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Zheng X, Han Y, Liang J. Anthropomorphic motion planning for multi-degree-of-freedom arms. Front Bioeng Biotechnol 2024; 12:1388609. [PMID: 38863490 PMCID: PMC11165200 DOI: 10.3389/fbioe.2024.1388609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Accepted: 05/13/2024] [Indexed: 06/13/2024] Open
Abstract
With the development of technology, the humanoid robot is no longer a concept, but a practical partner with the potential to assist people in industry, healthcare and other daily scenarios. The basis for the success of humanoid robots is not only their appearance, but more importantly their anthropomorphic behaviors, which is crucial for the human-robot interaction. Conventionally, robots are designed to follow meticulously calculated and planned trajectories, which typically rely on predefined algorithms and models, resulting in the inadaptability to unknown environments. Especially when faced with the increasing demand for personalized and customized services, predefined motion planning cannot be adapted in time to adapt to personal behavior. To solve this problem, anthropomorphic motion planning has become the focus of recent research with advances in biomechanics, neurophysiology, and exercise physiology which deepened the understanding of the body for generating and controlling movement. However, there is still no consensus on the criteria by which anthropomorphic motion is accurately generated and how to generate anthropomorphic motion. Although there are articles that provide an overview of anthropomorphic motion planning such as sampling-based, optimization-based, mimicry-based, and other methods, these methods differ only in the nature of the planning algorithms and have not yet been systematically discussed in terms of the basis for extracting upper limb motion characteristics. To better address the problem of anthropomorphic motion planning, the key milestones and most recent literature have been collated and summarized, and three crucial topics are proposed to achieve anthropomorphic motion, which are motion redundancy, motion variation, and motion coordination. The three characteristics are interrelated and interdependent, posing the challenge for anthropomorphic motion planning system. To provide some insights for the research on anthropomorphic motion planning, and improve the anthropomorphic motion ability, this article proposes a new taxonomy based on physiology, and a more complete system of anthropomorphic motion planning by providing a detailed overview of the existing methods and their contributions.
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Affiliation(s)
- Xiongfei Zheng
- State Key Laboratory of Intelligent Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China
| | - Yunyun Han
- Department of Neurobiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiejunyi Liang
- State Key Laboratory of Intelligent Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China
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2
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Langlois ET, Bennequin D, de Marco G. Role of the Cerebellum in the Construction of Functional and Geometrical Spaces. CEREBELLUM (LONDON, ENGLAND) 2024:10.1007/s12311-024-01693-y. [PMID: 38625534 DOI: 10.1007/s12311-024-01693-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 04/10/2024] [Indexed: 04/17/2024]
Abstract
The perceptual and motor systems appear to have a set of movement primitives that exhibit certain geometric and kinematic invariances. Complex patterns and mental representations can be produced by (re)combining some simple motor elements in various ways using basic operations, transformations, and respecting a set of laws referred to as kinematic laws of motion. For example, point-to-point hand movements are characterized by straight hand paths with single-peaked-bell-shaped velocity profiles, whereas hand speed profiles for curved trajectories are often irregular and more variable, with speed valleys and inflections extrema occurring at the peak curvature. Curvature and speed are generically related by the 2/3 power law. Mathematically, such laws can be deduced from a combination of Euclidean, affine, and equi-affine geometries, whose neural correlates have been partially detected in various brain areas including the cerebellum and the basal ganglia. The cerebellum has been found to play an important role in the control of coordination, balance, posture, and timing over the past years. It is also assumed that the cerebellum computes forward internal models in relationship with specific cortical and subcortical brain regions but its motor relationship with the perceptual space is unclear. A renewed interest in the geometrical and spatial role of the cerebellum may enable a better understanding of its specific contribution to the action-perception loop and behavior's adaptation. In this sense, we complete this overview with an innovative theoretical framework that describes a possible implementation and selection by the cerebellum of geometries adhering to different mathematical laws.
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Affiliation(s)
- Eya Torkhani Langlois
- LINP2, UPL, Université Paris Nanterre, 200 avenue de la République, Nanterre, 92000, France
| | - Daniel Bennequin
- Equipe Géométrie et Dynamique, Paris-Cité, UFR de Mathématiques, Bâtiment Sophie Germain, 8 place Aurélie Nemours, Paris, 75013, France
| | - Giovanni de Marco
- LINP2, UPL, Université Paris Nanterre, 200 avenue de la République, Nanterre, 92000, France.
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3
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Stepniewska I, Kaas JH. The dorsal stream of visual processing and action-specific domains in parietal and frontal cortex in primates. J Comp Neurol 2023; 531:1897-1908. [PMID: 37118872 PMCID: PMC10611900 DOI: 10.1002/cne.25489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 03/24/2023] [Accepted: 03/31/2023] [Indexed: 04/30/2023]
Abstract
This review summarizes our findings obtained from over 15 years of research on parietal-frontal networks involved in the dorsal stream of cortical processing. We have presented considerable evidence for the existence of similar, partially independent, parietal-frontal networks involved in specific motor actions in a number of primates. These networks are formed by connections between action-specific domains representing the same complex movement evoked by electrical microstimulation. Functionally matched domains in the posterior parietal (PPC) and frontal (M1-PMC) motor regions are hierarchically related. M1 seems to be a critical link in these networks, since the outputs of M1 are essential to the evoked behavior, whereas PPC and PMC mediate complex movements mostly via their connections with M1. Thus, lesioning or deactivating M1 domains selectively blocks matching PMC and PPC domains, while having limited impact on other domains. When pairs of domains are stimulated together, domains within the same parietal-frontal network (matching domains) are cooperative in evoking movements, while they are mainly competitive with other domains (mismatched domains) within the same set of cortical areas. We propose that the interaction of different functional domains in each cortical region (as well as in striatum) occurs mainly via mutual suppression. Thus, the domains at each level are in competition with each other for mediating one of several possible behavioral outcomes.
