Figure 1.

Control over criticality. (a) Second-order phase transitions, the amount of order (y-axis) is nonlinearly related to small changes in a control parameter (x-axis). Below the critical point (green dot), the system has low order (subcritical; blue), whereas above the critical point, the system has increasing order (super-critical; red). (b) The classic Ising model of magnetism: in the subcritical regime, there is no magnetism, as individual domains are misaligned; near the critical point, the individual domains are now more susceptible to an external magnetic field, causing fluctuations in magnetism; and in the super-critical regime, the domains align into an ordered magnetic state. (c) Analogously, in a neuronal population, a subcritical regime is associated with an absorbing quiescent state that arises from ineffective interactions between neurons, leading to stimuli that effectively dissipate; near criticality, there is maximal percolation among the network; whereas in the super-critical regime, heightened interactions are such that the network is over-excited by external inputs leading to runaway activity.