Scientists have wondered for a long time how neurons in our brain process information so efficiently. Traditional theories suggested that this required precisely tuned neural patterns. However, new research at IOB shows that highly efficient information processing can emerge from irregular, random patterns of neural activity.

In this groundbreaking theoretical study, researchers demonstrated that random neural patterns can actually compress information more effectively than previously thought possible. This discovery challenges our understanding of how the brain processes information and suggests that biological systems might achieve efficiency through controlled randomness rather than precise organization.

“It might seem surprising,” says Rava Azeredo da Silveira, the senior author. “We often think of efficiency as coming from precision, and of disorder or randomness as a hindrance. But we found that the right amount of randomness can actually lead to extremely efficient information processing in neural networks. We first came up with a purely theoretical argument, and then noticed that this strategy is actually used by the brain!”

This finding could have far-reaching implications for our understanding of brain function and the development of artificial neural networks.

Original Publication

Random compressed coding with neurons
Simone Blanco Malerba, Mirko Pieropan, Yoram Burak, Rava Azeredo da Silveira

Cell Rep. 2025 Mar 25;44(3):115412.

doi: 10.1016/j.celrep.2025.115412. Epub 2025 Mar 19.