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Affiliation(s)
- Iwona Stepniewska
- Department of Psychology, Vanderbilt University, Nashville, TN 37240
| | - Jon H. Kaas
- Department of Psychology, Vanderbilt University, Nashville, TN 37240
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Shaffer C, Barrett LF, Quigley KS. Signal processing in the vagus nerve: Hypotheses based on new genetic and anatomical evidence. Biol Psychol 2023; 182:108626. [PMID: 37419401 PMCID: PMC10563766 DOI: 10.1016/j.biopsycho.2023.108626] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 06/25/2023] [Accepted: 07/03/2023] [Indexed: 07/09/2023]
Abstract
Each organism must regulate its internal state in a metabolically efficient way as it interacts in space and time with an ever-changing and only partly predictable world. Success in this endeavor is largely determined by the ongoing communication between brain and body, and the vagus nerve is a crucial structure in that dialogue. In this review, we introduce the novel hypothesis that the afferent vagus nerve is engaged in signal processing rather than just signal relay. New genetic and structural evidence of vagal afferent fiber anatomy motivates two hypotheses: (1) that sensory signals informing on the physiological state of the body compute both spatial and temporal viscerosensory features as they ascend the vagus nerve, following patterns found in other sensory architectures, such as the visual and olfactory systems; and (2) that ascending and descending signals modulate one another, calling into question the strict segregation of sensory and motor signals, respectively. Finally, we discuss several implications of our two hypotheses for understanding the role of viscerosensory signal processing in predictive energy regulation (i.e., allostasis) as well as the role of metabolic signals in memory and in disorders of prediction (e.g., mood disorders).
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Affiliation(s)
- Clare Shaffer
- Department of Psychology, College of Science, Northeastern University, Boston, MA, USA.
| | - Lisa Feldman Barrett
- Department of Psychology, College of Science, Northeastern University, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Karen S Quigley
- Department of Psychology, College of Science, Northeastern University, Boston, MA, USA.
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Flash T, Zullo L. Biomechanics, motor control and dynamic models of the soft limbs of the octopus and other cephalopods. J Exp Biol 2023; 226:307147. [PMID: 37083140 DOI: 10.1242/jeb.245295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/22/2023]
Abstract
Muscular hydrostats are organs composed entirely of packed arrays of incompressible muscles and lacking any skeletal support. Found in both vertebrates and invertebrates, they are of great interest for comparative biomechanics from engineering and evolutionary perspectives. The arms of cephalopods (e.g. octopus and squid) are particularly interesting muscular hydrostats because of their flexibility and ability to generate complex behaviors exploiting elaborate nervous systems. Several lines of evidence from octopus studies point to the use of both brain and arm-embedded motor control strategies that have evolved to simplify the complexities associated with the control of flexible and hyper-redundant limbs and bodies. Here, we review earlier and more recent experimental studies on octopus arm biomechanics and neural motor control. We review several dynamic models used to predict the kinematic characteristics of several basic motion primitives, noting the shortcomings of the current models in accounting for behavioral observations. We also discuss the significance of impedance (stiffness and viscosity) in controlling the octopus's motor behavior. These factors are considered in light of several new models of muscle biomechanics that could be used in future research to gain a better understanding of motor control in the octopus. There is also a need for updated models that encompass stiffness and viscosity for designing and controlling soft robotic arms. The field of soft robotics has boomed over the past 15 years and would benefit significantly from further progress in biomechanical and motor control studies on octopus and other muscular hydrostats.
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Affiliation(s)
- Tamar Flash
- Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Letizia Zullo
- Bioinspired Soft Robotics & Center for Synaptic Neuroscience and Technology (NSYN), Istituto Italiano di Tecnologia, Largo Rosanna Benzi 10, 16132 Genova, Italy
- IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi 10, 16132 Genova, Italy
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Golomb D, Moore JD, Fassihi A, Takatoh J, Prevosto V, Wang F, Kleinfeld D. Theory of hierarchically organized neuronal oscillator dynamics that mediate rodent rhythmic whisking. Neuron 2022; 110:3833-3851.e22. [PMID: 36113472 PMCID: PMC10248719 DOI: 10.1016/j.neuron.2022.08.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 07/06/2022] [Accepted: 08/17/2022] [Indexed: 12/15/2022]
Abstract
Rodents explore their environment through coordinated orofacial motor actions, including whisking. Whisking can free-run via an oscillator of inhibitory neurons in the medulla and can be paced by breathing. Yet, the mechanics of the whisking oscillator and its interaction with breathing remain to be understood. We formulate and solve a hierarchical model of the whisking circuit. The first whisk within a breathing cycle is generated by inhalation, which resets a vibrissa oscillator circuit, while subsequent whisks are derived from the oscillator circuit. Our model posits, consistent with experiment, that there are two subpopulations of oscillator neurons. Stronger connections between the subpopulations support rhythmicity, while connections within each subpopulation induce variable spike timing that enhances the dynamic range of rhythm generation. Calculated cycle-to-cycle changes in whisking are consistent with experiment. Our model provides a computational framework to support longstanding observations of concurrent autonomous and driven rhythmic motor actions that comprise behaviors.
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Affiliation(s)
- David Golomb
- Department of Physiology and Cell Biology, Ben Gurion University, Be'er-Sheva 8410501, Israel; Department of Physics, Ben Gurion University, Be'er-Sheva 8410501, Israel; Zlotowski Center for Neuroscience, Ben Gurion University, Be'er-Sheva 8410501, Israel.
| | - Jeffrey D Moore
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA
| | - Arash Fassihi
- Department of Physics, University of California at San Diego, La Jolla, CA 92093, USA
| | - Jun Takatoh
- Department of Brain and Cognitive Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Vincent Prevosto
- Department of Brain and Cognitive Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Fan Wang
- Department of Brain and Cognitive Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; McGovern Institute, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - David Kleinfeld
- Department of Physics, University of California at San Diego, La Jolla, CA 92093, USA; Department of Neurobiology, University of California at San Diego, La Jolla, CA 92093, USA.
