The multimodality of infant's rhythmic movements as a modulator of the interaction with their caregivers

Transcranial magnetic stimulation (TMS) of the motor cortex can interrupt voluntary contralateral rhythmic limb movements. Using the method of “resetting index” (RI), our study investigated the TMS effect on different types of bimanual movements. Six normal subjects participated. For unimanual movement, each subject tapped either the right or left index finger at a comfortable rate. For bimanual movement, index fingers of both hands tapped in the same (in-phase) direction or in the opposite (antiphase) direction. TMS was applied to each hemisphere separately at various intensities from 0.5 to 1.5 times motor threshold (MT). TMS interruption of rhythm was quantified by RI. For the unimanual movements, TMS disrupted both contralateral and ipsilateral rhythmic hand movements, although the effect was much less in the ipsilateral hand. For the bimanual in-phase task, TMS could simultaneously reset the rhythmic movements of both hands, but the effect on the contralateral hand was less and the effect on the ipsilateral hand was more compared with the unimanual tasks. Similar effects were seen from right and left hemisphere stimulation. TMS had little effect on the bimanual antiphase task. The equal effect of right and left hemisphere stimulation indicates that neither motor cortex is dominant for simple bimanual in-phase movement. The smaller influence of contralateral stimulation and the greater effect of ipsilateral stimulation during bimanual in-phase movement compared with unimanual movement suggest hemispheric coupling. The antiphase movements were resistant to TMS disruption, and this suggests that control of rhythm differs in the 2 tasks. TMS produced a transient asynchrony of movements on the 2 sides, indicating that both motor cortices might be downstream of the clocking command or that the clocking is a consequence of the 2 hemispheres communicating equally with each other.

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Socio-emotional and motor engagement during musical activities in older adults with major neurocognitive impairment

Scientific Reports ◽

10.1038/s41598-021-94686-4 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Lise Hobeika ◽

Matthieu Ghilain ◽

Loris Schiaratura ◽

Micheline Lesaffre ◽

Dominique Huvent-Grelle ◽

...

Keyword(s):

Older Adults ◽

Music Therapy ◽

Body Motion ◽

Emotional Engagement ◽

Live Performance ◽

Rhythmic Movements ◽

Motor Activities ◽

Clinical Benefits ◽

Video Condition ◽

Musical Activities

AbstractAlthough music therapy may engender clinical benefits in patients with neurodegenerative disease, the impacts of social and musical factors of such activities on socio-emotional and motor engagements are poorly understood. To address this issue, non-verbal behaviors of 97 patients with or without major cognitive impairment (CI) were assessed when listening to music or a metronome in front of a musician who was present physically (live) or virtually (video). Socio-emotional engagement was quantified as emotional facial expression production and gaze direction. Motor engagement was quantified as overall body motion and the production of rhythmic movements. In both groups, positive facial expressions were more frequent and rhythmic motor activities lasted longer with music than with a metronome, and during a live performance rather than a video performance. Relative to patients without CI, patients with CI moved less with music, expressed fewer emotions, and spent less time looking at the musician in the video condition and in the metronome condition. The relative reductions in motor and socio-emotional engagements in patients with CI might be markers of disease progression. However, the presence of a live partner induces older adults to engage emotionally and physically in musical activities emphasizing the relevance of using live performance as motivational levers during music therapy.

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The primacy of rhythm: how discrete actions merge into a stable rhythmic pattern

Journal of Neurophysiology ◽

10.1152/jn.00587.2018 ◽

2019 ◽

Vol 121 (2) ◽

pp. 574-587 ◽

Cited By ~ 4

Author(s):

Zhaoran Zhang ◽

Dagmar Sternad

Keyword(s):

