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Hinnekens E, Barbu-Roth M, Do MC, Berret B, Teulier C. Generating variability from motor primitives during infant locomotor development. eLife 2023; 12:e87463. [PMID: 37523218 PMCID: PMC10390046 DOI: 10.7554/elife.87463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Accepted: 07/06/2023] [Indexed: 08/01/2023] Open
Abstract
Motor variability is a fundamental feature of developing systems allowing motor exploration and learning. In human infants, leg movements involve a small number of basic coordination patterns called locomotor primitives, but whether and when motor variability could emerge from these primitives remains unknown. Here we longitudinally followed 18 infants on 2-3 time points between birth (~4 days old) and walking onset (~14 months old) and recorded the activity of their leg muscles during locomotor or rhythmic movements. Using unsupervised machine learning, we show that the structure of trial-to-trial variability changes during early development. In the neonatal period, infants own a minimal number of motor primitives but generate a maximal motor variability across trials thanks to variable activations of these primitives. A few months later, toddlers generate significantly less variability despite the existence of more primitives due to more regularity within their activation. These results suggest that human neonates initiate motor exploration as soon as birth by variably activating a few basic locomotor primitives that later fraction and become more consistently activated by the motor system.
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Affiliation(s)
- Elodie Hinnekens
- Université Paris-Saclay, CIAMS, Orsay, France
- Université d'Orléans, CIAMS, Orléans, France
| | - Marianne Barbu-Roth
- Université de Paris, CNRS, Integrative Neuroscience and Cognition Center, Paris, France
| | - Manh-Cuong Do
- Université Paris-Saclay, CIAMS, Orsay, France
- Université d'Orléans, CIAMS, Orléans, France
| | - Bastien Berret
- Université Paris-Saclay, CIAMS, Orsay, France
- Université d'Orléans, CIAMS, Orléans, France
- Institut Universitaire de France, Paris, France
| | - Caroline Teulier
- Université Paris-Saclay, CIAMS, Orsay, France
- Université d'Orléans, CIAMS, Orléans, France
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2
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Rudolph JL, Selen LPJ, Medendorp WP. Plan versus motion-referenced generalization of fast and slow processes in reach adaptation. J Neurophysiol 2023; 129:767-780. [PMID: 36883742 DOI: 10.1152/jn.00294.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/09/2023] Open
Abstract
Generalization in motor learning refers to the transfer of a learned compensation to other relevant contexts. The generalization function is typically assumed to be of Gaussian shape, centered on the planned motion, although more recent studies associate generalization with the actual motion. Because motor learning is thought to involve multiple adaptive processes with different time constants, we hypothesized that these processes have different time-dependent contributions to the generalization. Guided by a model-based approach, the objective of the present study was to experimentally examine these contributions. We first reformulated a validated two-state adaptation model as a combination of weighted motor primitives, each specified as a Gaussian-shaped tuning function. Adaptation in this model is achieved by updating individual weights of the primitives of the fast and slow adaptive process separately. Depending on whether updating occurred in a plan-referenced or a motion-referenced manner, the model predicted distinct contributions to the overall generalization by the slow and fast process. We tested 23 participants in a reach adaptation task, using a spontaneous recovery paradigm consisting of five successive blocks of a long adaptation phase to a viscous force field, a short adaptation phase with the opposite force, and an error-clamp phase. Generalization was assessed in eleven movement directions relative to the trained target direction. Results of our participant population fell within a continuum of evidence for plan-referenced to evidence for motion-referenced updating. This mixture may reflect the differential weighting of explicit and implicit compensation strategies among participants.
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Affiliation(s)
- Judith L Rudolph
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, Netherlands
| | - Luc P J Selen
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, Netherlands
| | - W Pieter Medendorp
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, Netherlands
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3
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Hug F, Avrillon S, Ibáñez J, Farina D. Common synaptic input, synergies and size principle: Control of spinal motor neurons for movement generation. J Physiol 2023; 601:11-20. [PMID: 36353890 PMCID: PMC10098498 DOI: 10.1113/jp283698] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Accepted: 11/07/2022] [Indexed: 11/11/2022] Open
Abstract
Understanding how movement is controlled by the CNS remains a major challenge, with ongoing debate about basic features underlying this control. In current established views, the concepts of motor neuron recruitment order, common synaptic input to motor neurons and muscle synergies are usually addressed separately and therefore seen as independent features of motor control. In this review, we analyse the body of literature in a broader perspective and we identify a unified approach to explain apparently divergent observations at different scales of motor control. Specifically, we propose a new conceptual framework of the neural control of movement, which merges the concept of common input to motor neurons and modular control, together with the constraints imposed by recruitment order. This framework is based on the following assumptions: (1) motor neurons are grouped into functional groups (clusters) based on the common inputs they receive; (2) clusters may significantly differ from the classical definition of motor neuron pools, such that they may span across muscles and/or involve only a portion of a muscle; (3) clusters represent functional modules used by the CNS to reduce the dimensionality of the control; and (4) selective volitional control of single motor neurons within a cluster receiving common inputs cannot be achieved. Here, we discuss this framework and its underlying theoretical and experimental evidence.
