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Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review
Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review
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TY - CONF
T1 - Noise in interacting biological systems
AU - Stankovski, Tomislav
AU - McClintock, Peter V. E.
AU - Stefanovska, Aneta
PY - 2019/8/23
Y1 - 2019/8/23
N2 - Biological systems are never isolated, usually oscillatory, and invariably subject to noise and fluctuations that may be of either internal or external origin. We present a methodological framework for studying the deterministic interactions of biological oscillatory systems, while at the same time decomposing and evaluating the noise strength. Based on dynamical Bayesian inference, the method models coupled phase oscillators in the presence of dynamical noise. We demonstrate first the potential and the precision of the method on a predefined numerical system. Then we illustrate its usefulness in detecting how the noisestrengths from three human physiological systems – the heart, the lungs and the brain – are affected by general anæsthesia. The results demonstrate the potential of the method for detecting and quantifying noise from biological dynamical systems, quite generally.
AB - Biological systems are never isolated, usually oscillatory, and invariably subject to noise and fluctuations that may be of either internal or external origin. We present a methodological framework for studying the deterministic interactions of biological oscillatory systems, while at the same time decomposing and evaluating the noise strength. Based on dynamical Bayesian inference, the method models coupled phase oscillators in the presence of dynamical noise. We demonstrate first the potential and the precision of the method on a predefined numerical system. Then we illustrate its usefulness in detecting how the noisestrengths from three human physiological systems – the heart, the lungs and the brain – are affected by general anæsthesia. The results demonstrate the potential of the method for detecting and quantifying noise from biological dynamical systems, quite generally.
KW - dynamical Bayesian inference
KW - noise
KW - interactions
KW - coupling functions
KW - biological systems
M3 - Conference paper
T2 - 25th International Conference on Noise and Fluctuations
Y2 - 18 June 2019 through 21 June 2019
ER -