainable alternative to traditional materials and can enhance the performance of electronic devices due to its unique structural properties. Button mushrooms have also shown significant potential in this context. Research has indicated that their porosity can be exploited to create materials with large surface areas, which are essential for the development of efficient electronic components [17]. The synthesis of carbon composites from button mushrooms has been explored, revealing their ability to function effectively in energy storage applications [17]. Furthermore, the integration of button mushrooms into electronic systems has been investigated, demonstrating their potential as substrates for electronic devices [18]. In addition to their structural properties, the unique biological characteristics of fungi, including their ability to interact with various chemical compounds, can be harnessed to develop novel sensing technologies. For instance, electronic noses have been developed that use mushroom extracts to detect volatile compounds. These could be adapted for use in electronic devices that require environmental-sensing capabilities [19,20]. This intersection of biology and electronics opens new avenues for creating multifunctional devices that incorporate the sensory capabilities of mushrooms.