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De Bartolo D, Borhanazad M, Goudriaan M, Bekius A, Zandvoort CS, Buizer AI, Morelli D, Assenza C, Vermeulen RJ, Martens BHM, Iosa M, Dominici N. Exploring harmonic walking development in children with unilateral cerebral palsy and typically developing toddlers: Insights from walking experience. Hum Mov Sci 2024; 95:103218. [PMID: 38643727 DOI: 10.1016/j.humov.2024.103218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 04/05/2024] [Accepted: 04/12/2024] [Indexed: 04/23/2024]
Abstract
This longitudinal study investigated the impact of the first independent steps on harmonic gait development in unilateral cerebral palsy (CP) and typically developing (TD) children. We analysed the gait ratio values (GR) by comparing the duration of stride/stance, stance/swing and swing/double support phases. Our investigation focused on identifying a potential trend towards the golden ratio value of 1.618, which has been observed in the locomotion of healthy adults as a characteristic of harmonic walking. Locomotor ability was assessed in both groups at different developmental stages: before and after the emergence of independent walking. Results revealed that an exponential fit was observed only after the first unsupported steps were taken. TD children achieved harmonic walking within a relatively short period (approximately one month) compared to children with CP, who took about seven months to develop harmonic walking. Converging values for stride/stance and stance/swing gait ratios, averaged on the two legs, closely approached the golden ratio in TD children (R2 = 0.9) with no difference in the analysis of the left vs right leg separately. In contrast, children with CP exhibited a trend for stride/stance and stance/swing (R2 = 0.7), with distinct trends observed for the most affected leg which did not reach the golden ratio value for the stride/stance ratio (GR = 1.5), while the least affected leg exceeded it (GR = 1.7). On the contrary, the opposite trend was observed for the stance/swing ratio. These findings indicate an overall harmonic walking in children with CP despite the presence of asymmetry between the two legs. These results underscore the crucial role of the first independent steps in the progressive development of harmonic gait over time.
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Affiliation(s)
- Daniela De Bartolo
- Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Amsterdam Movement Sciences & Institute for Brain and Behaviour Amsterdam, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Laboratory of Neuromotor Physiology, Scientific Institute for Research, Hospitalization and Health Care (IRCCS) Santa Lucia Foundation, Rome, Italy
| | - Marzieh Borhanazad
- Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Amsterdam Movement Sciences & Institute for Brain and Behaviour Amsterdam, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Marije Goudriaan
- Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Amsterdam Movement Sciences & Institute for Brain and Behaviour Amsterdam, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Annike Bekius
- Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Amsterdam Movement Sciences & Institute for Brain and Behaviour Amsterdam, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Coen S Zandvoort
- Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Amsterdam Movement Sciences & Institute for Brain and Behaviour Amsterdam, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Annemieke I Buizer
- Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Rehabilitation Medicine, Amsterdam, the Netherlands; Amsterdam Movement Sciences, Rehabilitation & Development, Amsterdam, the Netherlands; Emma Children's Hospital, Amsterdam UMC, Amsterdam, the Netherlands
| | - Daniela Morelli
- Department of Pediatric Neurorehabilitation, Scientific Institute for Research, Hospitalization and Health Care (IRCCS) Santa Lucia Foundation, Rome, Italy
| | - Carla Assenza
- Department of Pediatric Neurorehabilitation, Scientific Institute for Research, Hospitalization and Health Care (IRCCS) Santa Lucia Foundation, Rome, Italy
| | - R Jeroen Vermeulen
- Department of Pediatric Neurology, Maastricht University Medical Center, School of Mental Health and Neuroscience, Maastricht, the Netherlands
| | - Brian H M Martens
- Department of Pediatric Neurology, Maastricht University Medical Center, School of Mental Health and Neuroscience, Maastricht, the Netherlands
| | - Marco Iosa
- Department of Psychology, Sapienza University of Rome, Italy
| | - Nadia Dominici
- Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Amsterdam Movement Sciences & Institute for Brain and Behaviour Amsterdam, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
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Hinnekens E, Berret B, Morard E, Do MC, Barbu-Roth M, Teulier C. Optimization of modularity during development to simplify walking control across multiple steps. Front Neural Circuits 2024; 17:1340298. [PMID: 38343616 PMCID: PMC10853381 DOI: 10.3389/fncir.2023.1340298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 12/14/2023] [Indexed: 02/15/2024] Open
Abstract
Introduction Walking in adults relies on a small number of modules, reducing the number of degrees of freedom that needs to be regulated by the central nervous system (CNS). While walking in toddlers seems to also involve a small number of modules when considering averaged or single-step data, toddlers produce a high amount of variability across strides, and the extent to which this variability interacts with modularity remains unclear. Methods Electromyographic activity from 10 bilateral lower limb muscles was recorded in both adults (n = 12) and toddlers (n = 12) over 8 gait cycles. Toddlers were recorded while walking independently and while being supported by an adult. This condition was implemented to assess if motor variability persisted with reduced balance constraints, suggesting a potential central origin rather than reliance on peripheral regulations. We used non-negative matrix factorization to model the underlying modular command with the Space-by-Time Decomposition method, with or without averaging data, and compared the modular organization of toddlers and adults during multiple walking strides. Results Toddlers were more variable in both conditions (i.e. independent walking and supported by an adult) and required significantly more modules to account for their greater stride-by-stride variability. Activations of these modules varied more across strides and were less parsimonious compared to adults, even with diminished balance constraints. Discussion The findings suggest that modular control of locomotion evolves between toddlerhood and adulthood as the organism develops and practices. Adults seem to be able to generate several strides of walking with less modules than toddlers. The persistence of variability in toddlers when balance constraints were lowered suggests a link with the ability to explore rather than with corrective mechanisms. In conclusion, the capacity of new walkers to flexibly activate their motor command suggests a broader range of possible actions, though distinguishing between modular and non-modular inputs remains challenging.
