We compare the predictions of the dissipative quantum model of the brain with neurophysiological data collected from electroencephalograms resulting from high-density arrays fixed on the surfaces of primary sensory and limbic areas of trained rabbits and cats. Functional brain imaging in relation to behavior reveals the formation of coherent domains of synchronized neuronal oscillatory activity and phase transitions predicted by the dissipative model.

In the engagement of the brain with its environment, large-scale neural interactions in brain dynamics create a mesoscopic order parameter, which is evaluated by measuring brain waves (electrocorticogram, ECoG). Such large-scale interactions emerge from the background activity of the brain that is sustained by mutual excitation in cortical populations and manifest in spatiotemporal patterns of neural activity. Band pass filtering reveals beats in ECoG power that recur at theta rates (3 −7 Hz) as null spikes in log10 power. The order parameter transiently approaches zero, and the microscopic activity is both disordered and symmetric. As the null spikes terminate, the order parameter resurges and imposes a mesoscopic spatial pattern of ECoG amplitude modulation that then governs the microscopic gamma activity and retrieves the memory of a stimulus. The brain waves reveal a spatial pattern of phase modulation in the form of a cone. The dissipative many-body model of brain dynamics describes these phase cones as vortices, which are initiated by the null spikes, and which stabilize the amplitude modulated patterns embedded in the turbulent neural noise from which they emerge.

The brain is a thermodynamic system operating far from equilibrium. Its function is to extract microscopic sensory information from the volleys of action potentials (pulses) that are delivered by immense arrays of sensory receptors, construct the macroscopic meaning of the information, and store, retrieve, and update that meaning by incorporating it into its knowledge base. The function is executed repetitively in the action-perception-assimilation cycle. Each cycle commences by a phase transition, in which the immense population comprising each sensory cortex condenses from a gas-like state to a liquid-like state. It ends with return of the cortex to the expectant gas-like state. We have modeled the microscopic thermodynamics of the cycle using quantum field theory. Our new result is modeling cortical macroscopic thermodynamics with the generalized Carnot cycle, in which the energy required for the construction of knowledge is supplied by brain metabolism and is dissipated as heat by the cerebral circulation. What makes the application possible is the unprecedented precision with which spatial patterns of ECoG are measured, thus providing precise state variables with which to represent energy vs. entropy. We present experimental evidence that these isothermal processes are coupled by adiabatic cooling and heating. We postulate that the action-perception-assimilation cycle comprises minimally three consecutive Carnot cycles required for basic perception, assimilation, and decision, and more cycles with greater complexity of cognitive tasks at hand.