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噪声振荡器的平均回报时间相位和随机渐近相位的定量比较。

Quantitative comparison of the mean-return-time phase and the stochastic asymptotic phase for noisy oscillators.

机构信息

National Research University Higher School of Economics, Moscow, Russia.

Instituto de Matemática Interdisciplinar, Universidad Complutense de Madrid, Madrid, Spain.

出版信息

Biol Cybern. 2022 Apr;116(2):219-234. doi: 10.1007/s00422-022-00929-6. Epub 2022 Mar 23.

Abstract

Seminal work by A. Winfree and J. Guckenheimer showed that a deterministic phase variable can be defined either in terms of Poincaré sections or in terms of the asymptotic (long-time) behaviour of trajectories approaching a stable limit cycle. However, this equivalence between the deterministic notions of phase is broken in the presence of noise. Different notions of phase reduction for a stochastic oscillator can be defined either in terms of mean-return-time sections or as the argument of the slowest decaying complex eigenfunction of the Kolmogorov backwards operator. Although both notions of phase enjoy a solid theoretical foundation, their relationship remains unexplored. Here, we quantitatively compare both notions of stochastic phase. We derive an expression relating both notions of phase and use it to discuss differences (and similarities) between both definitions of stochastic phase for (i) a spiral sink motivated by stochastic models for electroencephalograms, (ii) noisy limit-cycle systems-neuroscience models, and (iii) a stochastic heteroclinic oscillator inspired by a simple motor-control system.

摘要

温弗里(A. Winfree)和古肯海默(J. Guckenheimer)的开创性工作表明,确定性相位变量既可以用 Poincaré 截面来定义,也可以用趋近稳定极限环的轨迹的渐近(长时间)行为来定义。然而,在存在噪声的情况下,确定性相位的这种等价性被打破。对于随机振荡器,可以根据平均返回时间截面或作为 Kolmogorov 反向算子最慢衰减复本征函数的参数来定义不同的相降阶概念。尽管这两种相位概念都有坚实的理论基础,但它们之间的关系仍未得到探索。在这里,我们定量比较了这两种随机相位概念。我们推导出了一个将这两种相位概念联系起来的表达式,并使用它来讨论这两种随机相位定义之间的差异(和相似之处),包括(i)受脑电刺激随机模型启发的螺旋汇流,(ii)噪声极限环系统-神经科学模型,以及(iii)受简单的电机控制系统启发的随机异宿振荡器。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a04/9068686/269950121293/422_2022_929_Fig1_HTML.jpg

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