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Affiliation(s)
- Elodie Hinnekens
- Université Paris-Saclay, CIAMS, Orsay, France
- Université Paris-Saclay, CIAMS, Orléans, France
| | - Bastien Berret
- Université Paris-Saclay, CIAMS, Orsay, France
- Université Paris-Saclay, CIAMS, Orléans, France
| | - Estelle Morard
- Université Paris-Saclay, CIAMS, Orsay, France
- Université Paris-Saclay, CIAMS, Orléans, France
| | - Manh-Cuong Do
- Université Paris-Saclay, CIAMS, Orsay, France
- Université Paris-Saclay, CIAMS, Orléans, France
| | - Marianne Barbu-Roth
- Université Paris Cité, CNRS, Integrative Neuroscience and Cognition Center, Paris, France
| | - Caroline Teulier
- Université Paris-Saclay, CIAMS, Orsay, France
- Université Paris-Saclay, CIAMS, Orléans, France
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Rizzo R, Wang JWJL, DePold Hohler A, Holsapple JW, Vaou OE, Ivanov PC. Dynamic networks of cortico-muscular interactions in sleep and neurodegenerative disorders. FRONTIERS IN NETWORK PHYSIOLOGY 2023; 3:1168677. [PMID: 37744179 PMCID: PMC10512188 DOI: 10.3389/fnetp.2023.1168677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 08/09/2023] [Indexed: 09/26/2023]
Abstract
The brain plays central role in regulating physiological systems, including the skeleto-muscular and locomotor system. Studies of cortico-muscular coordination have primarily focused on associations between movement tasks and dynamics of specific brain waves. However, the brain-muscle functional networks of synchronous coordination among brain waves and muscle activity rhythms that underlie locomotor control remain unknown. Here we address the following fundamental questions: what are the structure and dynamics of cortico-muscular networks; whether specific brain waves are main network mediators in locomotor control; how the hierarchical network organization relates to distinct physiological states under autonomic regulation such as wake, sleep, sleep stages; and how network dynamics are altered with neurodegenerative disorders. We study the interactions between all physiologically relevant brain waves across cortical locations with distinct rhythms in leg and chin muscle activity in healthy and Parkinson's disease (PD) subjects. Utilizing Network Physiology framework and time delay stability approach, we find that 1) each physiological state is characterized by a unique network of cortico-muscular interactions with specific hierarchical organization and profile of links strength; 2) particular brain waves play role as main mediators in cortico-muscular interactions during each state; 3) PD leads to muscle-specific breakdown of cortico-muscular networks, altering the sleep-stage stratification pattern in network connectivity and links strength. In healthy subjects cortico-muscular networks exhibit a pronounced stratification with stronger links during wake and light sleep, and weaker links during REM and deep sleep. In contrast, network interactions reorganize in PD with decline in connectivity and links strength during wake and non-REM sleep, and increase during REM, leading to markedly different stratification with gradual decline in network links strength from wake to REM, light and deep sleep. Further, we find that wake and sleep stages are characterized by specific links strength profiles, which are altered with PD, indicating disruption in the synchronous activity and network communication among brain waves and muscle rhythms. Our findings demonstrate the presence of previously unrecognized functional networks and basic principles of brain control of locomotion, with potential clinical implications for novel network-based biomarkers for early detection of Parkinson's and neurodegenerative disorders, movement, and sleep disorders.
