Ensemble phenomena such as the emergence of a phase transition are by no means limited to artificial and inanimate entities. On the contrary, in living beings one may not infrequently observe similar phenomena, whose origin can be tracked down to the effect of the interaction among many components. Indeed, in living organisms the number of cells cooperating in biological and physiological processes is so large that ensemble behaviors are only to be expected. The rapid transition between two neural states was observed as early as the late 1980s (Freeman, 1988). The experimental setting used by Freeman and co-workers included animal and human subjects, engaged in goal-directed behavior, on which high-density electrode arrays were fixed. Action potentials and brain waves (electroencephalograms (EEG) and local field potentials) were then recorded and used to develop a data-driven brain theory.

Freeman and co-workers designed data processing algorithms that enhance the spatial and temporal resolution of the textures of brain activity patterns found in three-layer paleocortex and six-layer neocortex. A major discovery of their work was evidence that cortical self-organized criticality creates a pseudoequilibrium in brain dynamics that allows cortical mesoscopic state transitions to be modeled analogously to phase transitions in near-equilibrium physical systems.