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Leh A, Langhanns C, Zhao F, Gaschler R, Müller H. Muscle activity in explicit and implicit sequence learning: Exploring additional measures of learning and certainty via tensor decomposition. Acta Psychol (Amst) 2022; 226:103587. [PMID: 35447430 DOI: 10.1016/j.actpsy.2022.103587] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 03/09/2022] [Accepted: 04/06/2022] [Indexed: 11/24/2022] Open
Abstract
Sequence learning in serial reaction time tasks (SRTTs) is usually inferred through the reaction time measured by a keyboard. However, this chronometric parameter offers no information beyond the time point of the button-press. We therefore examined whether sequence learning can be measured by muscle activations via electromyography (EMG) in a dual-task paradigm. The primary task was a SRTT, in which the stimuli followed a fixed sequence in some blocks, whereas the sequence was random in the control condition. The secondary task stimulus was always random. One group was informed about the fixed sequence, and the other not. We assessed three dependent variables. The chronometric parameter premotor time represents the duration between stimulus onset and the onset of EMG activity, which indicates the start of the response. The other variables describe the response itself considering the EMG activity after response start. The EMG integral was analyzed, and additionally, tensor decomposition was implemented to assess sequence dependent changes in the contribution of the obtained subcomponents. The results show explicit sequence learning in this dual-task setting. Specifically, the informed group show shorter premotor times in fixed than random sequences as well as larger EMG integral and tensor contributions. Further, increased activity seems to represent response certainty, since a decrease is found for both groups in trials following erroneous responses. Interestingly, the sensitivity to sequence and post-error effects varies between the subcomponents. The results indicate that muscle activity can be a useful indicator of response behavior in addition to chronometric parameters.
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8
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Abstract
To control unmanned aerial systems, we rarely have a perfect system model. Safe and aggressive planning is also challenging for nonlinear and under-actuated systems. Expert pilots, however, demonstrate maneuvers that are deemed at the edge of plane envelope. Inspired by biological systems, in this paper, we introduce a framework that leverages methods in the field of control theory and reinforcement learning to generate feasible, possibly aggressive, trajectories. For the control policies, Dynamic Movement Primitives (DMPs) imitate pilot-induced primitives, and DMPs are combined in parallel to generate trajectories to reach original or different goal points. The stability properties of DMPs and their overall systems are analyzed using contraction theory. For reinforcement learning, Policy Improvement with Path Integrals (PI2) was used for the maneuvers. The results in this paper show that PI2 updated policies are a feasible and parallel combination of different updated primitives transfer the learning in the contraction regions. Our proposed methodology can be used to imitate, reshape, and improve feasible, possibly aggressive, maneuvers. In addition, we can exploit trajectories generated by optimization methods, such as Model Predictive Control (MPC), and a library of maneuvers can be instantly generated. For application, 3-DOF (degrees of freedom) Helicopter and 2D-UAV (unmanned aerial vehicle) models are utilized to demonstrate the main results.
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9
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Learning to Sequence and Blend Robot Skills via Differentiable Optimization. IEEE Robot Autom Lett 2022. [DOI: 10.1109/lra.2022.3184003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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10
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Lanotte F, McKinney Z, Grazi L, Chen B, Crea S, Vitiello N. Adaptive Control Method for Dynamic Synchronization of Wearable Robotic Assistance to Discrete Movements: Validation for Use Case of Lifting Tasks. IEEE T ROBOT 2021. [DOI: 10.1109/tro.2021.3073836] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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11
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Dagenais P, Hensman S, Haechler V, Milinkovitch MC. Elephants evolved strategies reducing the biomechanical complexity of their trunk. Curr Biol 2021; 31:4727-4737.e4. [PMID: 34428468 DOI: 10.1016/j.cub.2021.08.029] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 06/25/2021] [Accepted: 08/09/2021] [Indexed: 02/06/2023]
Abstract
The elephant proboscis (trunk), which functions as a muscular hydrostat with a virtually infinite number of degrees of freedom, is a spectacular organ for delicate to heavy object manipulation as well as social and sensory functions. Using high-resolution motion capture and functional morphology analyses, we show here that elephants evolved strategies that reduce the biomechanical complexity of their trunk. Indeed, our behavioral experiments with objects of various shapes, sizes, and weights indicate that (1) complex behaviors emerge from the combination of a finite set of basic movements; (2) curvature, torsion, and strain provide an appropriate kinematic representation, allowing us to extract motion primitives from the trunk trajectories; (3) transport of objects involves the proximal propagation of an inward curvature front initiated at the tip; (4) the trunk can also form pseudo-joints for point-to-point motion; and (5) the trunk tip velocity obeys a power law with its path curvature, similar to human hand drawing movements. We also reveal with unprecedented precision the functional anatomy of the African and Asian elephant trunks using medical imaging and macro-scale serial sectioning, thus drawing strong connections between motion primitives and muscular synergies. Our study is the first combined quantitative analysis of the mechanical performance, kinematic strategies, and functional morphology of the largest animal muscular hydrostat on Earth. It provides data for developing innovative "soft-robotic" manipulators devoid of articulations, replicating the high compliance, flexibility, and strength of the elephant trunk. VIDEO ABSTRACT.
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Affiliation(s)
- Paule Dagenais
- Laboratory of Artificial and Natural Evolution (LANE), Department of Genetics and Evolution, University of Geneva, 30, Quai Ernest-Ansermet, 1211 Geneva, Switzerland; SIB Swiss Institute of Bioinformatics, 30, Quai Ernest-Ansermet, 1211 Geneva, Switzerland
| | - Sean Hensman
- Adventure with Elephants, Bela Bela, South Africa
| | - Valérie Haechler
- Laboratory of Artificial and Natural Evolution (LANE), Department of Genetics and Evolution, University of Geneva, 30, Quai Ernest-Ansermet, 1211 Geneva, Switzerland
| | - Michel C Milinkovitch
- Laboratory of Artificial and Natural Evolution (LANE), Department of Genetics and Evolution, University of Geneva, 30, Quai Ernest-Ansermet, 1211 Geneva, Switzerland; SIB Swiss Institute of Bioinformatics, 30, Quai Ernest-Ansermet, 1211 Geneva, Switzerland.
