Multiscale Entropy of Cardiac and Postural Control Reflects a Flexible Adaptation to a Cognitive Task
In humans, physiological systems involved in maintaining stable conditions for health and well-being are complex, encompassing multiple interactions within and between system components. This complexity is mirrored in the temporal structure of the variability of output signals. Entropy has been reco...
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doaj-f170613b806d4a3086ff36df3b2d63fc2020-11-25T02:30:04ZengMDPI AGEntropy1099-43002019-10-012110102410.3390/e21101024e21101024Multiscale Entropy of Cardiac and Postural Control Reflects a Flexible Adaptation to a Cognitive TaskEstelle Blons0Laurent M. Arsac1Pierre Gilfriche2Veronique Deschodt-Arsac3Univ. Bordeaux, CNRS, Laboratoire IMS, UMR 5218, 33400 Talence, FranceUniv. Bordeaux, CNRS, Laboratoire IMS, UMR 5218, 33400 Talence, FranceUniv. Bordeaux, CNRS, Laboratoire IMS, UMR 5218, 33400 Talence, FranceUniv. Bordeaux, CNRS, Laboratoire IMS, UMR 5218, 33400 Talence, FranceIn humans, physiological systems involved in maintaining stable conditions for health and well-being are complex, encompassing multiple interactions within and between system components. This complexity is mirrored in the temporal structure of the variability of output signals. Entropy has been recognized as a good marker of systems complexity, notably when calculated from heart rate and postural dynamics. A degraded entropy is generally associated with frailty, aging, impairments or diseases. In contrast, high entropy has been associated with the elevated capacity to adjust to an ever-changing environment, but the link is unknown between entropy and the capacity to cope with cognitive tasks in a healthy young to middle-aged population. Here, we addressed classic markers (time and frequency domains) and refined composite multiscale entropy (MSE) markers (after pre-processing) of heart rate and postural sway time series in 34 participants during quiet versus cognitive task conditions. Recordings lasted 10 min for heart rate and 51.2 s for upright standing, providing time series lengths of 500–600 and 2048 samples, respectively. The main finding was that entropy increased during cognitive tasks. This highlights the possible links between our entropy measures and the systems complexity that probably facilitates a control remodeling and a flexible adaptability in our healthy participants. We conclude that entropy is a reliable marker of neurophysiological complexity and adaptability in autonomic and somatic systems.https://www.mdpi.com/1099-4300/21/10/1024heart rate variabilitypostureentropycomplexitycognitive task |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Estelle Blons Laurent M. Arsac Pierre Gilfriche Veronique Deschodt-Arsac |
spellingShingle |
Estelle Blons Laurent M. Arsac Pierre Gilfriche Veronique Deschodt-Arsac Multiscale Entropy of Cardiac and Postural Control Reflects a Flexible Adaptation to a Cognitive Task Entropy heart rate variability posture entropy complexity cognitive task |
author_facet |
Estelle Blons Laurent M. Arsac Pierre Gilfriche Veronique Deschodt-Arsac |
author_sort |
Estelle Blons |
title |
Multiscale Entropy of Cardiac and Postural Control Reflects a Flexible Adaptation to a Cognitive Task |
title_short |
Multiscale Entropy of Cardiac and Postural Control Reflects a Flexible Adaptation to a Cognitive Task |
title_full |
Multiscale Entropy of Cardiac and Postural Control Reflects a Flexible Adaptation to a Cognitive Task |
title_fullStr |
Multiscale Entropy of Cardiac and Postural Control Reflects a Flexible Adaptation to a Cognitive Task |
title_full_unstemmed |
Multiscale Entropy of Cardiac and Postural Control Reflects a Flexible Adaptation to a Cognitive Task |
title_sort |
multiscale entropy of cardiac and postural control reflects a flexible adaptation to a cognitive task |
publisher |
MDPI AG |
series |
Entropy |
issn |
1099-4300 |
publishDate |
2019-10-01 |
description |
In humans, physiological systems involved in maintaining stable conditions for health and well-being are complex, encompassing multiple interactions within and between system components. This complexity is mirrored in the temporal structure of the variability of output signals. Entropy has been recognized as a good marker of systems complexity, notably when calculated from heart rate and postural dynamics. A degraded entropy is generally associated with frailty, aging, impairments or diseases. In contrast, high entropy has been associated with the elevated capacity to adjust to an ever-changing environment, but the link is unknown between entropy and the capacity to cope with cognitive tasks in a healthy young to middle-aged population. Here, we addressed classic markers (time and frequency domains) and refined composite multiscale entropy (MSE) markers (after pre-processing) of heart rate and postural sway time series in 34 participants during quiet versus cognitive task conditions. Recordings lasted 10 min for heart rate and 51.2 s for upright standing, providing time series lengths of 500–600 and 2048 samples, respectively. The main finding was that entropy increased during cognitive tasks. This highlights the possible links between our entropy measures and the systems complexity that probably facilitates a control remodeling and a flexible adaptability in our healthy participants. We conclude that entropy is a reliable marker of neurophysiological complexity and adaptability in autonomic and somatic systems. |
topic |
heart rate variability posture entropy complexity cognitive task |
url |
https://www.mdpi.com/1099-4300/21/10/1024 |
work_keys_str_mv |
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