Study Reveals How Noise Enables Synchronization in Quiescent Biological Systems
Researchers using a 3D Sherman-Rinzel-Keizer model driven by multiplicative Feller noise have identified limitations in standard coherence resonance evaluation and proposed a logarithmic centroid method to more accurately extract optimal noise intensities. The work also characterizes a noise-induced transition from sub-threshold physiological shivering to macroscopic functional synchronization in gap-junction coupled systems. These findings offer a mathematical framework for understanding how quiescent biological systems may exploit stochastic fluctuations for functional recovery.
A preprint posted to arXiv investigates stochastic dynamics in excitable biological systems using a three-dimensional Sherman-Rinzel-Keizer (SRK) model subjected to multiplicative Feller noise. The authors identify a 'bathtub effect' — a broad, flat resonance valley — that causes traditional extremal methods for evaluating coherence resonance (CR) to produce statistical inaccuracies in deeply quiescent systems. To overcome this, they introduce a logarithmic centroid extraction method that filters stochastic jitter and recovers the underlying adiabatic Kramers scaling with high linearity. The study further delineates the physical boundary at which the adiabatic approximation breaks down under strong-noise conditions. Extending the analysis to gap-junction coupled networks, the researchers observe a noise-driven transition from sub-threshold physiological shivering — characterized by statistical correlation but negligible functional output — to macroscopic functional synchronization. The work spans statistical mechanics, biological physics, and nonlinear dynamics, and has undergone at least two revisions including a more rigorous experimental validation section.
What's missing
As a preprint, this work has not yet undergone formal peer review. The study's own scope leaves open questions about generalizability: the model is a specific 3D reduction of pancreatic beta-cell dynamics, and it is unclear how well the logarithmic centroid method or the identified adiabatic breakdown boundary transfer to other excitable biological systems or different noise types. The biological relevance of the gap-junction synchronization transition to specific physiological phenomena (e.g., actual shivering thermogenesis or insulin secretion) is asserted but not experimentally validated in living tissue.
What different sources said
- arXiv q-bioCenter
Breakdown of Adiabatic Scaling and Noise-Induced Functional Synchronization in Deeply Quiescent Excitable Systems
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