The recovery of parabolic avalanches in spatially subsampled neuronal networks at criticality.

In the brain, groups of neurons often fire together which is considered essential for normal brain function. A particular form of coincident firing has been identified for "neuronal avalanches" which are scale-invariant cascades of neuronal activity that rapidly engage large numbers of neurons. However, studying these avalanches when observing only a few neurons in the network is challenging. We used simulations and recordings from ongoing brain activity to explore how to overcome this challenge. We found that adjusting our temporal resolution and focusing on increasingly larger avalanches allows us to accurately detect rapid, parabolic expansions of these patterns even when examining a minuscule fraction of neurons. This identifies a general rule for how the brain operates best in engaging neurons to fire together, despite the limitations in our observations.