A new framework that causes artificial neural networks to mimic how real neural networks operate in the brain has been developed by a RIKEN neuroscientist and his collaborator. In addition to shedding light on how the brain works, this development could help inspire new AI systems that learn in a brain-like way. The research is published in Nature Communications.

Humans and animals have remarkable capacities to learn and perform complex tasks due to the brain’s amazing ability to take in sensory information and produce complex outputs.

Toshitake Asabuki of the RIKEN Center for Brain Science is fascinated by the brain and wants to discover how it works. “My team investigates how the brain learns efficiently and robustly,” he says. “We aim to identify learning rules that could, in principle, be implemented by real neural circuits in the brain.”