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Affiliation(s)
- François Hug
- Université Côte d'Azur, LAMHESS, Nice, France.,School of Biomedical Sciences, The University of Queensland, Brisbane, QLD, Australia
| | - Simon Avrillon
- Department of Bioengineering, Imperial College London, London, UK
| | - Jaime Ibáñez
- Department of Bioengineering, Imperial College London, London, UK.,BSICoS, IIS Aragón, Universidad de Zaragoza, Zaragoza, Spain.,Department for Clinical and movement neurosciences, Institute of Neurology, University College London, London, UK
| | - Dario Farina
- Department of Bioengineering, Imperial College London, London, UK
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4
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Chiovetto E, Salatiello A, d'Avella A, Giese MA. Toward a unifying framework for the modeling and identification of motor primitives. Front Comput Neurosci 2022; 16:926345. [PMID: 36172054 PMCID: PMC9510628 DOI: 10.3389/fncom.2022.926345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 08/08/2022] [Indexed: 11/13/2022] Open
Abstract
A large body of evidence suggests that human and animal movements, despite their apparent complexity and flexibility, are remarkably structured. Quantitative analyses of various classes of motor behaviors consistently identify spatial and temporal features that are invariant across movements. Such invariant features have been observed at different levels of organization in the motor system, including the electromyographic, kinematic, and kinetic levels, and are thought to reflect fixed modules-named motor primitives-that the brain uses to simplify the construction of movement. However, motor primitives across space, time, and organization levels are often described with ad-hoc mathematical models that tend to be domain-specific. This, in turn, generates the need to use model-specific algorithms for the identification of both the motor primitives and additional model parameters. The lack of a comprehensive framework complicates the comparison and interpretation of the results obtained across different domains and studies. In this work, we take the first steps toward addressing these issues, by introducing a unifying framework for the modeling and identification of qualitatively different classes of motor primitives. Specifically, we show that a single model, the anechoic mixture model, subsumes many popular classes of motor primitive models. Moreover, we exploit the flexibility of the anechoic mixture model to develop a new class of identification algorithms based on the Fourier-based Anechoic Demixing Algorithm (FADA). We validate our framework by identifying eight qualitatively different classes of motor primitives from both simulated and experimental data. We show that, compared to established model-specific algorithms for the identification of motor primitives, our flexible framework reaches overall comparable and sometimes superior reconstruction performance. The identification framework is publicly released as a MATLAB toolbox (FADA-T, https://tinyurl.com/compsens) to facilitate the identification and comparison of different motor primitive models.
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Affiliation(s)
- Enrico Chiovetto
- Section for Computational Sensomotorics, Centre for Integrative Neuroscience, Hertie Institute for Clinical Brain Research, University Clinic Tübingen, Tübingen, Germany
| | - Alessandro Salatiello
- Section for Computational Sensomotorics, Centre for Integrative Neuroscience, Hertie Institute for Clinical Brain Research, University Clinic Tübingen, Tübingen, Germany
| | - Andrea d'Avella
- Laboratory of Neuromotor Physiology, IRCCS Fondazione Santa Lucia, Rome, Italy
- Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, Italy
| | - Martin A. Giese
- Section for Computational Sensomotorics, Centre for Integrative Neuroscience, Hertie Institute for Clinical Brain Research, University Clinic Tübingen, Tübingen, Germany
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5
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McMahon C, Kowalski DP, Krupka AJ, Lemay MA. Single-cell and ensemble activity of lumbar intermediate and ventral horn interneurons in the spinal air-stepping cat. J Neurophysiol 2022; 127:99-115. [PMID: 34851739 PMCID: PMC8721903 DOI: 10.1152/jn.00202.2021] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 11/30/2021] [Accepted: 12/01/2021] [Indexed: 12/18/2022] Open
Abstract
We explored the relationship between population interneuronal network activation and motor output in the adult, in vivo, air-stepping, spinal cat. By simultaneously measuring the activity of large numbers of spinal interneurons, we explored ensembles of coherently firing interneurons and their relation to motor output. In addition, the networks were analyzed in relation to their spatial distribution along the lumbar enlargement for evidence of localized groups driving particular phases of the locomotor step cycle. We simultaneously recorded hindlimb EMG activity during stepping and extracellular signals from 128 channels across two polytrodes inserted within lamina V-VII of two separate lumbar segments. Results indicated that spinal interneurons participate in one of two ensembles that are highly correlated with the flexor or the extensor muscle bursts during stepping. Interestingly, less than half of the isolated single units were significantly unimodally tuned during the step cycle whereas >97% of the single units of the ensembles were significantly correlated with muscle activity. These results show the importance of population scale analysis in neural studies of behavior as there is a much greater correlation between muscle activity and ensemble firing than between muscle activity and individual neurons. Finally, we show that there is no correlation between interneurons' rostrocaudal locations within the lumbar enlargement and their preferred phase of firing or ensemble participation. These findings indicate that spinal interneurons of lamina V-VII encoding for different phases of the locomotor cycle are spread throughout the lumbar enlargement in the adult spinal cord.NEW & NOTEWORTHY We report on the ensemble organization of interneuronal activity in the spinal cord during locomotor movements and show that lumbar intermediate zone interneurons organize in two groups related to the two major phases of walking: stance and swing. Ensemble organization is also shown to better correlate with muscular output than single-cell activity, although ensemble membership does not appear to be somatotopically organized within the spinal cord.
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Affiliation(s)
- Chantal McMahon
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, Pennsylvania
| | - David P Kowalski
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, Pennsylvania
| | | | - Michel A Lemay
- Department of Bioengineering, Temple University, Philadelphia, Pennsylvania
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6
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Kim S, Kwon J, Kim JM, Park FC, Yeo SH. On the encoding capacity of human motor adaptation. J Neurophysiol 2021; 126:123-139. [PMID: 34077281 DOI: 10.1152/jn.00593.2020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Primitive-based models of motor learning suggest that adaptation occurs by tuning the responses of motor primitives. Based on this idea, we consider motor learning as an information encoding procedure, that is, a procedure of encoding a motor skill into primitives. The capacity of encoding is determined by the number of recruited primitives, which depends on how many primitives are "visited" by the movement, and this leads to a rather counterintuitive prediction that faster movement, where a larger number of motor primitives are involved, allows learning more complicated motor skills. Here, we provide a set of experimental results that support this hypothesis. First, we show that learning occurs only with movement, that is, only with nonzero encoding capacity. When participants were asked to counteract a rotating force applied to a robotic handle, they were unable to do so when maintaining a static posture but were able to adapt when making small circular movements. Our second experiment further investigated how adaptation is affected by movement speed. When adapting to a simple (low-information-content) force field, fast (high-capacity) movement did not have an advantage over slow (low-capacity) movement. However, for a complex (high-information-content) force field, the fast movement showed a significant advantage over slow movement. Our final experiment confirmed that the observed benefit of high-speed movement is only weakly affected by mechanical factors. Taken together, our results suggest that the encoding capacity is a genuine limiting factor of human motor adaptation.NEW & NOTEWORTHY We propose a novel concept called "encoding capacity" of motor adaptation, which describes an inherent limiting-factor of our brain's ability to learn new motor skills, just like any other storage system. By reinterpreting the existing primitive-based models of motor learning, we hypothesize that the encoding capacity is determined by the size of the movement, and present a set of experimental evidence suggesting that such limiting effect of encoding capacity does exist in human motor adaptation.
