The brain’s powerful information processing capacity can be largely attributed to neuronal microcircuits established by synaptic connectivity patterns. Precisely how neurosynaptic connectivity gives rise to higher-order cognitive functions such as learning and memory remains elusive. However, an important clue is that neural connectivity is spatiotemporally sparse and dynamic. In new research led by the University of Sydney, learning and memory are demonstrated in a unique physical substrate with these properties.
Nanowire networks are a type of nanotechnology typically made from tiny, highly conductive silver wires that are invisible to the naked eye, covered in a plastic material, which are scattered across each other like a mesh.
The wires mimic aspects of the networked physical structure of a human brain.
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.
“In this research, we found higher-order cognitive function, which we normally associate with the human brain, can be emulated in non-biological hardware,” said University of Sydney’s Dr. Alon Loeffler, first author of the study.
“This work builds on our previous research in which we showed how nanotechnology could be used to build a brain-inspired electrical device with neural network-like circuitry and synapse-like signaling.”
“Our current work paves the way towards replicating brain-like learning and memory in non-biological hardware systems and suggests that the underlying nature of brain-like intelligence may be physical.”
“The nanowire network is like a synthetic neural network because the nanowires act like neurons, and the places where they connect with each other are analogous to synapses,” said University of Sydney’s Professor Zdenka Kuncic, senior authors of the study.
“Instead of implementing some kind of machine learning task, in this…
Read the full article here