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The Quantum Neuroperceptual Horizon Hypothesis (QNPH): From Quantum Information to Neural Representation and Conscious Experience

Ángel Carrasco, Juan Carlos Montañez

Zenodo (CERN European Organization for Nuclear Research) August 25, 2026 preprint DOI: 10.5281/zenodo.22102662 (opens in new tab)

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AI-extracted from the abstract
Characteristics Theoretical or philosophical paper
Key points Proposes that physical phenomena inaccessible to natural human receptors, including signals detected with quantum instrumentation, may be converted into classical information and then into neurocompatible codes the brain can learn to discriminate and integrate. Argues this indirect pathway is a more conservative, testable alternative to claims of quantum telepathy, faster-than-light communication, or macroscopic quantum states in EEG bands.

Abstract

The Neuroperceptual Horizon Hypothesis proposes that the range of physical phenomena an organism can functionally incorporate into experience is constrained by receptors, transduction mechanisms, neural integration, learning, and technological tools. We extend this framework through the Quantum Neuroperceptual Horizon Hypothesis (QNPH), which examines how information originating in phenomena described by quantum physics could be indirectly incorporated into neural representations through measurement, transduction, computational processing, sensory or brain-computer interfaces, and neuroplasticity. The framework explicitly separates three domains: classical neural dynamics and brain oscillations; quantum-like cognition, which applies quantum probability formalisms without requiring quantum brain physics; and hypotheses proposing functionally relevant quantum processes in the brain, for which evidence remains controversial. QNPH does not posit faster-than-light communication, quantum telepathy, or that conventional EEG bands are macroscopic quantum states. Its central, testable proposition is more conservative: physical phenomena inaccessible to natural human receptors, including signals detected with quantum instrumentation, may be converted into classical information and subsequently into neurocompatible codes that the brain can learn to discriminate and integrate. We present a multiscale model, six postulates, an indirect quantum-to-neural transduction architecture, falsifiable predictions, and a staged experimental program designed to distinguish established evidence from inference and speculation.

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