Dynamical disentanglement in an analysis of oscillatory systems: an application to respiratory sinus arrhythmia
- We develop a technique for the multivariate data analysis of perturbed self-sustained oscillators. The approach is based on the reconstruction of the phase dynamics model from observations and on a subsequent exploration of this model. For the system, driven by several inputs, we suggest a dynamical disentanglement procedure, allowing us to reconstruct the variability of the system's output that is due to a particular observed input, or, alternatively, to reconstruct the variability which is caused by all the inputs except for the observed one. We focus on the application of the method to the vagal component of the heart rate variability caused by a respiratory influence. We develop an algorithm that extracts purely respiratory-related variability, using a respiratory trace and times of R-peaks in the electrocardiogram. The algorithm can be applied to other systems where the observed bivariate data can be represented as a point process and a slow continuous signal, e.g. for the analysis of neuronal spiking. This article is part of theWe develop a technique for the multivariate data analysis of perturbed self-sustained oscillators. The approach is based on the reconstruction of the phase dynamics model from observations and on a subsequent exploration of this model. For the system, driven by several inputs, we suggest a dynamical disentanglement procedure, allowing us to reconstruct the variability of the system's output that is due to a particular observed input, or, alternatively, to reconstruct the variability which is caused by all the inputs except for the observed one. We focus on the application of the method to the vagal component of the heart rate variability caused by a respiratory influence. We develop an algorithm that extracts purely respiratory-related variability, using a respiratory trace and times of R-peaks in the electrocardiogram. The algorithm can be applied to other systems where the observed bivariate data can be represented as a point process and a slow continuous signal, e.g. for the analysis of neuronal spiking. This article is part of the theme issue 'Coupling functions: dynamical interaction mechanisms in the physical, biological and social sciences'.…
Verfasserangaben: | Michael RosenblumORCiDGND, Martha Frühwirth, Maximilian MoserORCiD, Arkadij PikovskijORCiDGND |
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DOI: | https://doi.org/10.1098/rsta.2019.0045 |
ISSN: | 1364-503X |
ISSN: | 1471-2962 |
Pubmed ID: | https://pubmed.ncbi.nlm.nih.gov/31656138 |
Titel des übergeordneten Werks (Englisch): | Philosophical Transactions of the Royal Society of London, Series A : Mathematical, Physical and Engineering Sciences |
Verlag: | Royal Society |
Verlagsort: | London |
Publikationstyp: | Wissenschaftlicher Artikel |
Sprache: | Englisch |
Jahr der Erstveröffentlichung: | 2019 |
Erscheinungsjahr: | 2019 |
Datum der Freischaltung: | 12.09.2020 |
Freies Schlagwort / Tag: | autonomic nervous system; phase dynamics; point process; vagal sympathetic activity |
Band: | 377 |
Ausgabe: | 2160 |
Seitenanzahl: | 14 |
Fördernde Institution: | the Marie Sklodowska-Curie GrantEuropean Union (EU) [642563]; Russian Science FoundationRussian Science Foundation (RSF) [17-12-01534] |
Organisationseinheiten: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Mathematik |
Peer Review: | Referiert |
Publikationsweg: | Open Access |
Open Access / Bronze Open-Access |