Researchers have discovered, while investigating protein nanowires, how to use these biological, electricity-conducting filaments to make a neuromorphic memristor or “memory transistor” device. It runs extremely efficiently on very low power, as brains do, to carry signals between neurons.
One of the biggest hurdles to neuromorphic computing and one that made it seem unreachable is that most conventional computers operate at over 1 volt, while the brain sends signals called action potentials between neurons at around 80 millivolts — many times lower. Today, memristor voltage has been achieved in the range similar to a conventional computer but getting below that seemed improbable.
Using protein nanowires developed from the bacterium Geobacter, memristors have reached neurological voltages, enabling creation of a device that is as power-efficient as the biological counterparts in a brain. Geobacter's electrically conductive protein nanowires offer many advantages over expensive silicon nanowires, which require toxic chemicals and high-energy processes to produce. Protein nanowires also are more stable in water or bodily fluids, an important feature for biomedical applications. For this work, the researchers shear nanowires off the bacteria so only the conductive protein is used.
The researchers experimented with a pulsing on-off pattern of positive-negative charge sent through a tiny metal thread in a memristor, which creates an electrical switch. They used a metal thread because protein nanowires facilitate metal reduction, changing metal ion reactivity and electron transfer properties. This microbial ability is not surprising, because wild bacterial nanowires breathe and chemically reduce metals to get their energy the way humans breathe oxygen.
As the on-off pulses create changes in the metal filaments, new branching and connections are created in the tiny device, which is 100 times smaller than the diameter of a human hair. It creates an effect similar to learning — new connections — in a real brain. The conductivity, or the plasticity of the nanowire-memristor synapse, can be modulated so it can emulate biological components for brain-inspired computing. Compared to a conventional computer, this device has a learning capability that is not software-based.