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Affiliation(s)
- Seungyeon Kim
- Robotics Laboratory, Department of Mechanical and Aerospace Engineering, Seoul National University, Seoul, South Korea
| | - Jaewoon Kwon
- Robotics Laboratory, Department of Mechanical and Aerospace Engineering, Seoul National University, Seoul, South Korea
| | - Jin-Min Kim
- School of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Frank Chongwoo Park
- Robotics Laboratory, Department of Mechanical and Aerospace Engineering, Seoul National University, Seoul, South Korea
| | - Sang-Hoon Yeo
- School of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, Birmingham, United Kingdom
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7
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Nunes PF, Ostan I, Siqueira AAG. Evaluation of Motor Primitive-Based Adaptive Control for Lower Limb Exoskeletons. Front Robot AI 2020; 7:575217. [PMID: 33501336 PMCID: PMC7805746 DOI: 10.3389/frobt.2020.575217] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Accepted: 11/24/2020] [Indexed: 12/29/2022] Open
Abstract
In order to assist after-stroke individuals to rehabilitate their movements, research centers have developed lower limbs exoskeletons and control strategies for them. Robot-assisted therapy can help not only by providing support, accuracy, and precision while performing exercises, but also by being able to adapt to different patient needs, according to their impairments. As a consequence, different control strategies have been employed and evaluated, although with limited effectiveness. This work presents a bio-inspired controller, based on the concept of motor primitives. The proposed approach was evaluated on a lower limbs exoskeleton, in which the knee joint was driven by a series elastic actuator. First, to extract the motor primitives, the user torques were estimated by means of a generalized momentum-based disturbance observer combined with an extended Kalman filter. These data were provided to the control algorithm, which, at every swing phase, assisted the subject to perform the desired movement, based on the analysis of his previous step. Tests are performed in order to evaluate the controller performance for a subject walking actively, passively, and at a combination of these two conditions. Results suggest that the robot assistance is capable of compensating the motor primitive weight deficiency when the subject exerts less torque than expected. Furthermore, though only the knee joint was actuated, the motor primitive weights with respect to the hip joint were influenced by the robot torque applied at the knee. The robot also generated torque to compensate for eventual asynchronous movements of the subject, and adapted to a change in the gait characteristics within three to four steps.
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Affiliation(s)
- Polyana F. Nunes
- Rehabilitation Robotics Laboratory, Department of Mechanical Engineering, São Carlos School of Engineering, University of São Paulo, São Carlos, Brazil
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8
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Mileti I, Zampogna A, Santuz A, Asci F, Del Prete Z, Arampatzis A, Palermo E, Suppa A. Muscle Synergies in Parkinson's Disease. Sensors (Basel) 2020; 20:E3209. [PMID: 32517013 PMCID: PMC7308810 DOI: 10.3390/s20113209] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Revised: 05/28/2020] [Accepted: 06/03/2020] [Indexed: 01/01/2023]
Abstract
Over the last two decades, experimental studies in humans and other vertebrates have increasingly used muscle synergy analysis as a computational tool to examine the physiological basis of motor control. The theoretical background of muscle synergies is based on the potential ability of the motor system to coordinate muscles groups as a single unit, thus reducing high-dimensional data to low-dimensional elements. Muscle synergy analysis may represent a new framework to examine the pathophysiological basis of specific motor symptoms in Parkinson's disease (PD), including balance and gait disorders that are often unresponsive to treatment. The precise mechanisms contributing to these motor symptoms in PD remain largely unknown. A better understanding of the pathophysiology of balance and gait disorders in PD is necessary to develop new therapeutic strategies. This narrative review discusses muscle synergies in the evaluation of motor symptoms in PD. We first discuss the theoretical background and computational methods for muscle synergy extraction from physiological data. We then critically examine studies assessing muscle synergies in PD during different motor tasks including balance, gait and upper limb movements. Finally, we speculate about the prospects and challenges of muscle synergy analysis in order to promote future research protocols in PD.
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Affiliation(s)
- Ilaria Mileti
- Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, 00184 Rome, Italy; (I.M.); (Z.D.P.); (E.P.)
| | - Alessandro Zampogna
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy; (A.Z.); (F.A.)
| | - Alessandro Santuz
- Department of Training and Movement Sciences, Humboldt-Universität zu Berlin, 10115 Berlin, Germany; (A.S.); (A.A.)
- Berlin School of Movement Science, Humboldt-Universität zu Berlin, 10115 Berlin, Germany
- Atlantic Mobility Action Project, Brain Repair Centre, Department of Medical Neuroscience, Dalhousie University, Halifax, NS B3H 4R2, Canada
| | - Francesco Asci
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy; (A.Z.); (F.A.)
| | - Zaccaria Del Prete
- Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, 00184 Rome, Italy; (I.M.); (Z.D.P.); (E.P.)
| | - Adamantios Arampatzis
- Department of Training and Movement Sciences, Humboldt-Universität zu Berlin, 10115 Berlin, Germany; (A.S.); (A.A.)
- Berlin School of Movement Science, Humboldt-Universität zu Berlin, 10115 Berlin, Germany
| | - Eduardo Palermo
- Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, 00184 Rome, Italy; (I.M.); (Z.D.P.); (E.P.)
| | - Antonio Suppa
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy; (A.Z.); (F.A.)
- IRCCS Neuromed, 86077 Pozzilli (IS), Italy
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9
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Tieck JCV, Schnell T, Kaiser J, Mauch F, Roennau A, Dillmann R. Generating Pointing Motions for a Humanoid Robot by Combining Motor Primitives. Front Neurorobot 2019; 13:77. [PMID: 31619981 PMCID: PMC6759768 DOI: 10.3389/fnbot.2019.00077] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Accepted: 09/02/2019] [Indexed: 02/04/2023] Open
Abstract
The human motor system is robust, adaptive and very flexible. The underlying principles of human motion provide inspiration for robotics. Pointing at different targets is a common robotics task, where insights about human motion can be applied. Traditionally in robotics, when a motion is generated it has to be validated so that the robot configurations involved are appropriate. The human brain, in contrast, uses the motor cortex to generate new motions reusing and combining existing knowledge before executing the motion. We propose a method to generate and control pointing motions for a robot using a biological inspired architecture implemented with spiking neural networks. We outline a simplified model of the human motor cortex that generates motions using motor primitives. The network learns a base motor primitive for pointing at a target in the center, and four correction primitives to point at targets up, down, left and right from the base primitive, respectively. The primitives are combined to reach different targets. We evaluate the performance of the network with a humanoid robot pointing at different targets marked on a plane. The network was able to combine one, two or three motor primitives at the same time to control the robot in real-time to reach a specific target. We work on extending this work from pointing to a given target to performing a grasping or tool manipulation task. This has many applications for engineering and industry involving real robots.
