Ubiquity of Uncertainty in Neuron Systems

Brandon B. Le; Bennett Lamb; Luke Benfer; Sriharsha Sambangi; Nisal Geemal Vismith; Akshaj Jagarapu

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arXiv · 2507.15702

Ubiquity of Uncertainty in Neuron Systems

Brandon B. Le·Bennett Lamb·Luke Benfer·Sriharsha Sambangi·Nisal Geemal Vismith·Akshaj Jagarapu

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Abstract

We demonstrate that final-state uncertainty is ubiquitous in multistable systems of coupled neuronal maps, meaning that predicting whether one such system will eventually be chaotic or nonchaotic is often nearly impossible. We propose a "chance synchronization" mechanism that governs the emergence of unpredictability in neuron systems and support it by using basin classification, uncertainty exponent, and basin entropy techniques to analyze five simple discrete-time systems, each consisting of a different neuron model. Our results illustrate that uncertainty in neuron systems is not just a product of noise or high-dimensional complexity; it is also a fundamental property of low-dimensional, deterministic models, which has profound implications for understanding brain function, modeling cognition, and interpreting unpredictability in general multistable systems.

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Brandon B. Le, Bennett Lamb, Luke Benfer, Sriharsha Sambangi, Nisal Geemal Vismith, Akshaj Jagarapu. 2025-07-21. Ubiquity of Uncertainty in Neuron Systems. https://arxiv.org/abs/2507.15702

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