Dissipation, coherence and the quantum brain dynamics

Giuseppe Vitiello

Walter Freeman, Giuseppe Vitiello

Giuseppe Vitiello

This is a short review of some features of brain modeling in quantum field theory. The brain is continuously interacting with its environment and its functional activity has to be therefore described by a dissipative dynamics. In the model, memory states are generated by the mechanism of spontaneous breakdown of symmetry. From the dissipative dynamics several consequences can be derived, such as the description of the environment in terms of the time-reversed copy of the brain, called its Double. Formally this is achieved by the procedure of doubling the degrees of freedom and the resulting state is a two-mode entangled coherent state. The act of consciousness is proposed to reside in the dialog between the brain and its Double, occurring always in the present, the “Now”, where the brain and its Double indeed meet, on the surface of the time-mirror.

Vitiello, G

The quantum model of the brain proposed by Ricciardi and Umezawa is extended to dissipative dynamics in order to study the problem of memory capacity. It is shown that infinitely many vacua are accessible to memory printing in a way that in sequential information recording the storage of a new information does not destroy the previously stored ones, thus allowing a huge memory capacity. The mechanism of information printing is shown to induce breakdown of time-reversal symmetry. Thermal properties of the memory states as well as their relation with squeezed coherent states are finally discussed.

Mari Jibu, Kunio Yasue

Valeriy Kotenko

This manuscript proposes a testable research framework for studying two-phase Bayesian inference in open, noisy, brain-like systems. The work does not assume the existence of macroscopic quantum computation in biological tissue. Instead, it investigates whether resonance-assisted dynamics in dissipative systems can produce quantum-like computational advantages without long-lived coherence. The framework integrates variational Bayesian inference, stochastic resonance, and nonlinear feedback mechanisms. Concrete experimental and theoretical pathways are outlined to validate or falsify the proposed mechanisms. This project is now under legal monitoring. All commercial implementations must contact the author.