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Affiliation(s)
| | - Tristan Schnell
- FZI Research Center for Information Technology, Karlsruhe, Germany
| | - Jacques Kaiser
- FZI Research Center for Information Technology, Karlsruhe, Germany
| | - Felix Mauch
- FZI Research Center for Information Technology, Karlsruhe, Germany
| | - Arne Roennau
- FZI Research Center for Information Technology, Karlsruhe, Germany
| | - Rüdiger Dillmann
- FZI Research Center for Information Technology, Karlsruhe, Germany.,Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
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10
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Yang Q, Logan D, Giszter SF. Motor primitives are determined in early development and are then robustly conserved into adulthood. Proc Natl Acad Sci U S A 2019; 116:12025-34. [PMID: 31138689 DOI: 10.1073/pnas.1821455116] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
Motor patterns in legged vertebrates show modularity in both young and adult animals, comprising motor synergies or primitives. Are such spinal modules observed in young mammals conserved into adulthood or altered? Conceivably, early circuit modules alter radically through experience and descending pathways' activity. We analyze lumbar motor patterns of intact adult rats and the same rats after spinal transection and compare these with adult rats spinal transected 5 days postnatally, before most motor experience, using only rats that never developed hind limb weight bearing. We use independent component analysis (ICA) to extract synergies from electromyography (EMG). ICA information-based methods identify both weakly active and strongly active synergies. We compare all spatial synergies and their activation/drive strengths as proxies of spinal modules and their underlying circuits. Remarkably, we find that spatial primitives/synergies of adult injured and neonatal injured rats differed insignificantly, despite different developmental histories. However, intact rats possess some synergies that differ significantly, although modestly, in spatial structure. Rats injured as adults were more similar in modularity to rats that had neonatal spinal transection than to themselves before injury. We surmise that spinal circuit modules for spatial synergy patterns may be determined early, before postnatal day 5 (P5), and remain largely unaltered by subsequent development or weight-bearing experience. An alternative explanation but equally important is that, after complete spinal transection, both neonatal and mature adult spinal cords rapidly converge to common synergy sets. This fundamental or convergent synergy circuitry, fully determined by P5, is revealed after spinal cord transection.
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11
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Bollu T, Whitehead SC, Prasad N, Walker J, Shyamkumar N, Subramaniam R, Kardon B, Cohen I, Goldberg JH. Automated home cage training of mice in a hold-still center-out reach task. J Neurophysiol 2018; 121:500-512. [PMID: 30540551 DOI: 10.1152/jn.00667.2018] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
An obstacle to understanding neural mechanisms of movement is the complex, distributed nature of the mammalian motor system. Here we present a novel behavioral paradigm for high-throughput dissection of neural circuits underlying mouse forelimb control. Custom touch-sensing joysticks were used to quantify mouse forelimb trajectories with micron-millisecond spatiotemporal resolution. Joysticks were integrated into computer-controlled, rack-mountable home cages, enabling batches of mice to be trained in parallel. Closed loop behavioral analysis enabled online control of reward delivery for automated training. We used this system to show that mice can learn, with no human handling, a direction-specific hold-still center-out reach task in which a mouse first held its right forepaw still before reaching out to learned spatial targets. Stabilogram diffusion analysis of submillimeter-scale micromovements produced during the hold demonstrate that an active control process, akin to upright balance, was implemented to maintain forepaw stability. Trajectory decomposition methods, previously used in primates, were used to segment hundreds of thousands of forelimb trajectories into millions of constituent kinematic primitives. This system enables rapid dissection of neural circuits for controlling motion primitives from which forelimb sequences are built. NEW & NOTEWORTHY A novel joystick design resolves mouse forelimb kinematics with micron-millisecond precision. Home cage training is used to train mice in a hold-still center-out reach task. Analytical methods, previously used in primates, are used to decompose mouse forelimb trajectories into kinematic primitives.
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Affiliation(s)
- Tejapratap Bollu
- Department of Neurobiology and Behavior, Cornell University , Ithaca, New York
| | | | - Nikil Prasad
- Department of Neurobiology and Behavior, Cornell University , Ithaca, New York
| | - Jackson Walker
- Department of Neurobiology and Behavior, Cornell University , Ithaca, New York
| | - Nitin Shyamkumar
- Department of Neurobiology and Behavior, Cornell University , Ithaca, New York
| | - Raghav Subramaniam
- Department of Neurobiology and Behavior, Cornell University , Ithaca, New York
| | - Brian Kardon
- Department of Neurobiology and Behavior, Cornell University , Ithaca, New York
| | - Itai Cohen
- Department of Physics, Cornell University , Ithaca, New York
| | - Jesse H Goldberg
- Department of Neurobiology and Behavior, Cornell University , Ithaca, New York
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12
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Israely S, Leisman G, Carmeli E. Neuromuscular synergies in motor control in normal and poststroke individuals. Rev Neurosci 2018; 29:593-612. [PMID: 29397390 DOI: 10.1515/revneuro-2017-0058] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2017] [Accepted: 11/26/2017] [Indexed: 01/03/2023]
Abstract
Muscle synergies are proposed to function as motor primitives that are modulated by frontal brain areas to construct a large repertoire of movement. This paper reviews the history of the development of our current theoretical understanding of nervous system-based motor control mechanisms and more specifically the concept of muscle synergies. Computational models of muscle synergies, especially the nonnegative matrix factorization algorithm, are discussed with specific reference to the changes in synergy control post-central nervous system (CNS) lesions. An alternative approach for motor control is suggested, exploiting a combination of synergies control or flexible muscle control used for gross motor skills and for individualized finger movements. Rehabilitation approaches, either supporting or inhibiting the use of basic movement patterns, are discussed in the context of muscle synergies. Applications are discussed for the use of advanced technologies that can promote the recovery and functioning of the human CNS after stroke.