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Abd AT, Singh RE, Iqbal K, White G. A Perspective on Muscle Synergies and Different Theories Related to Their Adaptation. BIOMECHANICS 2021; 1:253-263. [DOI: 10.3390/biomechanics1020021] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/01/2023]
Abstract
The human motor system is a complex neuro-musculo sensory system that needs further investigations of neuro-muscular commands and sensory-motor coupling to decode movement execution. Some researchers suggest that the central nervous system (CNS) activates a small set of modules termed muscle synergies to simplify motor control. Further, these modules form functional building blocks of movement as they can explain the neurophysiological characteristics of movements. We can identify and extract these muscle synergies from electromyographic signals (EMG) recorded in the laboratory by using linear decomposition algorithms, such as principal component analysis (PCA) and non-Negative Matrix Factorization Algorithm (NNMF). For the past three decades, the hypothesis of muscle synergies has received considerable attention as we attempt to understand and apply the concept of muscle synergies in clinical settings and rehabilitation. In this article, we first explore the concept of muscle synergies. We then present different strategies of adaptation in these synergies that the CNS employs to accomplish a movement goal.
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Cheung VCK, Seki K. Approaches to revealing the neural basis of muscle synergies: a review and a critique. J Neurophysiol 2021; 125:1580-1597. [PMID: 33729869 DOI: 10.1152/jn.00625.2019] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023] Open
Abstract
The central nervous system (CNS) may produce coordinated motor outputs via the combination of motor modules representable as muscle synergies. Identification of muscle synergies has hitherto relied on applying factorization algorithms to multimuscle electromyographic data (EMGs) recorded during motor behaviors. Recent studies have attempted to validate the neural basis of the muscle synergies identified by independently retrieving the muscle synergies through CNS manipulations and analytic techniques such as spike-triggered averaging of EMGs. Experimental data have demonstrated the pivotal role of the spinal premotor interneurons in the synergies' organization and the presence of motor cortical loci whose stimulations offer access to the synergies, but whether the motor cortex is also involved in organizing the synergies has remained unsettled. We argue that one difficulty inherent in current approaches to probing the synergies' neural basis is that the EMG generative model based on linear combination of synergies and the decomposition algorithms used for synergy identification are not grounded on enough prior knowledge from neurophysiology. Progress may be facilitated by constraining or updating the model and algorithms with knowledge derived directly from CNS manipulations or recordings. An investigative framework based on evaluating the relevance of neurophysiologically constrained models of muscle synergies to natural motor behaviors will allow a more sophisticated understanding of motor modularity, which will help the community move forward from the current debate on the neural versus nonneural origin of muscle synergies.
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Affiliation(s)
- Vincent C K Cheung
- School of Biomedical Sciences and The Gerald Choa Neuroscience Centre, The Chinese University of Hong Kong, Hong Kong, China
| | - Kazuhiko Seki
- Department of Neurophysiology, National Institute of Neuroscience, Kodaira, Tokyo, Japan
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Donnarumma F, Prevete R, Maisto D, Fuscone S, Irvine EM, van der Meer MAA, Kemere C, Pezzulo G. A framework to identify structured behavioral patterns within rodent spatial trajectories. Sci Rep 2021; 11:468. [PMID: 33432100 PMCID: PMC7801653 DOI: 10.1038/s41598-020-79744-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2020] [Accepted: 11/10/2020] [Indexed: 11/09/2022] Open
Abstract
Animal behavior is highly structured. Yet, structured behavioral patterns-or "statistical ethograms"-are not immediately apparent from the full spatiotemporal data that behavioral scientists usually collect. Here, we introduce a framework to quantitatively characterize rodent behavior during spatial (e.g., maze) navigation, in terms of movement building blocks or motor primitives. The hypothesis that we pursue is that rodent behavior is characterized by a small number of motor primitives, which are combined over time to produce open-ended movements. We assume motor primitives to be organized in terms of two sparsity principles: each movement is controlled using a limited subset of motor primitives (sparse superposition) and each primitive is active only for time-limited, time-contiguous portions of movements (sparse activity). We formalize this hypothesis using a sparse dictionary learning method, which we use to extract motor primitives from rodent position and velocity data collected during spatial navigation, and successively to reconstruct past trajectories and predict novel ones. Three main results validate our approach. First, rodent behavioral trajectories are robustly reconstructed from incomplete data, performing better than approaches based on standard dimensionality reduction methods, such as principal component analysis, or single sparsity. Second, the motor primitives extracted during one experimental session generalize and afford the accurate reconstruction of rodent behavior across successive experimental sessions in the same or in modified mazes. Third, in our approach the number of motor primitives associated with each maze correlates with independent measures of maze complexity, hence showing that our formalism is sensitive to essential aspects of task structure. The framework introduced here can be used by behavioral scientists and neuroscientists as an aid for behavioral and neural data analysis. Indeed, the extracted motor primitives enable the quantitative characterization of the complexity and similarity between different mazes and behavioral patterns across multiple trials (i.e., habit formation). We provide example uses of this computational framework, showing how it can be used to identify behavioural effects of maze complexity, analyze stereotyped behavior, classify behavioral choices and predict place and grid cell displacement in novel environments.
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Affiliation(s)
- Francesco Donnarumma
- Institute of Cognitive Sciences and Technologies (ISTC), National Research Council (CNR), Via San Martino della Battaglia 44, 00185, Rome, Italy
| | - Roberto Prevete
- Department of Electric Engineering and Information Technologies (DIETI), Università degli Studi di Napoli Federico II, Naples, Italy
| | - Domenico Maisto
- Institute for High Performance Computing and Networking (ICAR), National Research Council (CNR), Via Pietro Castellino 111, 80131, Naples, Italy
| | | | - Emily M Irvine
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
| | | | - Caleb Kemere
- Electrical and Computer Engineering, Rice University, Houston, TX, USA
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies (ISTC), National Research Council (CNR), Via San Martino della Battaglia 44, 00185, Rome, Italy.
