Dynamical free energy based model for quantum decision making

Tanaka, Shigenori; Umegaki, Toshihito; Nishiyama, Akihiro; Kitoh-Nishioka, Hirotaka

doi:10.1016/j.physa.2022.127979

Cited by 10 publications

(17 citation statements)

References 42 publications

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“…Our parallelism between Bi-logic [45][46][47][48]. and quantum-classical phenomena in the brain can also be considered as the motivation for extending the current quantum-like models of cognition [53][54][55][56][57][58][59][60][61] to take into account quantumclassical processes.…”

Section: Quantum-classical Models Of Brainmentioning

confidence: 99%

“…However, a first application of this principle to quantum decision making can be found in Ref. [53].…”

Section: A General Semanticsmentioning

confidence: 99%

“…Frinston [125,126]. Recently, such a direction of research has witnessed interesting developments [53]. As for QC correlation functions, they are defined in the following way…”

Section: The Quantum-classical Model Of Brainmentioning

confidence: 99%

“…Therefore, given that logic, in accordance with the current theories of the human psyche [45][46][47][48], has a bipartite 'quantum-classical' structure, a clear quantum-classical theory adopted as "regulator" model of the brain activity complies with this theorem . We wish to remark, in passing, that any advancement of such an approach, would produce a significant consolidation of the quantum-like models of cognition developed in the past years [53][54][55][56][57][58][59][60][61].…”

Section: Introductionmentioning

confidence: 99%

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A Quantum-Classical Model of Brain Dynamics

Sergi¹,

Messina²,

Vicario³

et al. 2023

Preprint

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The study of the human psyche has elucidated a bipartite structure of cognition reflecting the quantum-classical nature of any process that generates knowledge and learning governed by brain activity. Acknowledging the importance of such a finding for modelization, we posit an approach to study brain by means of the quantum-classical dynamics of a Mixed Weyl symbol. The Mixed Weyl symbol is used to describe brain processes at the microscopic level and, when averaged over an appropriate ensemble, provides a link to the results of measurements made at the mesoscopic scale. Within this approach, quantum variables (such as,for example, nuclear and electron spins, dipole momenta of particles or molecules, tunneling degrees of freedom, etc may be represented by spinors while the electromagnetic fields and phonon modes involved in the processes are treated either classically or semi-classically, by also considering quantum zero-point fluctuations. Zero-point quantum effects can be incorporated into numerical simulations by controlling the temperature of each field mode via coupling to a dedicated Nosè-Hoover chain thermostat. The temperature of each thermostat is chosen in order to reproduce quantum statistics in the canonical ensemble. In this first paper, we introduce a quantum-classical model of brain dynamics, clarifying its mathematical strucure and focusing the discussion on its predictive value. Analytical consequences of the model are not reported in this paper, since they are left for future work. Our treatment incorporates compatible features of three well-known quantum approaches to brain dynamics - namely the electromagnetic field theory approach, the orchestrated objective reduction theory, and the dissipative quantum model of the brain - and hints at convincing arguments that sustain the existence of quantum-classical processes in the brain activity. All three models are reviewed.

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Section: Quantum-classical Models Of Brainmentioning

confidence: 99%

“…However, a first application of this principle to quantum decision making can be found in Ref. [53].…”

Section: A General Semanticsmentioning

confidence: 99%

“…Frinston [125,126]. Recently, such a direction of research has witnessed interesting developments [53]. As for QC correlation functions, they are defined in the following way…”

Section: The Quantum-classical Model Of Brainmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Quantum-Classical Model of Brain Dynamics

Sergi¹,

Messina²,

Vicario³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…As a final remark in this subsection, the averaged values of Biot number (Bi in Equation [9]) were estimated for Mb and GFP. In each of simulation systems, the Bi value is significantly larger than unity (4.0 ± 0.7 for Mb and 4.6 ± 1.9 for GFP), indicating that the heat conduction inside protein molecule progresses relatively slowly compared to that in surrounding solvent (water in this case).…”

Section: Spherically Symmetric Casesmentioning

confidence: 99%

Thermal conductivity and conductance of protein in aqueous solution: Effects of geometrical shape

et al. 2022

Self Cite

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Considering the importance of elucidating the heat transfer in living cells, we evaluated the thermal conductivity κ and conductance G of hydrated protein through all-atom non-equilibrium molecular dynamics simulation. Extending the computational scheme developed in earlier studies for spherical protein to cylindrical one under the periodic boundary condition, we enabled the theoretical analysis of anisotropic thermal conduction and also discussed the effects of protein size correction on the calculated results. While the present results for myoglobin and green fluorescent protein (GFP) by the spherical model were in fair agreement with previous computational and experimental results, we found that the evaluations for κ and G by the cylindrical model, in particular, those for the longitudinal direction of GFP, were enhanced substantially, but still keeping a consistency with experimental data. We also studied the influence by salt addition of physiological concentration, finding insignificant alteration of thermal conduction of protein in the present case.

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Social Human Collective Decision-Making and Its Applications with Brain Network Models

Thieu,

Melnik

2023

Modeling and Simulation in Science, Engineering and Technology

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Dynamical free energy based model for quantum decision making

Cited by 10 publications

References 42 publications

A Quantum-Classical Model of Brain Dynamics

A Quantum-Classical Model of Brain Dynamics

Thermal conductivity and conductance of protein in aqueous solution: Effects of geometrical shape

Social Human Collective Decision-Making and Its Applications with Brain Network Models

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