Scientists have confirmed the existence of critical points in a classic model of brain dynamics
At these critical points, networks of neurons are stable enough to store information reliably, but sensitive enough to send signals to distant parts of the brain
The team considered the Wilson-Cowan model, in which a collection of neurons is excited by external stimuli or by interactions with their neighbors. In previous studies of this model, researchers have used a simplified mean-field approximation that doesn’t explain the full range of complex phenomena observed in our brain.
Helias and his team went beyond this approximation by applying a technique called renormalization, which is commonly used in quantum field theory to deal with singularities—quantities that take on infinite values. The team’s model also involved a divergence in the strength of the interactions between neurons.
The researchers found that after renormalization, near and distant neurons alike could effectively communicate with one another, while still retaining the ability to store memories. This coordination at both small and large distance scales is a hallmark of criticality.
Although there is strong evidence for critical dynamics in the brain, nobody has yet fully explained why our brain operates this way
