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Garcia-Retortillo S, Rizzo R, Wang JWJL, Sitges C, Ivanov PC. Universal spectral profile and dynamic evolution of muscle activation: a hallmark of muscle type and physiological state. J Appl Physiol (1985) 2020; 129:419-441. [PMID: 32673157 DOI: 10.1152/japplphysiol.00385.2020] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
The skeletal muscle is an integrated multicomponent system with complex dynamics of continuous myoelectrical activation of various muscle types across time scales to facilitate muscle coordination among units and adaptation to physiological states. To understand the multiscale dynamics of neuromuscular activity, we investigated spectral characteristics of different muscle types across time scales and their evolution with physiological states. We hypothesized that each muscle type is characterized by a specific spectral profile, reflecting muscle composition and function, that remains invariant over time scales and is universal across subjects. Furthermore, we hypothesized that the myoelectrical activation and corresponding spectral profile during certain movements exhibit an evolution path in time that is unique for each muscle type and reflects responses in muscle dynamics to exercise, fatigue, and aging. To probe the multiscale mechanism of neuromuscular regulation, we developed a novel protocol of repeated squat exercise segments, each performed until exhaustion, and we analyzed differentiated spectral power responses over a range of frequency bands for leg and back muscle activation in young and old subjects. We found that leg and back muscle activation is characterized by muscle-specific spectral profiles, with differentiated frequency band contribution, and a muscle-specific evolution path in response to fatigue and aging that is universal across subjects in each age group. The uncovered universality among subjects in the spectral profile of each muscle at a given physiological state, as well as the robustness in the evolution of these profiles over a range of time scales and states, reveals a previously unrecognized multiscale mechanism underlying the differentiated response of distinct muscle types to exercise-induced fatigue and aging.NEW & NOTEWORTHY To understand coordinated function of distinct fibers in a muscle, we investigated spectral dynamics of muscle activation during maximal exercise across a range of frequency bands and time scales of observation. We discovered a spectral profile that is specific for each muscle type, robust at short, intermediate, and large time scales, universal across subjects, and characterized by a muscle-specific evolution path with accumulation of fatigue and aging, indicating a previously unrecognized multiscale mechanism of muscle tone regulation.
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Affiliation(s)
- Sergi Garcia-Retortillo
- University School of Health and Sport, University of Girona, Salt, Spain.,Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, Massachusetts.,Complex Systems in Sport, INEFC Universitat de Barcelona, Barcelona, Spain
| | - Rossella Rizzo
- Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, Massachusetts.,Evolutionary Systems Group Laboratory, Department of Physics, University of Calabria, Arcavacata di Rende, Italy
| | - Jilin W J L Wang
- Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, Massachusetts
| | - Carol Sitges
- University of Balearic Islands, Department of Psychology, Research Institute of Health Sciences and Health Research Institute of the Balearic Islands, Palma, Spain
| | - Plamen Ch Ivanov
- Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, Massachusetts.,Harvard Medical School and Division of Sleep Medicine, Brigham and Women's Hospital, Boston, Massachusetts.,Institute of Solid State Physics, Bulgarian Academy of Sciences, Sofia, Bulgaria
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Flexible Approach for Classifying EMG Signals for Rehabilitation Applications. NEUROPHYSIOLOGY+ 2020. [DOI: 10.1007/s11062-020-09851-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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