Open AccessNoninvasive inference methods for interaction and noise intensities of coupled oscillators using only spike time data
Author(s) -
Fumito Mori,
Hiroshi Kori
Publication year - 2022
Publication title -
proceedings of the national academy of sciences of the united states of america
Language(s) - English
Resource type - Journals
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.2113620119
Subject(s) - inference , noise (video) , coupling (piping) , computer science , statistical physics , set (abstract data type) , spike (software development) , coupling strength , intensity (physics) , biological system , statistical inference , algorithm , physics , mathematics , statistics , artificial intelligence , optics , mechanical engineering , software engineering , engineering , image (mathematics) , biology , programming language , condensed matter physics
Significance Identifying interactions is essential for understanding self-organized systems because they are a source of order, function, and complexity. However, distinguishing interaction and noise effect is generally difficult because they both critically affect the stability of an ordered state. We propose methods that enable us to simultaneously infer both interaction and noise intensities. Our methods use only the time series of periodic events such as spike time data and do not require any external stimuli. Moreover, it is not necessary to assume a function form to fit. We numerically demonstrate that our methods yield reasonable inference even for a relatively short time series. These features are particularly beneficial for application in biological and chemical complex systems.