FundamentalTimeNew preprint
Alzheimer's, Parkinson's, ALS, and Huntington's disease, four different molecular pathologies, one thermodynamic collapse.
We propose that their diverse molecular signatures are not independent accidents, but different entry points into the same physical failure: the irreversible accumulation of entropy in neural tissue.
📄 Neurodegeneration as Thermodynamic Failure
https://doi.org/10.5281/zenodo.20414888
#Neuroscience #Thermodynamics #Alzheimer #Parkinson #ALS #Huntington #OpenScience #Preprint
Neurodegeneration as Thermodynamic Failure: A Unified Framework for Alzheimer's, Parkinson's, ALS, and Huntington's Disease
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:$$\gamma\,\partial_t\mathcal{I} - D\,\nabla^2\mathcal{I} + m^2\,\mathcal{I} + \lambda\,\mathcal{I}^3 = \kappa\,P_\text{diss}$$ 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, $\Phi$, 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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