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Affiliation(s)
- Rossella Rizzo
- Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, MA, United States
- Department of Engineering, University of Palermo, Palermo, Italy
| | - Jilin W. J. L. Wang
- Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, MA, United States
| | - Anna DePold Hohler
- Department of Neurology, Steward St. Elizabeth’s Medical Center, Boston, MA, United States
- Department of Neurology, Boston University School of Medicine, Boston, MA, United States
| | - James W. Holsapple
- Department of Neurosurgery, Boston University School of Medicine, Boston, MA, United States
| | - Okeanis E. Vaou
- Department of Neurology, Steward St. Elizabeth’s Medical Center, Boston, MA, United States
- Department of Neurology, Boston University School of Medicine, Boston, MA, United States
| | - Plamen Ch. Ivanov
- Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, MA, United States
- Harvard Medical School and Division of Sleep Medicine, Brigham and Women Hospital, Boston, MA, United States
- Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria
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Garcia-Retortillo S, Romero-Gómez C, Ivanov PC. Network of muscle fibers activation facilitates inter-muscular coordination, adapts to fatigue and reflects muscle function. Commun Biol 2023; 6:891. [PMID: 37648791 PMCID: PMC10468525 DOI: 10.1038/s42003-023-05204-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 08/02/2023] [Indexed: 09/01/2023] Open
Abstract
Fundamental movement patterns require continuous skeletal muscle coordination, where muscle fibers with different timing of activation synchronize their dynamics across muscles with distinct functions. It is unknown how muscle fibers integrate as a network to generate and fine tune movements. We investigate how distinct muscle fiber types synchronize across arm and chest muscles, and respond to fatigue during maximal push-up exercise. We uncover that a complex inter-muscular network of muscle fiber cross-frequency interactions underlies push-up movements. The network exhibits hierarchical organization (sub-networks/modules) with specific links strength stratification profile, reflecting distinct functions of muscles involved in push-up movements. We find network reorganization with fatigue where network modules follow distinct phase-space trajectories reflecting their functional role and adaptation to fatigue. Consistent with earlier observations for squat movements under same protocol, our findings point to general principles of inter-muscular coordination for fundamental movements, and open a new area of research, Network Physiology of Exercise.
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Affiliation(s)
- Sergi Garcia-Retortillo
- Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, MA, 02215, USA
- Department of Health and Exercise Science, Wake Forest University, Winston-Salem, NC, 27190, USA
- Complex Systems in Sport, INEFC University of Barcelona, 08038, Barcelona, Spain
| | - Carlos Romero-Gómez
- Complex Systems in Sport, INEFC University of Barcelona, 08038, Barcelona, Spain
| | - Plamen Ch Ivanov
- Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, MA, 02215, USA.
- Harvard Medical School and Division of Sleep Medicine, Brigham and Women's Hospital, Boston, MA, 02115, USA.
- Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. Georgi Bonchev Str. Block 21, Sofia, 1113, Bulgaria.
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Bach MM, Zandvoort CS, Cappellini G, Ivanenko Y, Lacquaniti F, Daffertshofer A, Dominici N. Development of running is not related to time since onset of independent walking, a longitudinal case study. Front Hum Neurosci 2023; 17:1101432. [PMID: 36875237 PMCID: PMC9978154 DOI: 10.3389/fnhum.2023.1101432] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 01/23/2023] [Indexed: 02/18/2023] Open
Abstract
Introduction Children start to run after they master walking. How running develops, however, is largely unknown. Methods We assessed the maturity of running pattern in two very young, typically developing children in a longitudinal design spanning about three years. Leg and trunk 3D kinematics and electromyography collected in six recording sessions, with more than a hundred strides each, entered our analysis. We recorded walking during the first session (the session of the first independent steps of the two toddlers at the age of 11.9 and 10.6 months) and fast walking or running for the subsequent sessions. More than 100 kinematic and neuromuscular parameters were determined for each session and stride. The equivalent data of five young adults served to define mature running. After dimensionality reduction using principal component analysis, hierarchical cluster analysis based on the average pairwise correlation distance to the adult running cluster served as a measure for maturity of the running pattern. Results Both children developed running. Yet, in one of them the running pattern did not reach maturity whereas in the other it did. As expected, mature running appeared in later sessions (>13 months after the onset of independent walking). Interestingly, mature running alternated with episodes of immature running within sessions. Our clustering approach separated them. Discussion An additional analysis of the accompanying muscle synergies revealed that the participant who did not reach mature running had more differences in muscle contraction when compared to adults than the other. One may speculate that this difference in muscle activity may have caused the difference in running pattern.