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Affiliation(s)
- Sharon Israely
- Department of Physical Therapy, University of Haifa, Haifa 3498838, Israel
| | - Gerry Leisman
- Department of Physical Therapy, University of Haifa, Haifa 3498838, Israel.,National Institute for Brain and Rehabilitation Sciences-Israel, Nazareth 16470, Israel
| | - Eli Carmeli
- Department of Physical Therapy, University of Haifa, Haifa 3498838, Israel
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13
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Boccia G, Zoppirolli C, Bortolan L, Schena F, Pellegrini B. Shared and task-specific muscle synergies of Nordic walking and conventional walking. Scand J Med Sci Sports 2017; 28:905-918. [PMID: 29027265 DOI: 10.1111/sms.12992] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/05/2017] [Indexed: 01/08/2023]
Abstract
Nordic walking is a form of walking that includes a poling action, and therefore an additional subtask, with respect to conventional walking. The aim of this study was to assess whether Nordic walking required a task-specific muscle coordination with respect to conventional walking. We compared the electromyographic (EMG) activity of 15 upper- and lower-limb muscles of 9 Nordic walking instructors, while executing Nordic walking and conventional walking at 1.3 ms-1 on a treadmill. Non-negative matrix factorization method was applied to identify muscle synergies, representing the spatial and temporal organization of muscle coordination. The number of muscle synergies was not different between Nordic walking (5.2 ± 0.4) and conventional walking (5.0 ± 0.7, P = .423). Five muscle synergies accounted for 91.2 ± 1.1% and 92.9 ± 1.2% of total EMG variance in Nordic walking and conventional walking, respectively. Similarity and cross-reconstruction analyses showed that 4 muscle synergies, mainly involving lower-limb and trunk muscles, are shared between Nordic walking and conventional walking. One synergy acting during upper limb propulsion is specific to Nordic walking, modifying the spatial organization and the magnitude of activation of upper limb muscles compared to conventional walking. The inclusion of the poling action in Nordic walking does not increase the complexity of movement control and does not change the coordination of lower limb muscles. This makes Nordic walking a physical activity suitable also for people with low motor skill.
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Affiliation(s)
- G Boccia
- CeRiSM Research Centre for Sport, Mountain, and Health, University of Verona, Rovereto, Trento, Italy.,NeuroMuscularFunction Research Group, Department of Medical Sciences, School of Exercise and Sport Sciences, University of Turin, Torino, Italy
| | - C Zoppirolli
- CeRiSM Research Centre for Sport, Mountain, and Health, University of Verona, Rovereto, Trento, Italy.,Department of Neuroscience, Biomedicine and Movement Science, University of Verona, Verona, Italy
| | - L Bortolan
- CeRiSM Research Centre for Sport, Mountain, and Health, University of Verona, Rovereto, Trento, Italy.,Department of Neuroscience, Biomedicine and Movement Science, University of Verona, Verona, Italy
| | - F Schena
- CeRiSM Research Centre for Sport, Mountain, and Health, University of Verona, Rovereto, Trento, Italy.,Department of Neuroscience, Biomedicine and Movement Science, University of Verona, Verona, Italy
| | - B Pellegrini
- CeRiSM Research Centre for Sport, Mountain, and Health, University of Verona, Rovereto, Trento, Italy.,Department of Neuroscience, Biomedicine and Movement Science, University of Verona, Verona, Italy
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14
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Avraham G, Mawase F, Karniel A, Shmuelof L, Donchin O, Mussa-Ivaldi FA, Nisky I. Representing delayed force feedback as a combination of current and delayed states. J Neurophysiol 2017; 118:2110-2131. [PMID: 28724784 DOI: 10.1152/jn.00347.2017] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2017] [Revised: 07/10/2017] [Accepted: 07/16/2017] [Indexed: 11/22/2022] Open
Abstract
To adapt to deterministic force perturbations that depend on the current state of the hand, internal representations are formed to capture the relationships between forces experienced and motion. However, information from multiple modalities travels at different rates, resulting in intermodal delays that require compensation for these internal representations to develop. To understand how these delays are represented by the brain, we presented participants with delayed velocity-dependent force fields, i.e., forces that depend on hand velocity either 70 or 100 ms beforehand. We probed the internal representation of these delayed forces by examining the forces the participants applied to cope with the perturbations. The findings showed that for both delayed forces, the best model of internal representation consisted of a delayed velocity and current position and velocity. We show that participants relied initially on the current state, but with adaptation, the contribution of the delayed representation to adaptation increased. After adaptation, when the participants were asked to make movements with a higher velocity for which they had not previously experienced with the delayed force field, they applied forces that were consistent with current position and velocity as well as delayed velocity representations. This suggests that the sensorimotor system represents delayed force feedback using current and delayed state information and that it uses this representation when generalizing to faster movements.NEW & NOTEWORTHY The brain compensates for forces in the body and the environment to control movements, but it is unclear how it does so given the inherent delays in information transmission and processing. We examined how participants cope with delayed forces that depend on their arm velocity 70 or 100 ms beforehand. After adaptation, participants applied opposing forces that revealed a partially correct representation of the perturbation using the current and the delayed information.
