This is Your Brain on the Edge of Chaos

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What do our brains have in common with piles of sand, earthquakes, forest fires and avalanches?  Each of those is a dynamic system in a self-organized critical state, and according to a new study in PloS Computational Biology, so is the brain. 

Systems in a critical state are on the cusp of a transition between ordered and random behavior.   Take a pile of sand for example: as grains of sand are added to the pile, they eventually form a slope. At a certain point, the sloping sand reaches a “critical state,” and at this point adding even a single grain can cause an avalanche that may be small or large. We can’t predict the moment or size of the avalanche, but we know that when the critical state is reached, there are several potential responses that may occur in the system (pile of sand). 

In effect, the system is globally stable at the same time as being locally unstable. Local instability (small avalanches in the sand pile) can create global instability (large avalanches leading to the collapse of the pile) bringing the system back to a new stable state. The pile of sand reorganizes itself.

While self-organized critical state models have been used to model brain dynamics before (in simulated neural networks), this study took the additional step of linking  modeling with neuroimaging to measure dynamic changes in the synchronization of activity between different regions of the brain’s network.  After developing a profile of brain dynamics with neuroimaging, researchers compared the profile with synchronization of brain activity in critical-state computational models. They found that the computational model results exactly reflected the dynamic activity in the brain, which strongly suggests that the brain exists dynamically in a critical state.

Which is to say, another door has been opened to understanding how the brain functions on the precipice of utter chaos.  Next up will be to study how the brain’s criticality is (or is not) linked to its adaptability, and to cognitive performance overall.  There’s not much evidence out there at all yet pulling these threads together, but this study does establish the groundwork for much more research. 

Another interesting question to consider: to what extent are critical state dynamics in the brain linked with psychiatric disorders?  Can better understanding how the brain teeters on the brink of randomness enable more effective treatments for certain disorders?  It’s difficult to even discuss this possibility without relying too heavily on metaphors (“neuronal avalanche” for example — and that’s a term actually used in the study), but until we have more evidential rudiments to work with, metaphor will have to fill the gaps.

Manfred G. Kitzbichler, Marie L. Smith, Søren R. Christensen, Ed Bullmore (2009). Broadband Criticality of Human Brain Network Synchronization PLoS Computational Biology

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