Building Blocks ◽

Periodic Pattern ◽

Voluntary Movements ◽

Rhythmic Pattern ◽

Rhythmic Movements ◽

Discrete Movements ◽

Floquet Multipliers ◽

Physiological Processes ◽

Rhythmic Behavior ◽

Virtual Target

This study examined how humans spontaneously merge a sequence of discrete actions into a rhythmic pattern, even when periodicity is not required. Two experiments used a virtual throwing task, in which subjects performed a long sequence of discrete throwing movements, aiming to hit a virtual target. In experiment 1, subjects performed the task for 11 sessions. Although there was no instruction to perform rhythmically, the variability of the interthrow intervals decreased to a level comparable to that of synchronizing with a metronome; furthermore, dwell times shortened or even disappeared with practice. Floquet multipliers and decreasing variability of the arm trajectories estimated in state space indicated an increasing degree of dynamic stability. Subjects who achieved a higher level of periodicity and stability also displayed higher accuracy in the throwing task. To directly test whether rhythmicity affected performance, experiment 2 disrupted the evolving continuity and periodicity by enforcing a pause between successive throws. This discrete group performed significantly worse and with higher variability in their arm trajectories than the self-paced group. These findings are discussed in the context of previous neuroimaging results showing that rhythmic movements involve significantly fewer cortical and subcortical activations than discrete movements and therefore may pose a computationally more parsimonious solution. Such emerging stable rhythms in neuromotor subsystems may serve as building blocks or dynamic primitives for complex actions. The tendency for humans to spontaneously fall into a rhythm in voluntary movements is consistent with the ubiquity of rhythms at all levels of the physiological system. NEW & NOTEWORTHY When performing a series of throws to hit a target, humans spontaneously merged successive actions into a continuous approximately periodic pattern. The degree of rhythmicity and stability correlated with hitting accuracy. Enforcing irregular pauses between throws to disrupt the rhythm deteriorated performance. Stable rhythmic patterns may simplify control of movement and serve as dynamic primitives for more complex actions. This observation reveals that biological systems tend to exhibit rhythmic behavior consistent with a plethora of physiological processes.

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Neural network control for leg rhythmic movements via functional electrical stimulation

2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541) ◽

10.1109/ijcnn.2004.1380121 ◽

2005 ◽

Cited By ~ 1

Author(s):

Zhang Dingguo ◽

Zhu Kuanyi

Keyword(s):

Neural Network ◽

Electrical Stimulation ◽

Functional Electrical Stimulation ◽

Network Control ◽

Neural Network Control ◽

Rhythmic Movements

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Principles of rhythmic motor pattern generation

Physiological Reviews ◽

10.1152/physrev.1996.76.3.687 ◽

1996 ◽

Vol 76 (3) ◽

pp. 687-717 ◽

Cited By ~ 765

Author(s):

E. Marder ◽

R. L. Calabrese

Keyword(s):

Motor Pattern ◽

Pattern Generation ◽

Rhythmic Movements ◽

Motor Patterns ◽

Nervous Systems ◽

Cellular Processes ◽

Rhythmic Motor ◽

Computational Analyses ◽

Motor Pattern Generation ◽

Rhythmic Motor Pattern

Rhythmic movements are produced by central pattern-generating networks whose output is shaped by sensory and neuromodulatory inputs to allow the animal to adapt its movements to changing needs. This review discusses cellular, circuit, and computational analyses of the mechanisms underlying the generation of rhythmic movements in both invertebrate and vertebrate nervous systems. Attention is paid to exploring the mechanisms by which synaptic and cellular processes interact to play specific roles in shaping motor patterns and, consequently, movement.

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Myoelectric Control of Robotic Leg Prostheses and Exoskeletons: A Review

10.1115/detc2021-69203 ◽

2021 ◽

Author(s):

Ali Nasr ◽

Brokoslaw Laschowski ◽

John McPhee

Keyword(s):

Control Systems ◽

Myoelectric Control ◽

Machine Learning Algorithms ◽

Torque Control ◽

Future Research ◽

Reactive Control ◽

Rhythmic Movements ◽

Myoelectric Signals ◽

Joint Torques ◽

Robotic Leg

Abstract Myoelectric signals from the human motor control system can improve the real-time control and neural-machine interface of robotic leg prostheses and exoskeletons for different locomotor activities (e.g., walking, sitting down, stair ascent, and non-rhythmic movements). Here we review the latest advances in myoelectric control designs and propose future directions for research and innovation. We review the different wearable sensor technologies, actuators, signal processing, and pattern recognition algorithms used for myoelectric locomotor control and intent recognition, with an emphasis on the hierarchical architectures of volitional control systems. Common mechanisms within the control architecture include 1) open-loop proportional control with fixed gains, 2) active-reactive control, 3) joint mechanical impedance control, 4) manual-tuning torque control, 5) adaptive control with varying gains, and 6) closed-loop servo actuator control. Based on our review, we recommend that future research consider using musculoskeletal modeling and machine learning algorithms to map myoelectric signals from surface electromyography (EMG) to actuator joint torques, thereby improving the automation and efficiency of next-generation EMG controllers and neural interfaces for robotic leg prostheses and exoskeletons. We also propose an example model-based adaptive impedance EMG controller including muscle and multibody system dynamics. Ongoing advances in the engineering design of myoelectric control systems have implications for both locomotor assistance and rehabilitation.

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Neuronal Mechanisms Controlling Rhythmic Movements in Gastropod Molluscs

Stance and Motion ◽

10.1007/978-1-4899-0821-6_10 ◽

1988 ◽

pp. 107-121 ◽

Cited By ~ 1

Author(s):

Yu. I. Arshavsky ◽

T. G. Deliagina ◽

I. M. Gelfand ◽

G. N. Orlovsky ◽

Yu. V. Panchin ◽

...

