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A Quantum-Classical Model of Brain Dynamics.

Alessandro Sergi1,2, Antonino Messina3, Carmelo M Vicario4

  • 1Dipartimento di Scienze Matematiche e Informatiche, Scienze Fisiche e Scienze della Terra, Università degli Studi di Messina, viale F. Stagno d'Alcontres 31, 98166 Messina, Italy.

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|May 16, 2023
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Summary
This summary is machine-generated.

This study introduces a quantum-classical Hamiltonian model to explore brain dynamics. It bridges microscopic quantum processes with macroscopic brain measurements, offering a new perspective on the human psyche.

Keywords:
clinical psychologyelectromagnetic brain stimulationneuroscienceopen quantum systemsquantum brainquantum–classical dynamics

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Area of Science:

  • Neuroscience
  • Quantum Physics
  • Computational Biology

Background:

  • The human psyche exhibits a logic structure reflecting the world's quantum-classical nature.
  • Existing quantum brain theories (e.g., electromagnetic, objective reduction, dissipative) offer partial explanations.

Purpose of the Study:

  • To propose a novel quantum-classical Hamiltonian model for brain dynamics.
  • To link microscopic quantum phenomena to macroscopic brain measurements.
  • To integrate existing quantum brain theories.

Main Methods:

  • Utilizing a mixed Weyl symbol to represent brain processes at the microscopic level.
  • Employing spinors for quantum variables and classical/semi-classical treatment for fields and phonons.
  • Incorporating quantum zero-point effects via Nosé-Hoover chain thermostats to simulate quantum statistics.

Main Results:

  • A general quantum-classical Hamiltonian model is introduced.
  • The model provides a framework for studying the quantum-classical interface in the brain.
  • Numerical simulations are planned for future work.

Conclusions:

  • The proposed model offers a unified approach to understanding brain dynamics.
  • It has the potential to reconcile diverse quantum brain theories.
  • This work lays the foundation for future computational investigations into quantum effects in the brain.