Researchers from the University of Sydney led a group of international researchers who found that nanowire networks can display short- and long-term memory similar to the human brain. Nanowire networks are a type of nanotechnology typically made from tiny, highly conductive silver wires that are invisible to the naked eye and mimic aspects of the networked physical structure of a human brain. The wires act like neurons, and the places where they connect are analogous to synapses. The researchers found that the nanowire network could ‘remember’ a desired endpoint in an electric circuit seven steps back, meaning a score of 7 in an N-Back test.

To test the capabilities of the nanowire network, the researchers gave it a test similar to a standard memory task used in human psychology experiments called the N-Back task. When applied to the nanowire network, the researchers found it could ‘remember’ a desired endpoint in an electric circuit seven steps back, meaning a score of 7 in an N-Back test. This could lead to real-world applications such as improving robotics or sensor devices that need to make quick decisions in unpredictable environments.

The researchers said that when the nanowire network is constantly reinforced, it reaches a point where that reinforcement is no longer needed because the information is consolidated into memory. “It’s kind of like the difference between long-term […] and short-term memory in our brains,” senior author and School of Physics Prof. Zdenka Kuncic said. “If we want to remember something for a long […] time, we […] need to keep training our brains to consolidate that; otherwise, it just kind of fades away over time. One task showed that the nanowire network can store up to seven items in memory at substantially higher than chance levels without reinforcement training and near-perfect accuracy with reinforcement training.”

Advances in nanowire networks could herald many real-world applications, such as improving robotics or sensor devices that need to make quick decisions in unpredictable environments. This work builds on previous research in which the researchers showed how nanotechnology could be used to build a brain-inspired electrical device with neural network-like circuitry and synapse-like signaling. The researchers’ work paves the way toward replicating brain-like learning and memory in non-biological hardware systems. It suggests that the underlying nature of brain-like intelligence may be physical.

This new research was published in Science Advances.

References

• Loeffler, A., Diaz-Alvarez, A., Zhu, R., Ganesh, N., Shine, J. M., Nakayama, T., & Kuncic, Z. (2023). Neuromorphic learning, working memory, and metaplasticity in nanowire networks. Science Advances, 9(16), eadg3289.
• Ritchie, P. (2023, April 24). Nanowire networks learn and remember like a human brain. The University of Sydney; The University of Sydney. https://www.sydney.edu.au/news-opinion/news/2023/04/24/nanowire-networks-learn-and-remember-like-a-human-brain.html