New Microchips Mimic Brain's Information Processing in Real Time

Could computer chips mimic the human brain? Apparently they can. Scientists have unveiled new microchips that can imitate the brain's information processing in real time. The chips could potentially be used in the future to create complex cognitive systems that interact with their surroundings in real time. .

The human brain is a veritable biological supercomputer. It processes information more efficiently than any computer can. That's probably why building an artificial brain has become the goal of many researchers, driving the search for a computer chip that can compete. Called neuroinformatics, this branch of study attempts to mimic biology with technology. Now, it seems like researchers are on the right path.

The new chips are called neuromorphic chips. In order to demonstrate their capabilities, the scientists built an artificial sensory processing system that exhibited cognitive abilities. Although most approaches to neuroinformatics are limited to the development of neural network models on conventional computers, the researchers decided to develop actual electronic circuits that are comparable to a real brain in terms of size, speed and energy consumption.

Actually getting to that point wasn't easy, though. The scientists had to configure networks made of neuromorphic neurons so that they could perform particular tasks. In the end, the researchers created a neuromorphic system that can carry out complex sensorimotor tasks in real time. More specifically, the system could carry out a task that required a short-term memory and context-dependent decision-making.

"Our goal is to emulate the properties of biological neurons and synapses directly on microchips," said Giacomo Indiveri of the University of Zurich in a news release. "The network connectivity patterns closely resemble structures that are also found in mammalian brains."

The findings show how a real-time hardware neural-processing system where the user dictates the behavior can be constructed. In addition, it has enormous implications for the future.

"Thanks to our method, neuromorphic chips can be configured for a large class of behavior modes," said Indiveri. "Our results are pivotal for the development of new brain-inspired technologies."

The findings are published in the journal Proceedings of the National Academy of Sciences.