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da Silva Costa AA, Moraes R, Hortobágyi T, Sawers A. Older adults reduce the complexity and efficiency of neuromuscular control to preserve walking balance. Exp Gerontol 2020; 140:111050. [PMID: 32750424 DOI: 10.1016/j.exger.2020.111050] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Revised: 07/24/2020] [Accepted: 07/28/2020] [Indexed: 02/07/2023]
Abstract
Healthy aging modifies neuromuscular control of dynamic balance. Challenging tasks could amplify such modifications, providing clinical insights. We examined the effects of age and walking condition difficulty on neuromuscular control of walking balance. We analyzed whole-body kinematics and activity of 13 right leg and trunk muscles in 17 young (11 males and 6 females; age 24 ± 3 years) and 14 older adults (3 males and 11 females; age 69 ± 4 years) while walking on a taped line on the floor and a 6-cm wide beam. Spatiotemporal parameters of gait, margin of stability, motor performance, and muscle synergies were estimated. Regardless of age, maintaining walking balance was more difficult on the beam compared to the taped line as evidenced by a shorter distance walked (17.3%), a reduction in step length (5.8%) and speed (10.3%), as well as a 40.0% smaller margin of stability during beam vs. tape walking. The number of muscle synergies was also higher during beam vs. tape walking. Compared to younger adults, older adults had larger margin of stability during beam walking. Older adults also had higher muscle co-activity within each muscle synergy and greater variance accounted for by the first muscle synergy regardless of condition. Such age-effects may be interpreted as a safer, less efficient, and less complex neuromuscular modular control strategy. In conclusion, beam walking increased the difficulty of maintaining walking balance and induced adaptations in modular control. It seems that healthy older adults reduce the complexity and efficiency of neuromuscular control of walking to preserve walking balance.
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Affiliation(s)
- Andréia Abud da Silva Costa
- Ribeirão Preto Medical School, Graduate Program in Rehabilitation and Functional Performance, University of São Paulo, Brazil; Biomechanics and Motor Control Lab, School of Physical Education and Sport of Ribeirão Preto, University of São Paulo, Brazil
| | - Renato Moraes
- Ribeirão Preto Medical School, Graduate Program in Rehabilitation and Functional Performance, University of São Paulo, Brazil; Biomechanics and Motor Control Lab, School of Physical Education and Sport of Ribeirão Preto, University of São Paulo, Brazil
| | - Tibor Hortobágyi
- Center for Human Movement Sciences, University of Groningen Medical Center, Groningen, the Netherlands
| | - Andrew Sawers
- Department of Kinesiology and Nutrition, University of Illinois at Chicago, Chicago, IL, United States.
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16
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On Primitives in Motor Control. Motor Control 2020; 24:318-346. [DOI: 10.1123/mc.2019-0099] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2019] [Revised: 12/03/2019] [Accepted: 12/07/2019] [Indexed: 11/18/2022]
Abstract
The concept of primitives has been used in motor control both as a theoretical construct and as a means of describing the results of experimental studies involving multiple moving elements. This concept is close to Bernstein’s notion of engrams and level of synergies. Performance primitives have been explored in spaces of peripheral variables but interpreted in terms of neural control primitives. Performance primitives reflect a variety of mechanisms ranging from body mechanics to spinal mechanisms and to supraspinal circuitry. This review suggests that primitives originate at the task level as preferred time functions of spatial referent coordinates or at mappings from higher level referent coordinates to lower level, frequently abundant, referent coordinate sets. Different patterns of performance primitives can emerge depending, in particular, on the external force field.
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Pellegrino L, Coscia M, Casadio M. Muscle activities in similar arms performing identical tasks reveal the neural basis of muscle synergies. Exp Brain Res 2019; 238:121-138. [DOI: 10.1007/s00221-019-05679-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2019] [Accepted: 11/07/2019] [Indexed: 12/19/2022]
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18
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Mohan V, Bhat A, Morasso P. Muscleless motor synergies and actions without movements: From motor neuroscience to cognitive robotics. Phys Life Rev 2019; 30:89-111. [DOI: 10.1016/j.plrev.2018.04.005] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2017] [Revised: 04/12/2018] [Accepted: 04/16/2018] [Indexed: 10/17/2022]
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19
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Toma S, Santello M. Motor modules account for active perception of force. Sci Rep 2019; 9:8983. [PMID: 31222076 PMCID: PMC6586614 DOI: 10.1038/s41598-019-45480-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2018] [Accepted: 06/10/2019] [Indexed: 11/30/2022] Open
Abstract
Despite longstanding evidence suggesting a relation between action and perception, the mechanisms underlying their integration are still unclear. It has been proposed that to simplify the sensorimotor integration processes underlying active perception, the central nervous system (CNS) selects patterns of movements aimed at maximizing sampling of task-related sensory input. While previous studies investigated the action-perception loop focusing on the role of higher-level features of motor behavior (e.g., kinematic invariants, effort), the present study explored and quantified the contribution of lower-level organization of motor control. We tested the hypothesis that the coordinated recruitment of group of muscles (i.e., motor modules) engaged to counteract an external force contributes to participants’ perception of the same force. We found that: 1) a model describing the modulation of a subset of motor modules involved in the motor task accounted for about 70% of participants’ perceptual variance; 2) an alternative model, incompatible with the motor modules hypothesis, accounted for significantly lower variance of participants’ detection performance. Our results provide empirical evidence of the potential role played by muscle activation patterns in active perception of force. They also suggest that a modular organization of motor control may mediate not only coordination of multiple muscles, but also perceptual inference.