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Affiliation(s)
- Guy Avraham
- Department of Biomedical Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel; .,Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Firas Mawase
- Department of Physical Medicine and Rehabilitation, Johns Hopkins School of Medicine, Baltimore, Maryland
| | - Amir Karniel
- Department of Biomedical Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel.,Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Lior Shmuelof
- Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva, Israel.,Department of Brain and Cognitive Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Opher Donchin
- Department of Biomedical Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel.,Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Ferdinando A Mussa-Ivaldi
- Northwestern University and Rehabilitation Institute of Chicago, Chicago, Illinois.,Department of Biomedical Engineering, Northwestern University, Evanston, Illinois; and.,Sensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, Illinois
| | - Ilana Nisky
- Department of Biomedical Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel.,Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Beer-Sheva, Israel
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15
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Hirai H, Miyazaki F, Naritomi H, Koba K, Oku T, Uno K, Uemura M, Nishi T, Kageyama M, Krebs HI. On the Origin of Muscle Synergies: Invariant Balance in the Co-activation of Agonist and Antagonist Muscle Pairs. Front Bioeng Biotechnol 2015; 3:192. [PMID: 26636079 PMCID: PMC4656836 DOI: 10.3389/fbioe.2015.00192] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2015] [Accepted: 11/06/2015] [Indexed: 12/05/2022] Open
Abstract
Investigation of neural representation of movement planning has attracted the attention of neuroscientists, as it may reveal the sensorimotor transformation essential to motor control. The analysis of muscle synergies based on the activity of agonist–antagonist (AA) muscle pairs may provide insight into such transformations, especially for a reference frame in the muscle space. In this study, we examined the AA concept using the following explanatory variables: the AA ratio, which is related to the equilibrium-joint angle, and the AA sum, which is associated with joint stiffness. We formulated muscle synergies as a function of AA sums, positing that muscle synergies are composite units of mechanical impedance. The AA concept can be regarded as another form of the equilibrium-point (EP) hypothesis, and it can be extended to the concept of EP-based synergies. We introduce, here, a novel tool for analyzing the neurological and motor functions underlying human movements and review some initial insights from our results about the relationships between muscle synergies, endpoint stiffness, and virtual trajectories (time series of EP). Our results suggest that (1) muscle synergies reflect an invariant balance in the co-activation of AA muscle pairs; (2) each synergy represents the basis for the radial, tangential, and null movements of the virtual trajectory in the polar coordinates centered on the specific joint at the base of the body; and (3) the alteration of muscle synergies (for example, due to spasticity or rigidity following neurological injury) results in significant distortion of endpoint stiffness and concomitant virtual trajectories. These results indicate that muscle synergies (i.e., the balance of muscle mechanical impedance) are essential for motor control.
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Affiliation(s)
- Hiroaki Hirai
- Department of Mechanical Science and Bioengineering, Graduate School of Engineering Science, Osaka University , Toyonaka , Japan
| | - Fumio Miyazaki
- Department of Mechanical Science and Bioengineering, Graduate School of Engineering Science, Osaka University , Toyonaka , Japan
| | | | - Keitaro Koba
- Department of Mechanical Science and Bioengineering, Graduate School of Engineering Science, Osaka University , Toyonaka , Japan
| | - Takanori Oku
- Department of Mechanical Science and Bioengineering, Graduate School of Engineering Science, Osaka University , Toyonaka , Japan
| | - Kanna Uno
- Department of Mechanical Science and Bioengineering, Graduate School of Engineering Science, Osaka University , Toyonaka , Japan
| | - Mitsunori Uemura
- Department of Mechanical Science and Bioengineering, Graduate School of Engineering Science, Osaka University , Toyonaka , Japan
| | - Tomoki Nishi
- Department of Rehabilitation, Senri Chuo Hospital , Toyonaka , Japan
| | - Masayuki Kageyama
- Department of Rehabilitation, Senri Chuo Hospital , Toyonaka , Japan
| | - Hermano Igo Krebs
- Department of Mechanical Science and Bioengineering, Graduate School of Engineering Science, Osaka University , Toyonaka , Japan ; Department of Mechanical Engineering, Massachusetts Institute of Technology , Cambridge, MA , USA ; Department of Neurology, University of Maryland School of Medicine , Baltimore, MD , USA ; Department of Rehabilitation Medicine I, School of Medicine, Fujita Health University , Toyoake , Japan ; Institute of Neuroscience, University of Newcastle , Newcastle upon Tyne , UK
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16
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d'Avella A, Giese M, Ivanenko YP, Schack T, Flash T. Editorial: Modularity in motor control: from muscle synergies to cognitive action representation. Front Comput Neurosci 2015; 9:126. [PMID: 26500533 PMCID: PMC4598477 DOI: 10.3389/fncom.2015.00126] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2015] [Accepted: 09/22/2015] [Indexed: 12/24/2022] Open
Affiliation(s)
- Andrea d'Avella
- Department of Biomedical Sciences and Morphological and Functional Images, University of Messina Messina, Italy ; Laboratory of Neuromotor Physiology, Santa Lucia Foundation Rome, Italy
| | - Martin Giese
- Section for Computational Sensomotorics, Department of Cognitive Neurology, Hertie Institute for Clinical Brain Research and Center for Integrative Neuroscience, University Clinic Tuebingen Tuebingen, Germany
| | - Yuri P Ivanenko
- Laboratory of Neuromotor Physiology, Santa Lucia Foundation Rome, Italy
| | - Thomas Schack
- Research Group Neurocognition and Action-Biomechanics and Cognitive Interaction Technology-Center of Excellence, Bielefeld University Bielefeld, Germany
| | - Tamar Flash
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science Rehovot, Israel
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17
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Abstract
A wide range of blind source separation methods have been used in motor control research for the extraction of movement primitives from EMG and kinematic data. Popular examples are principal component analysis (PCA), independent component analysis (ICA), anechoic demixing, and the time-varying synergy model (d'Avella and Tresch, 2002). However, choosing the parameters of these models, or indeed choosing the type of model, is often done in a heuristic fashion, driven by result expectations as much as by the data. We propose an objective criterion which allows to select the model type, number of primitives and the temporal smoothness prior. Our approach is based on a Laplace approximation to the posterior distribution of the parameters of a given blind source separation model, re-formulated as a Bayesian generative model. We first validate our criterion on ground truth data, showing that it performs at least as good as traditional model selection criteria [Bayesian information criterion, BIC (Schwarz, 1978) and the Akaike Information Criterion (AIC) (Akaike, 1974)]. Then, we analyze human gait data, finding that an anechoic mixture model with a temporal smoothness constraint on the sources can best account for the data.
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Affiliation(s)
- Dominik M Endres
- Section Computational Sensomotorics, Department of Cognitive Neurology, CIN, HIH, BCCN, University Clinic Tübingen Tübingen, Germany
| | - Enrico Chiovetto
- Section Computational Sensomotorics, Department of Cognitive Neurology, CIN, HIH, BCCN, University Clinic Tübingen Tübingen, Germany
| | - Martin A Giese
- Section Computational Sensomotorics, Department of Cognitive Neurology, CIN, HIH, BCCN, University Clinic Tübingen Tübingen, Germany
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18
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Abstract
Walking, catching a ball and reaching are all tasks in which humans and animals exhibit advanced motor skills. Findings in biological research concerning motor control suggest a modular control hierarchy which combines movement/motor primitives into complex and natural movements. Engineers inspire their research on these findings in the quest for adaptive and skillful control for robots. In this work we propose a modular architecture with control primitives (MACOP) which uses a set of controllers, where each controller becomes specialized in a subregion of its joint and task-space. Instead of having a single controller being used in this subregion [such as MOSAIC (modular selection and identification for control) on which MACOP is inspired], MACOP relates more to the idea of continuously mixing a limited set of primitive controllers. By enforcing a set of desired properties on the mixing mechanism, a mixture of primitives emerges unsupervised which successfully solves the control task. We evaluate MACOP on a numerical model of a robot arm by training it to generate desired trajectories. We investigate how the tracking performance is affected by the number of controllers in MACOP and examine how the individual controllers and their generated control primitives contribute to solving the task. Furthermore, we show how MACOP compensates for the dynamic effects caused by a fixed control rate and the inertia of the robot.
