Quantitative Biology

Quantum Biology of Cognition: A Unified Model for How Living Systems Turn Randomness into Meaningful Time

Authors: Stephan Brown
Comments: 23 Pages. Licensed under CC-BY 4.0

This paper presents a unified theoretical framework that integrates four major pillars of contemporary physics and neuroscience: quantum biology, Integrated Information Theory (IIT), the Free Energy Principle (FEP), and Orchestrated Objective Reduction (Orch-OR). We propose that neural microtubules exploit quantum coherence to convert environmental randomness into the structured, meaningful flow of lived time (Bergson’s durée).A coherence amplification parameter λ is introduced, spanning nine orders of magnitude from bulk water (λ ≈ 1) to the hypothesized gravity-induced objective-reduction regime (λ ≈ 10u2079). Quantum error-correction mechanisms in the microtubule lattice are argued to sustain coherence at physiological temperature long enough to influence cognition and to provide the discrete ~25 ms "moments" of experience observed in ~40 Hz gamma synchrony.The synthesis yields three primary falsifiable predictions testable within 2—5 years using existing techniques: (1) 5—10 % deuteration (Du2082O) should slow visual conjunction search by 15—100 ms due to reduced proton tunneling; (2) two-dimensional electronic spectroscopy of isolated tubulin dimers should reveal coherence persisting ≳ 100 fs at 310 K; (3) anesthetic potency should correlate with reduction in integrated-information proxies (e.g., perturbational complexity indexin ways classical ion-channel models cannot explain.We adopt an epistemically humble stance: the core Orch-OR mechanism remains unproven and is considered improbable under current physics priors, but the framework’s internal consistency and near-term empirical accessibility distinguish it from unfalsifiable speculation. If the three primary predictions all fail in well-designed studies by 2030, the microtubule-based quantum-cognition hypothesis will be regarded as refuted.
Category: Quantitative Biology