Illinois Grainger findings challenge traditional neuroscience

New insight into decision-making pathways in the brain may impact the way engineers think about artificial intelligence, according to new research from The Grainger College of Engineering at the University of Illinois Urbana-Champaign. Led by electrical and computer engineering professor Yurii Vlasov and published in Proceedings of the National Academy of Science (PNAS), the group’s findings highlight the involvement of early brain regions in decision-making, challenging long-held assumptions about brain hierarchy.

The human brain has long been considered the most complex structure in the universe; it remains such an enigma that reverse-engineering the brain was identified in 2008 by the National Academy of Engineering as one of 14 grand challenges for engineering in the 21^st century. For decades, assumptions about the human brain have formed the basis for convolutional neural networks and other types of artificial intelligence: namely, that decision-making occurs in a hierarchical bottom-up flow of information beginning in early brain regions and ending in the frontal cortex. But in recent years, scientists such as Vlasov have begun to question that prevailing view.

An alternative perspective hinges on natural intelligence — a process molded by evolution instead of machines. In this view of the brain, decision-making occurs not only through sequential stages but via nested feedback loops that operate bidirectionally. Natural intelligence is more computationally powerful than current iterations of artificial intelligence and requires significantly less power, making it an attractive model for future AIs. To improve their understanding of this process, Vlasov and his interdisciplinary team of researchers sought to dissect and understand brain architecture from a systems-level view.

“We want to learn from a billion years of evolution,” Vlasov said. “How is that biological intelligence organized architecturally? Can we learn from the architectural side of the brain and emulate that to make AI more effective, less power hungry, and more intelligent than it currently is? In the level of decision-making, that's where current AI is lacking.”

To contend with the complexities of studying the brain, Vlasov started by examining its earliest stages involved in sensing and perception of the world. After recording neural activity in mice navigating a virtual reality corridor and making perceptual decisions, the Illinois researchers were surprised to find decision-making signals as early in the brain hierarchy as in the primary somatosensory cortex (S1). S1 appeared to be dynamically modulated by top-down regulation, engaged by the higher-level brain regions via feedback loops, suggesting that decision-making is not solely relying on unidirectional feed-forward processes as previously thought.

“The neural code of the brain is still mostly an unknown language,” Vlasov said. “But this systems-level understanding can be viewed as a potential impact on how more efficient artificial neural networks can be built — how the next generation of AI can be thought through. Maybe with these analogies that we learn from real brains, we can improve AI further.”

While not a direct recipe for building better AIs, Vlasov positions the results as something new that can be learned from the brain. Going forward, Vlasov and his team will further explore the complexity of their findings in the context of temporal dynamics while developing new tools to interrogate and collect signals from the brain.

“By looking at the fast temporal dynamics of neural activity, maybe we can understand better how these feedback loops are engaged in making decisions,” Vlasov said. “Maybe that’s the approach that potentially uncovers these currently unknown mechanisms — how these feedback loops are organized dynamically and how they form and shape different levels of processing. Maybe that can be implemented in new architectures for AI.”

Illinois Grainger Engineering Affiliations

Yurii Vlasov is an Illinois Grainger Engineering Founder Professor in the Department of Electrical and Computer Engineering. Vlasov is affiliated with the Department of Bioengineering, Holonyak Micro and Nanotechnology Lab, Carle Illinois College of Medicine and the Beckman Institute for Advanced Science and Technology. He holds the John Bardeen Endowed Chair appointment.