Stationarity breaking in coupled physical systems revealed by recurrence analysis
Thiago de Lima Prado, Gustavo Zampier dos Santos Lima, Bruno, Lob\~ao-Soares, George Carlos do Nascimento, Gilberto Corso, Sergio Roberto, Lopes

TL;DR
This paper demonstrates that recurrence quantifier, determinism, can detect stationarity breaking and coupling in physical systems, including physiological data, revealing insights into sleep micro arousals and inter-regional brain interactions.
Contribution
It introduces a novel application of recurrence quantifiers to detect coupling and stationarity breaking in coupled systems and physiological data, advancing non-invasive analysis methods.
Findings
Recurrence quantifier detects stationarity breaking in coupled systems.
Method reveals coupling between hippocampus and motor areas in mice.
Detects micro arousals in sleep from accelerometer data.
Abstract
In this letter we explore how recurrence quantifier, the determinism (), can reveal stationarity breaking and coupling between physical systems. We demonstrate that it is possible to detect small variations in a dynamical system based only on temporal signal displayed by another system coupled to it. To introduce basic ideas, we consider a well known dynamical system composed of two master-slave coupled Lorenz oscillators. We start evidencing that due to the sensitivity of computed from temporal time series of slave oscillator, its is possible to detect the stationary breaking imposed in the master oscillator. As a second example, the method is carried out in a real physiological data acquired from accelerometer sensors () and used to detect micro arousal phenomenology (described by a sharp burst in signal) during sleep periods in…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsNeural dynamics and brain function · Sleep and Wakefulness Research · Circadian rhythm and melatonin