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Affiliation(s)
- Margit M. Bach
- Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Amsterdam Movement Sciences & Institute of Brain and Behavior Amsterdam, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Coen S. Zandvoort
- Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Amsterdam Movement Sciences & Institute of Brain and Behavior Amsterdam, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Germana Cappellini
- Laboratory of Neuromotor Physiology, Istituto di Ricovero e Cura a Carattere Scientifico Fondazione Santa Lucia, Rome, Italy
- Department of Systems Medicine, Center of Space Biomedicine, University of Rome Tor Vergata, Rome, Italy
| | - Yury Ivanenko
- Laboratory of Neuromotor Physiology, Istituto di Ricovero e Cura a Carattere Scientifico Fondazione Santa Lucia, Rome, Italy
| | - Francesco Lacquaniti
- Laboratory of Neuromotor Physiology, Istituto di Ricovero e Cura a Carattere Scientifico Fondazione Santa Lucia, Rome, Italy
- Department of Systems Medicine, Center of Space Biomedicine, University of Rome Tor Vergata, Rome, Italy
| | - Andreas Daffertshofer
- Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Amsterdam Movement Sciences & Institute of Brain and Behavior Amsterdam, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Nadia Dominici
- Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Amsterdam Movement Sciences & Institute of Brain and Behavior Amsterdam, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
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Garcia-Retortillo S, Ivanov PC. Inter-muscular networks of synchronous muscle fiber activation. FRONTIERS IN NETWORK PHYSIOLOGY 2022; 2:1059793. [PMID: 36926057 PMCID: PMC10012969 DOI: 10.3389/fnetp.2022.1059793] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Accepted: 10/28/2022] [Indexed: 11/16/2022]
Abstract
Skeletal muscles continuously coordinate to facilitate a wide range of movements. Muscle fiber composition and timing of activation account for distinct muscle functions and dynamics necessary to fine tune muscle coordination and generate movements. Here we address the fundamental question of how distinct muscle fiber types dynamically synchronize and integrate as a network across muscles with different functions. We uncover that physiological states are characterized by unique inter-muscular network of muscle fiber cross-frequency interactions with hierarchical organization of distinct sub-networks and modules, and a stratification profile of links strength specific for each state. We establish how this network reorganizes with transition from rest to exercise and fatigue-a complex process where network modules follow distinct phase-space trajectories reflecting their functional role in movements and adaptation to fatigue. This opens a new area of research, Network Physiology of Exercise, leading to novel network-based biomarkers of health, fitness and clinical conditions.
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Affiliation(s)
- Sergi Garcia-Retortillo
- Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, MA, United States
- Department of Health and Exercise Science, Wake Forest University, Winston-Salem, NC, United States
- Complex Systems in Sport INEFC University of Barcelona, Barcelona, Spain
| | - Plamen Ch. Ivanov
- Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, MA, United States
- Harvard Medical School and Division of Sleep Medicine, Brigham and Women’s Hospital, Boston, MA, United States
- Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria
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Rizzo R, Garcia-Retortillo S, Ivanov PC. Dynamic networks of physiologic interactions of brain waves and rhythms in muscle activity. Hum Mov Sci 2022; 84:102971. [PMID: 35724499 DOI: 10.1016/j.humov.2022.102971] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Accepted: 06/09/2022] [Indexed: 11/25/2022]
Abstract
The brain plays a central role in facilitating vital body functions and in regulating physiological and organ systems, including the skeleto-muscular and locomotor system. While neural control is essential to synchronize and coordinate activation of various muscle groups and muscle fibers within muscle groups in relation to body movements and distinct physiologic states, the dynamic networks of brain-muscle interactions have not been explored and the complex regulatory mechanism of brain-muscle control remains unknown. Here we present a first study of network interactions between brain waves at different cortical locations and peripheral muscle activity across key physiologic states - wake, sleep and distinct sleep stages. Utilizing a novel approach based on the Network Physiology framework and the concept of time delay stability, we find that for each physiologic state the network of cortico-muscular interactions is characterized by a specific hierarchical organization of network topology and network links strength, where particular brain waves are main mediators of interaction and control of muscular activity. Further, we uncover that with transition from one physiological state to another, the brain-muscle interaction network undergoes marked reorganization in the profile of network links strength, indicating a direct association between network structure and physiological state and function. The pronounced stratification in brain-muscle network characteristics across sleep stages is consistent for chin and leg muscle groups and persists across subjects, indicating a remarkable universality and a previously unrecognized basic physiologic mechanism that regulates muscle activity even during rest and in the absence targeted direct movement. Our findings demonstrate previously unrecognized coordination between brain waves and activation of different muscle fiber types within muscle groups, laws of brain-muscle cross-communication and principles of network integration and control. These investigations demonstrate the potential of network-based biomarkers for classification of distinct physiological states and conditions, for the diagnosis and prognosis of neurodegenerative, movement and sleep disorders, and for developing efficient treatment strategies.
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Affiliation(s)
- Rossella Rizzo
- Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, MA 02215, USA; Department of Engineering, University of Palermo, 90128 Palermo, Italy.
| | - Sergi Garcia-Retortillo
- Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, MA 02215, USA
| | - Plamen Ch Ivanov
- Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, MA 02215, USA.
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