Oren Shriki

The theory of thermodynamic criticality is well established in the physical sciences. It provides a powerful framework to understand various emergent phenomena in systems with a large number of interacting elements. In this chapter, we explore how to apply this framework to study neuronal avalanche dynamics in the brain, specifically for resting activitiy recorded from monkeys and humans using microelectrode arrays and magnetoencephalography, respectively. By numerically changing a control parameter, equivalent to thermodynamic temperature in nonbiological systems, we observe typical critical behavior in cortical dynamics near the actual physiological condition. Specifically, we demonstrate the phase transition of an order parameter that quantifies average cortical activity, as well as the divergence of susceptibility and specific heat which quantify input sensitivity and internal complexity of the system, respectively. By demonstrating finite-size scaling for these quantities, we derive the corresponding critical exponents, which uncover a distinct, yet universal organization of brain dynamics. These results demonstrate that normal brain dynamics at rest resides near or at thermodynamic criticality, which provides important functional benefits, such as large dynamic range and internal memory capacity, to cortical information processing.