New research challenges traditional views of how the brain makes decisions, suggesting that even its earliest regions play a more active and dynamic role than previously thought.

New research from The Grainger College of Engineering at the University of Illinois Urbana-Champaign suggests that how the brain makes decisions could influence the future design of artificial intelligence. Led by electrical and computer engineering professor Yurii Vlasov and published in Proceedings of the National Academy of Sciences (PNAS), the study shows that early brain regions play a role in decision-making, challenging long-standing ideas about how the brain is organized.

The human brain is often described as the most complex structure in the universe. Its inner workings remain so difficult to understand that reverse-engineering it was named one of the National Academy of Engineering’s 14 grand challenges in 2008. For years, scientists have based artificial intelligence systems such as convolutional neural networks on the assumption that decisions arise through a step-by-step flow of information, starting in early sensory regions and ending in the frontal cortex. However, researchers like Vlasov are now reexamining that assumption.

Beyond Hierarchical Models of Intelligence

Another way to understand the brain focuses on natural intelligence, which has been shaped by evolution rather than designed by humans. In this framework, decision-making does not happen in a simple sequence. Instead, it involves interconnected feedback loops that send signals in both directions across different brain regions.