Bounded channel noise in a 5D Hodgkin-Huxley cortical pacemaker model triggers stochastic awakening via Kramers escape deep subthreshold, robust coherence resonance near subcritical Hopf, and noise-accelerated escape to high-frequency irregular bursting suprathreshold.
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D-MODD is a data-derived Langevin stochastic differential equation whose transition kernel reproduces the one-step opinion change probabilities observed in social media data on a polarized climate topic.
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Noise-accelerated Kramers Escape and Coherence Resonance in a 5D Neural Manifold
Bounded channel noise in a 5D Hodgkin-Huxley cortical pacemaker model triggers stochastic awakening via Kramers escape deep subthreshold, robust coherence resonance near subcritical Hopf, and noise-accelerated escape to high-frequency irregular bursting suprathreshold.
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D-MODD: A Diffusion Model of Opinion Dynamics Derived from Online Data
D-MODD is a data-derived Langevin stochastic differential equation whose transition kernel reproduces the one-step opinion change probabilities observed in social media data on a polarized climate topic.