Keyword(s):

Rhythmic Movements ◽

Neuronal Mechanisms

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Biomechanical Models for Radial Distance Determination by the Rat Vibrissal System

Journal of Neurophysiology ◽

10.1152/jn.00707.2006 ◽

2007 ◽

Vol 98 (4) ◽

pp. 2439-2455 ◽

Cited By ~ 97

Author(s):

J. Alexander Birdwell ◽

Joseph H. Solomon ◽

Montakan Thajchayapong ◽

Michael A. Taylor ◽

Matthew Cheely ◽

...

Keyword(s):

Angular Position ◽

Three Dimensional ◽

Radial Distance ◽

Rate Of Change ◽

Dynamic State ◽

Rhythmic Movements ◽

Tactile Information ◽

Biomechanical Models ◽

Object Distance ◽

Dimensional Object

Rats use active, rhythmic movements of their whiskers to acquire tactile information about three-dimensional object features. There are no receptors along the length of the whisker; therefore all tactile information must be mechanically transduced back to receptors at the whisker base. This raises the question: how might the rat determine the radial contact position of an object along the whisker? We developed two complementary biomechanical models that show that the rat could determine radial object distance by monitoring the rate of change of moment (or equivalently, the rate of change of curvature) at the whisker base. The first model is used to explore the effects of taper and inherent whisker curvature on whisker deformation and used to predict the shapes of real rat whiskers during deflections at different radial distances. Predicted shapes closely matched experimental measurements. The second model describes the relationship between radial object distance and the rate of change of moment at the base of a tapered, inherently curved whisker. Together, these models can account for recent recordings showing that some trigeminal ganglion (Vg) neurons encode closer radial distances with increased firing rates. The models also suggest that four and only four physical variables at the whisker base—angular position, angular velocity, moment, and rate of change of moment—are needed to describe the dynamic state of a whisker. We interpret these results in the context of our evolving hypothesis that neural responses in Vg can be represented using a state-encoding scheme that includes combinations of these four variables.

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Single (1:1) vs. double (1:2) metronomes for the spontaneous entrainment and stabilisation of human rhythmic movements

Experimental Brain Research ◽

10.1007/s00221-018-5382-4 ◽

2018 ◽

Vol 236 (12) ◽

pp. 3341-3350 ◽

Cited By ~ 3

Author(s):

Manuel Varlet ◽

Rohan Williams ◽

Cécile Bouvet ◽

Peter E. Keller

Keyword(s):

Rhythmic Movements

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Physiology and Morphology of Shared and Specialized Spinal Interneurons for Locomotion and Scratching

Journal of Neurophysiology ◽

10.1152/jn.90235.2008 ◽

2008 ◽

Vol 99 (6) ◽

pp. 2887-2901 ◽

Cited By ~ 44

Author(s):

Ari Berkowitz

Keyword(s):

Direct Evidence ◽

Ventral Horn ◽

Morphological Properties ◽

Rhythmic Movements ◽

Potential Oscillations ◽

Spinal Interneurons ◽

Firing Rates ◽

Motor Outputs ◽

Membrane Potential Oscillations

Distinct types of rhythmic movements that use the same muscles are typically generated largely by shared multifunctional neurons in invertebrates, but less is known for vertebrates. Evidence suggests that locomotion and scratching are produced partly by shared spinal cord interneuronal circuity, although direct evidence with intracellular recording has been lacking. Here, spinal interneurons were recorded intracellularly during fictive swimming and fictive scratching in vivo and filled with Neurobiotin. Some interneurons that were rhythmically activated during both swimming and scratching had axon terminal arborizations in the ventral horn of the hindlimb enlargement, indicating their likely contribution to hindlimb motor outputs during both behaviors. We previously described a morphological group of spinal interneurons (“transverse interneurons” or T neurons) that were rhythmically activated during all forms of fictive scratching at higher peak firing rates and with larger membrane potential oscillations than scratch-activated spinal interneurons with different dendritic orientations. The current study demonstrates that T neurons are activated during both swimming and scratching and thus are components of the shared circuitry. Many spinal interneurons activated during fictive scratching are also activated during fictive swimming (scratch/swim neurons), but others are suppressed during swimming (scratch-specialized neurons). The current study demonstrates that some scratch-specialized neurons receive strong and long-lasting hyperpolarizing inhibition during fictive swimming and are also morphologically distinct from T neurons. Thus this study indicates that locomotion and scratching are produced by a combination of shared and dedicated interneurons whose physiological and morphological properties are beginning to be revealed.

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