Noise-accelerated Kramers Escape and Coherence Resonance in a 5D Neural Manifold
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arXiv
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| Formato: | Preprint |
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2026
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| _version_ | 1866914536224718848 |
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| author | Wu, Yefan |
| author_facet | Wu, Yefan |
| contents | Intrinsic channel noise is fundamental to neural processing, yet its state-dependent nature, when constrained by strict Feller boundary conditions, is often overlooked. Here, we demonstrate that this bounded multiplicative noise is not merely a source of jitter but an active dynamical force that fundamentally reshapes neural excitability. Investigating a 5D Hodgkin-Huxley-type cortical pacemaker model, we utilize a full-truncation semi-implicit Euler scheme to ensure rigorous probability conservation and domain-preserving integration. Through comprehensive parameter sweeps, we uncover a rich triphasic landscape of noise-induced transitions dictated by the underlying bifurcation structure. Deep in the subthreshold regime, multiplicative noise acts as a constructive force, triggering stochastic awakening via Kramers escape. Near the subcritical Hopf bifurcation, this evolves into highly robust coherence resonance (CR). Crucially, in the supra-threshold oscillatory regime, our framework reveals a striking dynamical shift: a generalized, noise-accelerated Kramers escape. Under extreme multiplicative noise - characteristic of sparse channel populations - strictly bounded fluctuations actively amplify escape rates from the hyperpolarized slow manifold, transforming regular pacing into high-frequency, irregular bursting. Conductance perturbation experiments confirm the profound biological robustness of this transition. These findings establish a physically rigorous mechanism for how boundary-constrained noise drives high-dimensional oscillators toward states of pathological hyperexcitability. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2605_04088 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Noise-accelerated Kramers Escape and Coherence Resonance in a 5D Neural Manifold Wu, Yefan Neurons and Cognition Probability Chaotic Dynamics Biological Physics 37N25, 60H10, 34C23, 92C20 Intrinsic channel noise is fundamental to neural processing, yet its state-dependent nature, when constrained by strict Feller boundary conditions, is often overlooked. Here, we demonstrate that this bounded multiplicative noise is not merely a source of jitter but an active dynamical force that fundamentally reshapes neural excitability. Investigating a 5D Hodgkin-Huxley-type cortical pacemaker model, we utilize a full-truncation semi-implicit Euler scheme to ensure rigorous probability conservation and domain-preserving integration. Through comprehensive parameter sweeps, we uncover a rich triphasic landscape of noise-induced transitions dictated by the underlying bifurcation structure. Deep in the subthreshold regime, multiplicative noise acts as a constructive force, triggering stochastic awakening via Kramers escape. Near the subcritical Hopf bifurcation, this evolves into highly robust coherence resonance (CR). Crucially, in the supra-threshold oscillatory regime, our framework reveals a striking dynamical shift: a generalized, noise-accelerated Kramers escape. Under extreme multiplicative noise - characteristic of sparse channel populations - strictly bounded fluctuations actively amplify escape rates from the hyperpolarized slow manifold, transforming regular pacing into high-frequency, irregular bursting. Conductance perturbation experiments confirm the profound biological robustness of this transition. These findings establish a physically rigorous mechanism for how boundary-constrained noise drives high-dimensional oscillators toward states of pathological hyperexcitability. |
| title | Noise-accelerated Kramers Escape and Coherence Resonance in a 5D Neural Manifold |
| topic | Neurons and Cognition Probability Chaotic Dynamics Biological Physics 37N25, 60H10, 34C23, 92C20 |
| url | https://arxiv.org/abs/2605.04088 |