Sustainable memristors from shiitake mycelium for high-frequency bioelectronics

Area of Science:

• Bioelectronics
• Unconventional Computing
• Materials Science

Background:

• Neuromorphic computing aims to mimic the brain's efficiency but faces challenges with rare-earth materials and complex fabrication.
• Current neuromorphic solutions like semiconductor chips and neural organoids present sustainability and maintenance issues.

Purpose of the Study:

• To explore shiitake (Lentinula edodes) fungi as a sustainable and robust alternative for neuromorphic computing.
• To investigate the potential of fungal mycelial networks for adaptive electrical signaling and information processing.

Main Methods:

• Interfacing shiitake mycelial networks with electrodes to create fungal memristors.
• Training and testing the functionality of fungal memristors, including their response to electrical signals.
• Assessing the preservation capabilities through dehydration and performance at high frequencies.

Main Results:

• Demonstrated fungal memristors grown from shiitake fungi exhibit adaptive electrical signaling similar to neuronal spiking.
• Fungal computers retained functionality after dehydration and operated at frequencies up to 5.85 kHz with 90% ± 1% accuracy.
• Shiitake fungi showed notable radiation resistance, indicating potential for aerospace applications.

Conclusions:

• Fungal computers offer a scalable, eco-friendly platform for neuromorphic tasks, bridging bioelectronics and unconventional computing.
• Shiitake fungi present a viable, sustainable alternative to conventional materials in neuromorphic hardware.
• The developed fungal computing approach has potential applications in various fields, including aerospace.