Non-Markovian Type II-infinity Operator Dynamics in Cortical Fields: Resolving Thermal Decoherence in Neurocomputational Matrices and Orchestrated Objective Reduction

This repository contains the complete peer-replications block—including the computational simulation python source code and the theoretical preprint text—formalizing a non-perturbative, algebraic resolution to the problem of thermal decoherence in quantum neurobiology. By mapping the mammalian cortical connectome onto infinite semi-finite Type II-infinity von Neumann factors, we derive a strict non-Markovian memory kernel via the Nakajima-Zwanzig projection technique. This framework demonstrates how phase information undergoes continuous coherent feedback into localized neural subsystems, neutralizing thermal noise and stabilizing quantum superposition states within macromolecular superradiant tubulin clusters over biological timescales (10–25 ms). The computational suite structurally integrates:1. Neurochemical modulation profiles (Dopamine, Serotonin, Acetylcholine) and anesthetic-induced loss of consciousness parameters.2. A deterministic biomechanical trigger mechanism linking Penrose gravitational self-reduction energy (Eg) directly to the activation thresholds of voltage-gated Na+/K+ ion channels.3. Non-Markovian 1/f^γ power-law fractal memory kinetics under real physiological constraints.4. Holographic Multi-scale Entanglement Renormalization Ansatz (MERA) network flows synchronized with Giulio Tononi's Integrated Information Theory (IIT) Phi-index metrics. File Inventory:- Resolving Thermal Decoherence in Neurocomputational Matrices and Orchestrated Objective Reduction.pdf: Manuscript (Preprint PDF)- README.md: Comprehensive architectural documentation, theoretical preprint text, and experimental replication manual.- quantum_neurobiology_node.py: Autonomous Python execution script computing biophysical parameters and thermodynamic limits across three active macro-cognitive states.