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Autore principale: Liu, Regina Yufang
Natura: Recurso digital
Lingua:inglese
Pubblicazione: Zenodo 2026
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Accesso online:https://doi.org/10.5281/zenodo.18818803
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author Liu, Regina Yufang
author_facet Liu, Regina Yufang
contents <p>Neural Stability Architecture defines functional longevity as a property of control-system organization rather than biological time.</p> <p> </p> <p>The framework models human motor and cognitive performance as a hierarchical regulatory structure in which stability depends on the coherence of signal transmission, energy distribution, and adaptive feedback loops. Functional decline is interpreted as progressive regulatory noise accumulation that disrupts cross-level coordination within this architecture.</p> <p> </p> <p>Within this model, longevity does not emerge from tissue preservation alone, but from sustained regulatory coherence under pressure.</p> <p> </p> <p>This work establishes the macro-structural explanation of human functional stability.</p> <p> </p> <p>In parallel, Neural Stability Engineering specifies the executable pathway. It examines how controlled instability and calibrated perturbation may function as structured inputs to reorganize regulatory pathways within sensorimotor systems. Rather than emphasizing surface-level output training, this approach defines intervention conditions under which adaptive recalibration occurs without proportional increases in physical load.</p> <p> </p> <p>The two works are vertically related rather than parallel:</p> <p>Neural Stability Architecture defines the governing model;</p> <p>Neural Stability Engineering proposes the operational mechanism.</p> <p> </p> <p>Together, they form a coherent theoretical and technical framework for understanding and engineering human stability. Note: This framework is now actively developed and commercially implemented by Neural Longevity Labs Inc. as part of the HCS-OS ecosystem.</p>
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spellingShingle Neural Stability Architecture: Toward a Control-Theoretic Framework for Regulatory Noise and Human Functional Longevity
Liu, Regina Yufang
Neural stability
<p>Neural Stability Architecture defines functional longevity as a property of control-system organization rather than biological time.</p> <p> </p> <p>The framework models human motor and cognitive performance as a hierarchical regulatory structure in which stability depends on the coherence of signal transmission, energy distribution, and adaptive feedback loops. Functional decline is interpreted as progressive regulatory noise accumulation that disrupts cross-level coordination within this architecture.</p> <p> </p> <p>Within this model, longevity does not emerge from tissue preservation alone, but from sustained regulatory coherence under pressure.</p> <p> </p> <p>This work establishes the macro-structural explanation of human functional stability.</p> <p> </p> <p>In parallel, Neural Stability Engineering specifies the executable pathway. It examines how controlled instability and calibrated perturbation may function as structured inputs to reorganize regulatory pathways within sensorimotor systems. Rather than emphasizing surface-level output training, this approach defines intervention conditions under which adaptive recalibration occurs without proportional increases in physical load.</p> <p> </p> <p>The two works are vertically related rather than parallel:</p> <p>Neural Stability Architecture defines the governing model;</p> <p>Neural Stability Engineering proposes the operational mechanism.</p> <p> </p> <p>Together, they form a coherent theoretical and technical framework for understanding and engineering human stability. Note: This framework is now actively developed and commercially implemented by Neural Longevity Labs Inc. as part of the HCS-OS ecosystem.</p>
title Neural Stability Architecture: Toward a Control-Theoretic Framework for Regulatory Noise and Human Functional Longevity
topic Neural stability
url https://doi.org/10.5281/zenodo.18818803