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May 29, 20260 citationsOpen Access

Neurodegeneration as Thermodynamic Failure: A Unified Framework for Alzheimer's, Parkinson's, ALS, and Huntington's Disease

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ALAbderrahim Lyoubi-Idrissi

Key Points

  • The study aims to establish a thermodynamic framework to explain neurodegeneration in various diseases. It identifies specific failure modes associated with Alzheimer's, Parkinson's, ALS, and Huntington's disease.
  • Introduced a unified field-theoretic framework analyzing the I-field representing entropy in neural tissue.
  • Derived a master equation governing the dynamics of entropy accumulation and its impact on neurodegeneration.
  • Developed a dimensionless collapse index to quantify the distance from a healthy state.
  • Each neurodegenerative disorder exhibits predicted failure modes; Alzheimer's is linked to metabolic clearance failure.
  • Parkinson's disease features spatial transport blockade, while ALS results from excessive entropy production.
  • Huntington's disease is driven by structural self-regulation collapse, with a collapse index, Φ, indicating necessity of clinical intervention when exceeding unity.

Abstract

We introduce a unified field-theoretic framework that identifies neurodegeneration as a fundamental failure of thermodynamic stability. The core of this theory is the I-field, a scalar field representing the local density of accumulated entropy. This field accumulates wherever neural tissue dissipates energy, propagates along axonal pathways, and modulates ionic conductances through a conformal suppression mechanism. Its evolution is governed by a single master equation: \, ₜI - D\, ²I + m²\, I + \, I³ = \, Pdiss We demonstrate that the four primary neurodegenerative pathologies represent specific and predictable failure modes of this dynamics. Alzheimer’s disease emerges as a failure of metabolic clearance. Parkinson’s disease is characterized by a blockade of spatial transport. Amyotrophic lateral sclerosis results from the hyper-production of entropy, and Huntington’s disease is driven by the collapse of the field’s structural self-regulation. By analyzing these field dynamics, we derive a dimensionless collapse index, , which quantifies the thermodynamic distance between a healthy state and the point of no return. When this index exceeds unity, the functional attractor of the neural substrate vanishes, making clinical collapse a thermodynamic necessity. Unlike traditional models, this framework avoids reliance on empirical rate functions or fitted parameters. It provides a first-principles bridge between non-equilibrium thermodynamics and neural electrophysiology. This approach yields falsifiable predictions regarding representational drift rates and spatial field signatures, offering a new physical foundation for the early diagnosis and thermodynamic classification of neurodegenerative disease.

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Cite This Study

Abderrahim Lyoubi-Idrissi (2026) studied this question.

synapsesocial.com/papers/6a192df7fab5b468c4416efchttps://doi.org/10.5281/zenodo.20414888
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