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Affiliation(s)
- Simone Toma
- Laboratory of Neuromotor Physiology, Santa Lucia Foundation, Rome, 00179, Italy. .,School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, 85287-9709, USA.
| | - Marco Santello
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, 85287-9709, USA
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20
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Deng K, Szczecinski NS, Arnold D, Andrada E, Fischer MS, Quinn RD, Hunt AJ. Neuromechanical Model of Rat Hindlimb Walking with Two-Layer CPGs. Biomimetics (Basel) 2019; 4:E21. [PMID: 31105206 PMCID: PMC6477610 DOI: 10.3390/biomimetics4010021] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Revised: 02/16/2019] [Accepted: 02/19/2019] [Indexed: 01/05/2023] Open
Abstract
This work demonstrates a neuromechanical model of rat hindlimb locomotion undergoing nominal walking with perturbations. In the animal, two types of responses to perturbations are observed: resetting and non-resetting deletions. This suggests that the animal locomotor system contains a memory-like organization. To model this phenomenon, we built a synthetic nervous system that uses separate rhythm generator and pattern formation layers to activate antagonistic muscle pairs about each joint in the sagittal plane. Our model replicates the resetting and non-resetting deletions observed in the animal. In addition, in the intact (i.e., fully afferented) rat walking simulation, we observe slower recovery after perturbation, which is different from the deafferented animal experiment. These results demonstrate that our model is a biologically feasible description of some of the neural circuits in the mammalian spinal cord that control locomotion, and the difference between our simulation and fictive motion shows the importance of sensory feedback on motor output. This model also demonstrates how the pattern formation network can activate muscle synergies in a coordinated way to produce stable walking, which motivates the use of more complex synergies activating more muscles in the legs for three-dimensional limb motion.
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Affiliation(s)
- Kaiyu Deng
- Department of Mechanical and Aerospace Engineering, Case Western Reserve University, Cleveland, OH 44106, USA.
| | - Nicholas S Szczecinski
- Department of Mechanical and Aerospace Engineering, Case Western Reserve University, Cleveland, OH 44106, USA.
| | - Dirk Arnold
- Institute of Zoology and Evolutionary Research, Friedrich-Schiller University Jena, Erbertstr. 1, 07743 Jena, Germany.
| | - Emanuel Andrada
- Institute of Zoology and Evolutionary Research, Friedrich-Schiller University Jena, Erbertstr. 1, 07743 Jena, Germany.
| | - Martin S Fischer
- Institute of Zoology and Evolutionary Research, Friedrich-Schiller University Jena, Erbertstr. 1, 07743 Jena, Germany.
| | - Roger D Quinn
- Department of Mechanical and Aerospace Engineering, Case Western Reserve University, Cleveland, OH 44106, USA.
| | - Alexander J Hunt
- Department of Mechanical and Materials Engineering, Portland State University, Portland, OR 97207, USA.
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Berrueta TA, Pervan A, Fitzsimons K, Murphey TD. Dynamical System Segmentation for Information Measures in Motion. IEEE Robot Autom Lett 2019. [DOI: 10.1109/lra.2018.2884091] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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22
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Barrett LF, Finlay BL. Concepts, Goals and the Control of Survival-Related Behaviors. Curr Opin Behav Sci 2018; 24:172-179. [PMID: 31157289 DOI: 10.1016/j.cobeha.2018.10.001] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Scientists have long studied the actions that impact basic survival in various domains of life, such as defense, foraging, reproduction, thermoregulation, and so on, as if such actions will reveal the nature of emotion. Each domain of survival came to be characterized by a repertoire of distinct actions, and each action was thought to be caused by a dedicated neural circuit, called a survival circuit. Survival circuits are thought to be triggered by sensory events in the world, quickly producing obligatory, stereotypic reflexes as well as more flexible, deliberate responses. In this paper, we consider recent evidence from behavioral ecology that even so-called "reflexes" are better understood as purposeful, flexible actions that unfold across a range of temporal trajectories. They are highly context-dependent and tailored to the requirements of the situation. We then consider evidence from the neuroscience of motor control that motor actions are assembled by neural populations, not triggered by simple circuits. We end by considering the value of these suggestions for understanding the species-general vs. species-specific contributions to emotion.
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Affiliation(s)
- Lisa Feldman Barrett
- Department of Psychology, Northeastern University.,Psychiatric Neuroimaging Division, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital
| | - Barbara L Finlay
- Behavioral and Evolutionary Neuroscience Group, Department of Psychology, Cornell University
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23
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Consistent visuomotor adaptations and generalizations can be achieved through different rotations of robust motor modules. Sci Rep 2018; 8:12657. [PMID: 30140072 PMCID: PMC6107677 DOI: 10.1038/s41598-018-31174-2] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2018] [Accepted: 08/08/2018] [Indexed: 12/29/2022] Open
Abstract
Humans can adapt their motor commands in response to alterations in the movement environment. This is achieved by tuning different motor primitives, generating adaptations that can be generalized also to relevant untrained scenarios. A theory of motor primitives has shown that natural movements can be described as combinations of muscle synergies. Previous studies have shown that motor adaptations are achieved by tuning the recruitment of robust synergy modules. Here we tested if: 1) different synergistic tunings can be achieved in response to the same perturbations applied with different orders of exposure; 2) different synergistic tunings can explain different patterns of generalization of adaptation. We found that exposing healthy individuals to two visuomotor rotation perturbations covering different parts of the same workspace in a different order resulted in different tunings of the activation of the same set of synergies. Nevertheless, these tunings resulted in the same net biomechanical adaptation patterns. We also show that the characteristics of the different tunings correlate with the presence and extent of generalization of adaptation to untrained portions of the workspace. Our results confirm synergies as invariant motor primitives whose recruitment is dynamically tuned during motor adaptations.