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Affiliation(s)
- Tim Waegeman
- Department of Electronics and Information Systems, Ghent University Ghent, Belgium
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19
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Endres D, Meirovitch Y, Flash T, Giese MA. Segmenting sign language into motor primitives with Bayesian binning. Front Comput Neurosci 2013; 7:68. [PMID: 23750135 PMCID: PMC3664315 DOI: 10.3389/fncom.2013.00068] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2013] [Accepted: 05/08/2013] [Indexed: 11/16/2022] Open
Abstract
The endpoint trajectories of human movements fulfill characteristic power laws linking velocity and curvature. The parameters of these power laws typically vary between different segments of longer action sequences. These parameters might thus be exploited for the unsupervised segmentation of actions into movement primitives. For the example of sign language we investigate whether such segments can be identified by Bayesian binning (BB), using a Gaussian observation model whose mean has a polynomial time dependence. We show that this method yields good segmentation and correctly models ground truth kinematics composed of consecutive segments derived from wrist trajectories recorded from users of Israeli Sign Language (ISL). Importantly, polynomial orders between 3 and 5 yield an optimal trade-off between complexity and accuracy of the trajectory approximation, in accordance with the minimum acceleration and minimum jerk models. Comparing the orders of the polynomials best approximating natural kinematics against those needed to fit the power law ground truth data suggests that kinematic properties not compatible with power laws are also not adequately represented by low order polynomials and require higher order polynomials for a good approximation.
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Affiliation(s)
- Dominik Endres
- Department of Cognitive Neurology, Section Computational Sensomotorics, CIN, HIH and University Clinic TübingenTübingen, Germany
| | - Yaron Meirovitch
- Department of Applied Mathematics and Computer Science, The Weizmann Institute of ScienceRehovot, Israel
| | - Tamar Flash
- Department of Applied Mathematics and Computer Science, The Weizmann Institute of ScienceRehovot, Israel
| | - Martin A. Giese
- Department of Cognitive Neurology, Section Computational Sensomotorics, CIN, HIH and University Clinic TübingenTübingen, Germany
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20
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Abstract
A key idea in motor learning is that internal models of environmental dynamics are internally represented as functions of spatial variables including position, velocity, and acceleration of body motion. We refer to such a representation as motion dependent. The evidence for a motion-dependent representation is, however, primarily based on examination of the adaptation to motion-dependent dynamic environments. To more rigorously test this idea, we examined the adaptive response to perturbations that cannot be well approximated by motion-state: force-impulses--brief, high-amplitude pulses of force. The induced adaptation characterizes the impulse response of the system--a widely used technique for probing system dynamics in engineering systems identification. Here we examined the adaptive responses to two different force-impulse perturbations during human voluntary reaching movements. We found that although neither could be well approximated by motion-state (R(2) < 0.18 in both cases), both perturbations induced single-trial adaptive responses that were (R(2) > 0.87). Moreover, these responses were similar in shape to those induced by low-fidelity motion-based approximations of the force-impulses (r > 0.88). Remarkably, we found that the motion dependence of the adaptive responses to force-impulses persisted, even after prolonged exposure (R(2) > 0.95). During a 300-trial training period, trial-to-trial fluctuations in the position, velocity, and acceleration of motion accurately predicted trial-to-trial fluctuations in the adaptive response, and the adaptation gradually became more specific to the perturbation, but only via reorganization of the structure of the motion-dependent representation. These results indicate that internal models of environmental dynamics represent these dynamics in a motion-dependent manner, regardless of the nature of the dynamics encountered.
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Affiliation(s)
- Gary C Sing
- Center for Brain Science, Harvard School of Engineering and Applied Sciences, Cambridge, Massachusetts 02138, USA
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21
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Abstract
The purpose of the present study was to determine whether subjects who have learned a complex motor skill exhibit similar neuromuscular control strategies. We studied a population of experienced gymnasts during backward giant swings on the high bar. This cyclic movement is interesting because it requires learning, as untrained subjects are unable to perform this task. Nine gymnasts were tested. Both kinematics and electromyographic (EMG) patterns of 12 upper-limb and trunk muscles were recorded. Muscle synergies were extracted by non-negative matrix factorization (NMF), providing two components: muscle synergy vectors and synergy activation coefficients. First, the coefficient of correlation (r) and circular cross-correlation (r(max)) were calculated to assess similarities in the mechanical patterns, EMG patterns, and muscle synergies between gymnasts. We performed a further analysis to verify that the muscle synergies (in terms of muscle synergy vectors or synergy activation coefficients) extracted for one gymnast accounted for the EMG patterns of the other gymnasts. Three muscle synergies explained 89.9 ± 2.0% of the variance accounted for (VAF). The coefficients of correlation of the muscle synergy vectors among the participants were 0.83 ± 0.08, 0.86 ± 0.09, and 0.66 ± 0.28 for synergy #1, #2, and #3, respectively. By keeping the muscle synergy vectors constant, we obtained an averaged VAF across all pairwise comparisons of 79 ± 4%. For the synergy activation coefficients, r(max)-values were 0.96 ± 0.03, 0.92 ± 0.03, and 0.95 ± 0.03, for synergy #1, #2, and #3, respectively. By keeping the synergy activation coefficients constant, we obtained an averaged VAF across all pairwise comparisons of 72 ± 5%. Although variability was found (especially for synergy #3), the gymnasts exhibited gross similar neuromuscular strategies when performing backward giant swings. This confirms that the muscle synergies are consistent across participants, even during a skilled motor task that requires learning.
