Biologically Plausible Quantum Error Correction\\in a Three-Layer Neural Spin Model
Discuss this preprint
Start a discussion What are Sciety discussions?Listed in
This article is not in any list yet, why not save it to one of your lists.Abstract
Whether quantum coherence plays a functional role in neural information processing remains contested, largely because biological environments are deemed too noisy for quantum states to sur- vive at relevant timescales. We construct a three-layer model—nuclear spin memory, radical pair interface, classical electrochemistry—and identify five quantum error correction (QEC) paradigms that map onto known biophysical mechanisms: decoherence-free subspaces (DFS) via 31P singlet states, dynamical decoupling (DD) via protein motional narrowing, purification QEC (PQEC) ex- ploiting enzymatic redundancy (∼104 copies/cell), gauging symmetry protection via radical-pair spin conservation, and catalytic coherence recovery (ICEC) at enzyme active sites. We parametrize the model for two molecular systems: monoamine oxidase A (MAO-A; γeff = 4.55, radical pair un- confirmed) and Drosophila cryptochrome (CRY; γeff = 3.25, radical pair experimentally confirmed, |J| < 1 MHz). We quantify each mechanism individually: DFS provides complete protection against collective dephasing (F = 1.000), DD yields a B−2 0 -dependent relaxation suppression (4.6×107-fold at Earth field vs X-band), and PQEC achieves near-unity fidelity using 64 of ∼104 available copies. We integrate gauging, PQEC, and covariant recovery into a unified three-layer stabilizer and benchmark it on pattern classification, time-series prediction, and quantum-coherent decision dynamics. For MAO-A, the stabilizer significantly outperforms standard covariant QEC in classification (accuracy 85.2% vs 80.0%, p = 0.017, Cohen’s d = 1.19) and coherence preservation (+40% at moderate noise), while for time-series prediction the improvement is not statistically significant (p = 0.79). CRY yields statistically equivalent stabilizer performance (MNIST 86.2% vs 85.2%, p = 0.67; spike median MSE 7.31 vs 7.65, Mann–Whitney p = 0.99), demonstrating that the QEC framework is robust across molecular substrates. CRY’s decisive advantages are experimental: a confirmed radical pair and immunity to homeostatic neurotransmitter buffering. Four falsifiable experiments are proposed.