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DeWolf T, Stewart TC, Slotine JJ, Eliasmith C. A spiking neural model of adaptive arm control. Proc Biol Sci 2017; 283:rspb.2016.2134. [PMID: 27903878 DOI: 10.1098/rspb.2016.2134] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2016] [Accepted: 11/03/2016] [Indexed: 11/12/2022] Open
Abstract
We present a spiking neuron model of the motor cortices and cerebellum of the motor control system. The model consists of anatomically organized spiking neurons encompassing premotor, primary motor, and cerebellar cortices. The model proposes novel neural computations within these areas to control a nonlinear three-link arm model that can adapt to unknown changes in arm dynamics and kinematic structure. We demonstrate the mathematical stability of both forms of adaptation, suggesting that this is a robust approach for common biological problems of changing body size (e.g. during growth), and unexpected dynamic perturbations (e.g. when moving through different media, such as water or mud). To demonstrate the plausibility of the proposed neural mechanisms, we show that the model accounts for data across 19 studies of the motor control system. These data include a mix of behavioural and neural spiking activity, across subjects performing adaptive and static tasks. Given this proposed characterization of the biological processes involved in motor control of the arm, we provide several experimentally testable predictions that distinguish our model from previous work.
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Affiliation(s)
- Travis DeWolf
- Centre for Theoretical Neuroscience, University of Waterloo, Waterloo, Ontario, Canada N2L3G1 .,Applied Brain Research, Inc., Waterloo, Ontario, Canada N2L3G1
| | - Terrence C Stewart
- Centre for Theoretical Neuroscience, University of Waterloo, Waterloo, Ontario, Canada N2L3G1.,Applied Brain Research, Inc., Waterloo, Ontario, Canada N2L3G1
| | | | - Chris Eliasmith
- Centre for Theoretical Neuroscience, University of Waterloo, Waterloo, Ontario, Canada N2L3G1.,Applied Brain Research, Inc., Waterloo, Ontario, Canada N2L3G1
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25
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EEG topographies provide subject-specific correlates of motor control. Sci Rep 2017; 7:13229. [PMID: 29038516 PMCID: PMC5643537 DOI: 10.1038/s41598-017-13482-1] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2017] [Accepted: 09/25/2017] [Indexed: 11/08/2022] Open
Abstract
Electroencephalography (EEG) of brain activity can be represented in terms of dynamically changing topographies (microstates). Notably, spontaneous brain activity recorded at rest can be characterized by four distinctive topographies. Despite their well-established role during resting state, their implication in the generation of motor behavior is debated. Evidence of such a functional role of spontaneous brain activity would provide support for the design of novel and sensitive biomarkers in neurological disorders. Here we examined whether and to what extent intrinsic brain activity contributes and plays a functional role during natural motor behaviors. For this we first extracted subject-specific EEG microstates and muscle synergies during reaching-and-grasping movements in healthy volunteers. We show that, in every subject, well-known resting-state microstates persist during movement execution with similar topographies and temporal characteristics, but are supplemented by novel task-related microstates. We then show that the subject-specific microstates' dynamical organization correlates with the activation of muscle synergies and can be used to decode individual grasping movements with high accuracy. These findings provide first evidence that spontaneous brain activity encodes detailed information about motor control, offering as such the prospect of a novel tool for the definition of subject-specific biomarkers of brain plasticity and recovery in neuro-motor disorders.
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26
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Olesh EV, Pollard BS, Gritsenko V. Gravitational and Dynamic Components of Muscle Torque Underlie Tonic and Phasic Muscle Activity during Goal-Directed Reaching. Front Hum Neurosci 2017; 11:474. [PMID: 29018339 PMCID: PMC5623018 DOI: 10.3389/fnhum.2017.00474] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2017] [Accepted: 09/11/2017] [Indexed: 12/24/2022] Open
Abstract
Human reaching movements require complex muscle activations to produce the forces necessary to move the limb in a controlled manner. How gravity and the complex kinetic properties of the limb contribute to the generation of the muscle activation pattern by the central nervous system (CNS) is a long-standing and controversial question in neuroscience. To tackle this issue, muscle activity is often subdivided into static and phasic components. The former corresponds to posture maintenance and transitions between postures. The latter corresponds to active movement production and the compensation for the kinetic properties of the limb. In the present study, we improved the methodology for this subdivision of muscle activity into static and phasic components by relating them to joint torques. Ten healthy subjects pointed in virtual reality to visual targets arranged to create a standard center-out reaching task in three dimensions. Muscle activity and motion capture data were synchronously collected during the movements. The motion capture data were used to calculate postural and dynamic components of active muscle torques using a dynamic model of the arm with 5 degrees of freedom. Principal Component Analysis (PCA) was then applied to muscle activity and the torque components, separately, to reduce the dimensionality of the data. Muscle activity was also reconstructed from gravitational and dynamic torque components. Results show that the postural and dynamic components of muscle torque represent a significant amount of variance in muscle activity. This method could be used to define static and phasic components of muscle activity using muscle torques.
