Connections, or
synapses, between neurons are inspiring scientists to create
artificial
versions that could lead to smarter electronics. Credit: American Chemical
Society
Making a computer that learns and remembers like a human
brain is a daunting challenge. The complex organ has 86 billion neurons and
trillions of connections — or synapses — that can grow stronger or weaker over
time. But now scientists report in ACS’ journal Nano Letters the development of
a first-of-its-kind synthetic synapse that mimics the plasticity of the real
thing, bringing us one step closer to human-like artificial intelligence.
While the brain still holds many secrets, one thing we do
know is that the flexibility, or plasticity, of neuronal synapses is a critical
feature. In the synapse, many factors, including how many signaling molecules
get released and the timing of release, can change. This mutability allows
neurons to encode memories, learn and heal themselves. In recent years,
researchers have been building artificial neurons and synapses with some
success but without the flexibility needed for learning. Tian-Ling Ren and
colleagues set out to address that challenge.
The researchers created an artificial synapse out of
aluminum oxide and twisted bilayer graphene. By applying different electric
voltages to the system, they found they could control the reaction intensity of
the receiving “neuron.” The team says their novel dynamic system could aid in
the development of biology-inspired electronics capable of learning and
self-healing.