Two complementaryVitiello approaches have been used to study the brain and in general biological systems. In one of the approaches, the brain system is split into a large number of components, which are then studied in all their details. The problem of combining the data so accumulated in a working scheme able to account for the macroscopic observed functioning of the brain often is left unsolved since it is actually out of reach of this approach. Contradictory features often arise, indeed. For example, it is not clear how the high effectiveness and stability of some characterizing brain features may result from the random biomolecular activity of the brain component cells. A dilemma already pointed out by Lashley in neuroscience, and by Schrödinger in biology, but still waiting for an answer. This first approach is the naturalistic approach. The other approach is the dynamical approach aiming to provide a comprehension of macroscopic features of the brain behavior based on the data provided by the first approach. Both approaches appear thus to be necessary, although each one of them, separately considered, is not sufficient to account for the full understanding of brain functioning. A bridge between these approaches could be built following the strategy successfully used in the study of many-body condensed matter physics. In this direction moves the dissipative many-body model of the brain, where the observed amplitude-modulated (AM) assemblies of coherently oscillating neurons are described in the frame of the quantum field theory (QFT)Quantum field theory (QFT) of spontaneously broken symmetry theories. Observations of scale-free phenomena in brain activity are related to the coherent dynamics playing a crucial role in the dissipative model. A representation in terms of thermodynamicThermodynamic generalized Carnot-Rankine cycles is provided, which describes the process of formation of the coherent AM patterns as a transition from a disordered, gas-like state of high entropyEntropy to liquid-like organized neuronal configurations of low entropyEntropy. The mental activity (the mind) is described as the search in the backward time, and the reconstruction of the past perceptual experiences aimed to plan the action to be taken by the brain in the future (forward time). Among many hypotheses of possible actions, the brain realizes the one that has the highest Bayes probability to be successful in obtaining the aimed result. The Bayes rule is built-in into the adopted QFTQuantum field theory (QFT) formalism.

Commentary by Giuseppe Vitiello

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发表日期：

2026年

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Giuseppe Vitiello

摘要

Two complementaryVitiello approaches have been used to study the brain and in general biological systems. In one of the approaches, the brain system is split into a large number of components, which are then studied in all their details. The problem of combining the data so accumulated in a working scheme able to account for the macroscopic observed functioning of the brain often is left unsolved since it is actually out of reach of this approach. Contradictory features often arise, indeed. For example, it is not clear how the high effectiveness and stability of some characterizing brain features may result from the random biomolecular activity of the brain component cells. A dilemma already pointed out by Lashley in neuroscience, and by Schrödinger in biology, but still waiting for an answer. This first approach is the naturalistic approach. The other approach is the dynamical approach aiming to provide a comprehension of macroscopic features of the brain behavior based on the data provided by the first approach. Both approaches appear thus to be necessary, although each one of them, separately considered, is not sufficient to account for the full understanding of brain functioning. A bridge between these approaches could be built following the strategy successfully used in the study of many-body condensed matter physics. In this direction moves the dissipative many-body model of the brain, where the observed amplitude-modulated (AM) assemblies of coherently oscillating neurons are described in the frame of the quantum field theory (QFT)Quantum field theory (QFT) of spontaneously broken symmetry theories. Observations of scale-free phenomena in brain activity are related to the coherent dynamics playing a crucial role in the dissipative model. A representation in terms of thermodynamicThermodynamic generalized Carnot-Rankine cycles is provided, which describes the process of formation of the coherent AM patterns as a transition from a disordered, gas-like state of high entropyEntropy to liquid-like organized neuronal configurations of low entropyEntropy. The mental activity (the mind) is described as the search in the backward time, and the reconstruction of the past perceptual experiences aimed to plan the action to be taken by the brain in the future (forward time). Among many hypotheses of possible actions, the brain realizes the one that has the highest Bayes probability to be successful in obtaining the aimed result. The Bayes rule is built-in into the adopted QFTQuantum field theory (QFT) formalism.