Abstract

Background: Previous papers have developed a statistical mechanics of neocortical interactions (SMNI) fit to short-term memory and EEG data. Adaptive Simulated Annealing (ASA) has been developed to perform fits to such nonlinear stochastic systems. An N-dimensional path-integral algorithm for quantum systems, qPATHINT, has been developed from classical PATHINT. Both fold short-time propagators (distributions or wave functions) over long times. Previous papers applied qPATHINT to two systems, in neocortical interactions and financial options. Objective: In this paper the quantum path-integral for Calcium ions is used to derive a closed-form analytic solution at arbitrary time that is used to calculate interactions with classical-physics SMNI interactions among scales. Using fits of this SMNI model to EEG data, including these effects, will help determine if this is a reasonable approach. Method: Methods of mathematical-physics for optimization and for path integrals in classical and quantum spaces are used for this project. Studies using supercomputer resources tested various dimensions for their scaling limits. In this paper the quantum path-integral is used to derive a closed-form analytic solution at arbitrary time that is used to calculate interactions with classical-physics SMNI interactions among scales. Results: The mathematical-physics and computer parts of the study are successful, in that there is modest improvement of cost/objective functions used to fit EEG data using these models. Conclusions: This project points to directions for more detailed calculations using more EEG data and qPATHINT at each time slice to propagate quantum calcium waves, synchronized with PATHINT propagation of classical SMNI.

Highlights

  • This project calculates quantum Ca2+ interactions with EEG

  • < p >ψ∗ψ was used in classical-physics statistical mechanics of neocortical interactions (SMNI) fits to EEG data using Adaptive Simulated Annealing (ASA)

  • Training with ASA used 100K generated states over 12 subjects with and without A, followed by 1000 generated states with the simplex local code contained with ASA

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Summary

Objective

In this paper the quantum path-integral for Calcium ions is used to derive a closed-form analytic solution at arbitrary time that is used to calculate interactions with classical-physics SMNI interactions among scales. Using fits of this SMNI model to EEG data, including these effects, will help determine if this is a reasonable approach. Method: Methods of mathematical-physics for optimization and for path integrals in classical and quantum spaces are used for this project. In this paper the quantum path-integral is used to derive a closed-form analytic solution at arbitrary time that is used to calculate interactions with classical-physics SMNI interactions among scales.

Introduction
Synaptic Interactions
Neuronal Interactions
SMNI Parameters From Experiments
Verification of basic SMNI Hypothesis
Three Basic SMNI Models
Comparing EEG Testing Data with Training Data
PATHINT STM
PATHINT STM Visual
Tripartite Synaptic Interactions
Vector Potential of Wire
Effects of Vector Potential on Momenta
Importance Sampling
ASA Applications
Path-Integral Algorithms PATHINT and qPATHINT
Path-Integral Riemannian Geometry
Three Approaches Are Mathematically Equivalent
PATHINT Applications
Shocks
Lessons Learned From SMFM and SMNI
Results
Supercomputer Resources
Quantum Zeno Effects
Nano-Robotic Applications
Free Will
Conclusions
Full Text
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