The brain doesn’t just work together. also competes. So determines an international study from the University of Oxford, the University of Cambridge, Pompeu Fabra University and the Montreal Neurological Institute in Canada, published in Nature Neuroscience. The study reveals that the human brain—like that of macaques and mice—works thanks to a stable balance between these two forces. Using advanced whole-brain computer modeling, the researchers showed that while specialized circuits cooperate internally, there are long-term competitive interactions between them to manage limited resources. Reproducing this balance could bring us closer to creating digital copies of a person’s brain, a major breakthrough in precision medicine and the development of AI models with greater computational power.
Models with competitive interactions – based on the everyday experience that we cannot attend to everything at once – consistently outperform purely cooperative ones. This explains the joint work of specialized areas for cognition and behavior. According to the authors, too much cooperation can lead to situations of hyper-synchrony that do not actually occur. Instead, competition acts as a stabilizing force: it prevents uncontrolled activity and allows different brain systems to take turns in shaping overall brain dynamics.
The analysis of more than 14,000 neuroimaging studies revealed that models with competitive interactions produce patterns of activity that more closely resemble real cognitive processes, such as those involved in attention and memory. “Competition between circuits allows certain networks to take precedence over others depending on what is relevant at any given moment, which explains phenomena such as decision-making,” explains Gustavo Deco, ICREA Research Professor at Pompeu Fabra University, one of the senior authors of the study.
This suggests that competition is crucial to enable the brain to flexibly activate appropriate combinations of regions: a hallmark of intelligent behavior.”
Morten Kringelbach, a professor at the University of Oxford, senior author of the study
An effective model for diagnosis, improvement and treatment
Using data about the structure and function of a person’s brain, this new model can reproduce the unique activity patterns of a person’s brain, better capturing what distinguishes one person’s brain from another’s. This brings us closer to having “a realistic digital twin of a given brain: the one that matches your brain better than any other brain,” according to the study’s lead author, Dr. Andrea Luppi of the University of Oxford.
According to Deco, this model not only allows the brain to be digitally reproduced but “provides much better information for predicting disease and symptoms than traditional measures.” As Luppi reports, in addition to diagnosis, “these models could be used to simulate an individual’s brain response to stimulation, medication or disease, tailoring treatment to each individual’s brain.”
The fact that the cooperative-competitive architecture is consistently found in humans, macaques, and mice suggests that it is a fundamental feature of mammalian brain organization. More generally, it could reflect fundamental operating principles of intelligent systems.
The study also reveals that networks that combine cooperation and competition have greater computational capabilities in neuromorphic computing (artificial intelligence inspired by the brain). These networks process and integrate information more efficiently, confirming that the balance between the two forces is essential for intelligent computation.
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