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Affiliation(s)
- Julien Frère
- Laboratory « Motricité, Interactions, Performance », University of Maine Le Mans, France
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22
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Roh J, Rymer WZ, Beer RF. Robustness of muscle synergies underlying three-dimensional force generation at the hand in healthy humans. J Neurophysiol 2012; 107:2123-42. [PMID: 22279190 PMCID: PMC3331600 DOI: 10.1152/jn.00173.2011] [Citation(s) in RCA: 95] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2011] [Accepted: 01/19/2012] [Indexed: 12/21/2022] Open
Abstract
Previous studies using advanced matrix factorization techniques have shown that the coordination of human voluntary limb movements may be accomplished using combinations of a small number of intermuscular coordination patterns, or muscle synergies. However, the potential use of muscle synergies for isometric force generation has been evaluated mostly using correlational methods. The results of such studies suggest that fixed relationships between the activations of pairs of muscles are relatively rare. There is also emerging evidence that the nervous system uses independent strategies to control movement and force generation, which suggests that one cannot conclude a priori that isometric force generation is accomplished by combining muscle synergies, as shown in movement control. In this study, we used non-negative matrix factorization to evaluate the ability of a few muscle synergies to reconstruct the activation patterns of human arm muscles underlying the generation of three-dimensional (3-D) isometric forces at the hand. Surface electromyographic (EMG) data were recorded from eight key elbow and shoulder muscles during 3-D force target-matching protocols performed across a range of load levels and hand positions. Four synergies were sufficient to explain, on average, 95% of the variance in EMG datasets. Furthermore, we found that muscle synergy composition was conserved across biomechanical task conditions, experimental protocols, and subjects. Our findings are consistent with the view that the nervous system can generate isometric forces by assembling a combination of a small number of muscle synergies, differentially weighted according to task constraints.
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Affiliation(s)
- Jinsook Roh
- Sensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, IL, USA.
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23
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Abstract
Previous studies using intact and spinalized animals have suggested that coordinated movements can be generated by appropriate combinations of muscle synergies controlled by the central nervous system (CNS). However, which CNS regions are responsible for expressing muscle synergies remains an open question. We address whether the brain stem and spinal cord are involved in expressing muscle synergies used for executing a range of natural movements. We analyzed the electromyographic (EMG) data recorded from frog leg muscles before and after transection at different levels of the neuraxis-rostral midbrain (brain stem preparations), rostral medulla (medullary preparations), and the spinal-medullary junction (spinal preparations). Brain stem frogs could jump, swim, kick, and step, while medullary frogs could perform only a partial repertoire of movements. In spinal frogs, cutaneous reflexes could be elicited. Systematic EMG analysis found two different synergy types: 1) synergies shared between pre- and posttransection states and 2) synergies specific to individual states. Almost all synergies found in natural movements persisted after transection at rostral midbrain or medulla but not at the spinal-medullary junction for swim and step. Some pretransection- and posttransection-specific synergies for a certain behavior appeared as shared synergies for other motor behaviors of the same animal. These results suggest that the medulla and spinal cord are sufficient for the expression of most muscle synergies in frog behaviors. Overall, this study provides further evidence supporting the idea that motor behaviors may be constructed by muscle synergies organized within the brain stem and spinal cord and activated by descending commands from supraspinal areas.
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Affiliation(s)
- Jinsook Roh
- McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
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24
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Abstract
The purpose of the present experiment is to further understand the effect of levels of processing (top-down vs. bottom-up) on the perception of movement kinematics and primitives for grasping actions in order to gain insight into possible primitives used by the mirror system. In the present study, we investigated the potential of identifying such primitives using an action segmentation task. Specifically, we investigated whether or not segmentation was driven primarily by the kinematics of the action, as opposed to high-level top-down information about the action and the object used in the action. Participants in the experiment were shown 12 point-light movies of object-centered hand/arm actions that were either presented in their canonical orientation together with the object in question (top-down condition) or upside down (inverted) without information about the object (bottom-up condition). The results show that (1) despite impaired high-level action recognition for the inverted actions participants were able to reliably segment the actions according to lower-level kinematic variables, (2) segmentation behavior in both groups was significantly related to the kinematic variables of change in direction, velocity, and acceleration of the wrist (thumb and finger tips) for most of the included actions. This indicates that top-down activation of an action representation leads to similar segmentation behavior for hand/arm actions compared to bottom-up, or local, visual processing when performing a fairly unconstrained segmentation task. Motor primitives as parts of more complex actions may therefore be reliably derived through visual segmentation based on movement kinematics.
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Affiliation(s)
- Paul E Hemeren
- School of Humanities and Informatics, University of Skövde Skövde, Sweden
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25
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Ivanenko YP, Cappellini G, Dominici N, Poppele RE, Lacquaniti F. Coordination of locomotion with voluntary movements in humans. J Neurosci 2005; 25:7238-53. [PMID: 16079406 PMCID: PMC6725226 DOI: 10.1523/jneurosci.1327-05.2005] [Citation(s) in RCA: 276] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2005] [Revised: 06/16/2005] [Accepted: 06/17/2005] [Indexed: 11/21/2022] Open
Abstract
Muscle activity occurring during human locomotion can be accounted for by five basic temporal activation patterns in a variety of locomotion conditions. Here, we examined how these activation patterns interact with muscle activity required for a voluntary movement. Subjects produced a voluntary movement during locomotion, and we examined the resulting kinematics, kinetics, and EMG activity in 16-31 ipsilateral limb and trunk muscles during the tasks. There were four voluntary tasks added to overground walking (approximately 5 km/h) in which subjects kicked a ball, stepped over an obstacle, or reached down and grasped an object on the floor (weight support on either the right or the left foot). Statistical analyses of EMG waveforms showed that the five basic locomotion patterns were invariantly present in each task, although they could be differently weighted across muscles, suggesting a characteristic locomotion timing of muscle activations. We also observed a separate activation that was timed to the voluntary task. The coordination of locomotion with the voluntary task was accomplished by combining activation timings that were associated separately with the voluntary task and locomotion. Activation associated with the voluntary tasks was either synchronous with the timing for locomotion or had additional activations not represented in the basic locomotion timing. We propose that this superposition of an invariant locomotion timing pattern with a voluntary activation timing may be consistent with the proposal suggesting that compound movements are produced through a superposition of motor programs.
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Affiliation(s)
- Yuri P Ivanenko
- Department of Neuromotor Physiology, Scientific Institute Foundation Santa Lucia, 00179 Rome, Italy.
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