Researchers from Northwestern University and the University of Hong Kong developed a brain-like computing device that is capable of learning by association. The research was published April 30 in the journal Nature Communications.
Similar to how famed physiologist Ivan Pavlov conditioned dogs to associate a bell with food, the researchers successfully conditioned their circuit to associate light with pressure. The device’s secret lies within its novel organic, electrochemical “synaptic transistors,” which simultaneously process and store information just like the human brain.
The researchers demonstrated that the transistor can mimic the short-term and long-term plasticity of synapses in the human brain, building on memories to learn over time. With its brain-like ability, the novel transistor and circuit could potentially overcome the limitations of traditional computing, including their energy-sapping hardware and limited ability to perform multiple tasks at the same time. The brain-like device also has higher fault tolerance, continuing to operate smoothly even when some components fail.
“Although the modern computer is outstanding, the human brain can easily outperform it in some complex and unstructured tasks, such as pattern recognition, motor control and multisensory integration,” said Northwestern’s Jonathan Rivnay, a senior author of the study.
Researchers from Northwestern University and the University of Hong Kong developed a brain-like computing device that is capable of learning by association. The research was published April 30 in the journal Nature Communications.
Similar to how famed physiologist Ivan Pavlov conditioned dogs to associate a bell with food, the researchers successfully conditioned their circuit to associate light with pressure. The device’s secret lies within its novel organic, electrochemical “synaptic transistors,” which simultaneously process and store information just like the human brain.
The researchers demonstrated that the transistor can mimic the short-term and long-term plasticity of synapses in the human brain, building on memories to learn over time. With its brain-like ability, the novel transistor and circuit could potentially overcome the limitations of traditional computing, including their energy-sapping hardware and limited ability to perform multiple tasks at the same time. The brain-like device also has higher fault tolerance, continuing to operate smoothly even when some components fail.
“Although the modern computer is outstanding, the human brain can easily outperform it in some complex and unstructured tasks, such as pattern recognition, motor control and multisensory integration,” said Northwestern’s Jonathan Rivnay, a senior author of the study.