Nathan M. Thornhill is an independent researcher working at the intersection of
complexity science, information theory, and consciousness studies. His work asks a deceptively
simple question: what separates systems that persist from those that don’t?
The Existence Threshold framework answers it through measurable information dynamics:
integration, differentiation, and the balance between them. Applied to binary discrete systems,
the criterion classified pattern persistence across ten cellular automata without error, and the
same paper reports the boundary where it stops working. Crossing a dimensional boundary costs
roughly 86% of a pattern’s information, measured over 1,500 patterns. That figure is a
measurement at its stated parameters rather than a constant of nature, and his later work traces
what makes it move.
The Dynamic Existence Threshold applies the same balance to system state rather than pattern
persistence. It classifies states well, including sleep stages from EEG and task success from
internal geometry on verifiable-output benchmarks. It is a coherence detector rather than a
forecaster, a boundary drawn by his own pre-registered tests rather than by a reviewer. The
method is the subject of a U.S. provisional patent application.
The work on this page asks whether the internal dynamics that carry a decision to commitment
differ between cortex and AI models running matched tasks.
Thornhill is entirely self-taught. His prior career spans healthcare, from nursing assistant
through nursing-home administration and ICU admissions. He runs a technology consultancy in
Fort Wayne, Indiana, and when he isn’t researching he’s playing guitar, gardening,
or spending time with his wife and daughter.
The sources behind the poster. The preprint carries the full text and the pre-registrations.
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[dataset] Luo TZ et al. 2025. Data from: Transitions in dynamical regime and neural mode during perceptual decisions. Dryad. doi:10.5061/dryad.sj3tx96dm
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[dataset] Neupane S, Fiete I, Jazayeri M. 2024. Mental navigation in the primate entorhinal cortex. DANDI Archive, dandiset 000897. dandiarchive.org/dandiset/000897
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Schiereck SS, Pérez-Rivera DT, Mah A, DeMaegd ML, Hocker D, Ward RM, Savin C, Constantinople CM. 2026. The orbitofrontal cortex updates beliefs for state inference. Neuron 114(3):507–520.e8. doi:10.1016/j.neuron.2025.11.014
[dataset] Schiereck SS et al. 2026. Data from: The orbitofrontal cortex updates beliefs for state inference. Zenodo. doi:10.5281/zenodo.16997337
Searle JR. 2017. Biological naturalism. In: Schneider S, Velmans M, editors. The Blackwell Companion to Consciousness, 2nd ed. Wiley-Blackwell. p. 327–336. doi:10.1002/9781119132363.ch23
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