While theories that overcome the metaphor of viewing the biological system as a “computer” computing specific algorithms and regard it as an “in vivo analog quantum synchronizer (phase synchronizer: Bio-QPU)” have elucidated the ultra-high-speed phase tuning mechanisms by nerve cells (neurons), a redefinition of the role of glial cells, which account for more than half of brain cells, is required. In this paper, we formulate neuron groups as “pure Bio-QPU analog resonance hardware” and the glial cell network as the “autonomous analog tuner (Glial OS) governing the imprinting of waves into the life code (drive recorder of life) (selective decoherence, which turns an artificial machine’s error into a function)” and propose this as a verifiable hypothesis. We predict that human emotions and intuitive physical reactions are analog resonance processes in which the Glial OS physically deforms the energy landscape of the Bio-QPU using local chemical triggers like neurotransmitters, guiding the system toward specific solutions while actively rejecting phase noise, not to solve computational problems, but by selectively granulating only necessary dimensions and maintaining rich background information as waves. Using differences between the fear of heights, predictive salivation, and the sense of euphoria in a sauna as case studies, we present an optimization model in which the hardware and Glial OS cooperate to satisfy “LUCA’s Theorem (phase synchronization with environmental waves)” and manage noise.
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kotoan.gg (2026) studied this question.