Cortical contributions to locomotor primitives in toddlers and adults

Zandvoort, Coen S.; Daffertshofer, Andreas; Dominici, Nadia

doi:10.1016/j.isci.2022.105229

Cited by 14 publications

(15 citation statements)

References 64 publications

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“…Previous research has shown increased beta activity during the double-support phase in cortical activity (Bruijn et al, 2015;Gwin et al, 2011;Seeber et al, 2015;Wagner et al, 2012) and corticomuscular coherence (Roeder et al, 2018;Zandvoort et al, 2021Zandvoort et al, , 2022, suggesting a corticospinal drive to the muscles (Artoni et al, 2017;Jensen et al, 2019). Here we show the modular organization of common spinal input to different lower leg muscles, which compliments previous notions of modular control of gait (Dominici et al, 2011;Ivanenko et al, 2007;Kiehn, 2016).…”

Section: Discussionsupporting

confidence: 90%

“…Here we show the modular organization of common spinal input to different lower leg muscles, which compliments previous notions of modular control of gait (Dominici et al, 2011; Ivanenko et al, 2007; Kiehn, 2016). In particular, muscle synergy analysis has revealed two lateralized muscle synergies that are involved in the touch-down and lift-off of the left and right legs, which show coherent activity with the motor cortices (Zandvoort et al, 2021, 2022) and emerge around the onset of independent walking in children (Dominici et al, 2011). The two lateralized brain-muscle networks identified in the current study were also precisely timed to the critical events of the gait cycle – lift-off and heel strike – and remained activated while the foot was in the air.…”

Section: Discussionmentioning

confidence: 99%

“…This cortical input to spinal motor neurons appears to be reduced in the elderly and may be linked to changes in the temporal coordination of gait (Roeder et al, 2020). Zandvoort and colleagues (2021, 2022) found that cortical beta-band activity was linked with specific patterns of distributed muscle activity (i.e. muscle synergies), which are involved in controlling shear forces to decelerate and accelerate the body (Dominici et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

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Dynamics of brain-muscle networks reveal effects of age and somatosensory function on gait

Roeder

Breakspear

Kerr

et al. 2023

Preprint

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The neural control of walking requires the interaction between multiple sensory and motor systems. We assess brain-muscle networks during overground gait to assess the dynamic interactions between neural systems involved in gait control. Mobile electroencephalography (EEG) and electromyography (EMG) was recorded from 24 healthy young adults, 24 healthy older adults, and 21 individuals with Parkinson's Disease during overground walking. We estimated dynamic functional connectivity between bilateral sensorimotor cortices and eight leg muscles within a gait cycle. Using multivariate analysis, we extracted brain-muscle networks and investigated the inter-subject variability in the network activation patterns. We identified three orthogonal brain-muscle networks within a gait cycle: 1) a bilateral network that is left-right symmetric and mostly active during the double support phase, 2) a left-lateralised network that is activated during the left swing phase, 3) a right-lateralised network active during the right swing phase. These networks span a low-dimensional subspace in which neuromuscular gait dynamics unfold: the trajectories reveal that the networks are simultaneously co-expressed during the double support phase but with different networks dominating the initial and terminal double support phase. Assessing the inter-subject variability in trajectories, we found an age-related contraction of the trajectories corresponding to a general reduction in neuromuscular connectivity at older age and a selective enhancement of the bilateral network in participants with impaired tactile sensitivity of the foot. The three brain-muscle networks provide a parsimonious description of neuromuscular connectivity during overground walking. The inter-subject variability in low-dimensional trajectories is associated with age and somatosensory function. The selective increase of the bilateral network may reflect a compensation strategy to maintain mediolateral gait stability in response to impaired somatosensory information from the feet.

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Section: Discussionsupporting

confidence: 90%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Dynamics of brain-muscle networks reveal effects of age and somatosensory function on gait

Roeder

Breakspear

Kerr

et al. 2023

Preprint

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“…We recruited two children and five adults. The two children (1 male/1 female) were recruited before taking their first independent steps as part of a larger study ( Zandvoort et al, 2022 ). The adult participants (4 male/1 female, 30-45 years old) were recruited by word-of-mouth as part of a previous study ( Cappellini et al, 2006 ).…”

Section: Methodsmentioning

confidence: 99%

“…Of the recorded muscles, the following 11 (bilateral for the children, unilateral for the adults) muscles TA, MG, LG, SOL, RF, VMO, VLO, BF, TFL, GLM, and ES were retained for further analysis. EMG data were visually inspected, and artifacts were removed using a custom-written burst-detection algorithm ( Bach et al, 2021b ; Zandvoort et al, 2022 ). After high-pass (2nd-order bidirectional Butterworth filter at 20 Hz; De Luca et al, 2010 ; Willigenburg et al, 2012 ; Bach et al, 2021b ) and notch filtering (2 nd -order bi-directional Butterworth around k⋅50 Hz, k = 1,…,10, with half-bandwidth of 0.5 Hz), the EMG data were rectified using the modulus of the analytic signal and finally low-pass filtered (bi-directional 2 nd -order Butterworth filter at 10 Hz) to obtain the corresponding EMG envelopes ( Dominici et al, 2011 ; Oliveira et al, 2016 ; Bekius et al, 2021 ).…”

Section: Methodsmentioning

confidence: 99%

Development of running is not related to time since onset of independent walking, a longitudinal case study

Bach

Zandvoort

Cappellini

et al. 2023

Front. Hum. Neurosci.

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IntroductionChildren start to run after they master walking. How running develops, however, is largely unknown.MethodsWe 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.ResultsBoth 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.DiscussionAn 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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Fundamental Approaches of Studying the Neural Origin of Muscle Synergy

Samanta,

Bhattacharyya

2024

Motion Analysis of Biological Systems

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Cortical contributions to locomotor primitives in toddlers and adults

Cited by 14 publications

References 64 publications

Dynamics of brain-muscle networks reveal effects of age and somatosensory function on gait

Dynamics of brain-muscle networks reveal effects of age and somatosensory function on gait

Development of running is not related to time since onset of independent walking, a longitudinal case study

Fundamental Approaches of Studying the Neural Origin of Muscle Synergy

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