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Affiliation(s)
- Erienne V Olesh
- Department of Human Performance, School of Medicine, West Virginia University, Morgantown, WV, United States.,Centers for Neuroscience, School of Medicine, West Virginia University, Morgantown, WV, United States
| | - Bradley S Pollard
- Department of Human Performance, School of Medicine, West Virginia University, Morgantown, WV, United States.,Centers for Neuroscience, School of Medicine, West Virginia University, Morgantown, WV, United States
| | - Valeriya Gritsenko
- Department of Human Performance, School of Medicine, West Virginia University, Morgantown, WV, United States.,Centers for Neuroscience, School of Medicine, West Virginia University, Morgantown, WV, United States.,Department of Mechanical and Aerospace Engineering, Benjamin M. Statler College of Engineering and Mineral Resources, West Virginia University, Morgantown, WV, United States
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27
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Temporal specificity of the initial adaptive response in motor adaptation. PLoS Comput Biol 2017; 13:e1005438. [PMID: 28692658 PMCID: PMC5503165 DOI: 10.1371/journal.pcbi.1005438] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2015] [Accepted: 03/02/2017] [Indexed: 11/19/2022] Open
Abstract
Repeated exposure to a novel physical environment eventually leads to a mature adaptive response whereby feedforward changes in motor output mirror both the amplitude and temporal structure of the environmental perturbations. However, adaptive responses at the earliest stages of learning have been found to be not only smaller, but systematically less specific in their temporal structure compared to later stages of learning. This observation has spawned a lively debate as to whether the temporal structure of the initial adaptive response is, in fact, stereotyped and non-specific. To settle this debate, we directly measured the adaptive responses to velocity-dependent and position-dependent force-field perturbations (vFFs and pFFs) at the earliest possible stage of motor learning in humans–after just a single-movement exposure. In line with previous work, we found these earliest stage adaptive responses to be more similar than the perturbations that induced them. However, the single-trial adaptive responses for vFF and pFF perturbations were clearly distinct, and the disparity between them reflected the difference between the temporal structure of the perturbations that drove them. Critically, we observed these differences between single-trial adaptive responses when vFF and pFF perturbations were randomly intermingled from one trial to the next within the same block, indicating perturbation response specificity at the single trial level. These findings demonstrate that the initial adaptive responses to physical perturbations are not stereotyped. Instead, the neural plasticity in sensorimotor areas is sensitive to the temporal structure of a movement perturbation even at the earliest stage in learning. This insight has direct implications for the development of computational models of early-stage motor adaptation and the evolution of this adaptive response with continued training. With repeated exposure to a perturbation, the sensorimotor system learns to develop an adaptive response that is highly specific to both the amplitude and temporal structure of that perturbation in order to effectively counteract it. It is widely known that the amplitude of the adaptive response starts small and gradually grows to the right size with repeated exposure. However, it is also the case that the temporal structure of the adaptive response starts somewhat generically and gradually grows into the right shape with repeated exposure. A key question is whether the adaptive response to a perturbation begins with a stereotyped temporal structure that only becomes specified with further practice, or if it begins with a degree of specificity for the experienced perturbation that need only to be refined by practice. Here, by precisely measuring the temporal pattern of motor output in the single-trial adaptive response to two different perturbations, we show that the initial adaptive response is indeed specific to the temporal characteristics of the perturbation, even when the disturbance randomly changed from one trial to the next. These results demonstrate that the sensorimotor system is sensitive to the temporal features of a disturbance, even when experienced just once.
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28
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Kinematics in the brain: unmasking motor control strategies? Exp Brain Res 2017; 235:2639-2651. [PMID: 28573311 PMCID: PMC5550544 DOI: 10.1007/s00221-017-4982-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2016] [Accepted: 05/10/2017] [Indexed: 12/02/2022]
Abstract
In rhythmical movement performance, our brain has to sustain movement while correcting for biological noise-induced variability. Here, we explored the functional anatomy of brain networks during voluntary rhythmical elbow flexion/extension using kinematic movement regressors in fMRI analysis to verify the interest of method to address motor control in a neurological population. We found the expected systematic activation of the primary sensorimotor network that is suggested to generate the rhythmical movement. By adding the kinematic regressors to the model, we demonstrated the potential involvement of cerebellar–frontal circuits as a function of the irregularity of the variability of the movement and the primary sensory cortex in relation to the trajectory length during task execution. We suggested that different functional brain networks were related to two different aspects of rhythmical performance: rhythmicity and error control. Concerning the latter, the partitioning between more automatic control involving cerebellar–frontal circuits versus less automatic control involving the sensory cortex seemed thereby crucial for optimal performance. Our results highlight the potential of using co-registered fine-grained kinematics and fMRI measures to interpret functional MRI activations and to potentially unmask the organisation of neural correlates during motor control.
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Ferrante S, Chia Bejarano N, Ambrosini E, Nardone A, Turcato AM, Monticone M, Ferrigno G, Pedrocchi A. A Personalized Multi-Channel FES Controller Based on Muscle Synergies to Support Gait Rehabilitation after Stroke. Front Neurosci 2016; 10:425. [PMID: 27695397 PMCID: PMC5025903 DOI: 10.3389/fnins.2016.00425] [Citation(s) in RCA: 52] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2016] [Accepted: 08/30/2016] [Indexed: 01/22/2023] Open
Abstract
It has been largely suggested in neuroscience literature that to generate a vast variety of movements, the Central Nervous System (CNS) recruits a reduced set of coordinated patterns of muscle activities, defined as muscle synergies. Recent neurophysiological studies have recommended the analysis of muscle synergies to finely assess the patient's impairment, to design personalized interventions based on the specific nature of the impairment, and to evaluate the treatment outcomes. In this scope, the aim of this study was to design a personalized multi-channel functional electrical stimulation (FES) controller for gait training, integrating three novel aspects: (1) the FES strategy was based on healthy muscle synergies in order to mimic the neural solutions adopted by the CNS to generate locomotion; (2) the FES strategy was personalized according to an initial locomotion assessment of the patient and was designed to specifically activate the impaired biomechanical functions; (3) the FES strategy was mapped accurately on the altered gait kinematics providing a maximal synchronization between patient's volitional gait and stimulation patterns. The novel intervention was tested on two chronic stroke patients. They underwent a 4-week intervention consisting of 30-min sessions of FES-supported treadmill walking three times per week. The two patients were characterized by a mild gait disability (walking speed > 0.8 m/s) at baseline. However, before treatment both patients presented only three independent muscle synergies during locomotion, resembling two different gait abnormalities. After treatment, the number of extracted synergies became four and they increased their resemblance with the physiological muscle synergies, which indicated a general improvement in muscle coordination. The originally merged synergies seemed to regain their distinct role in locomotion control. The treatment benefits were more evident for one patient, who achieved a clinically important change in dynamic balance (Mini-Best Test increased from 17 to 22) coupled with a very positive perceived treatment effect (GRC = 4). The treatment had started the neuro-motor relearning process also on the second subject, but twelve sessions were not enough to achieve clinically relevant improvements. This attempt to apply the novel theories of neuroscience research in stroke rehabilitation has provided promising results, and deserves to be further investigated in a larger clinical study.
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Affiliation(s)
- Simona Ferrante
- Neuroengineering and Medical Robotics Laboratory, Department of Electronics, Information and Bioengineering, Politecnico di Milano Milan, Italy
| | - Noelia Chia Bejarano
- Neuroengineering and Medical Robotics Laboratory, Department of Electronics, Information and Bioengineering, Politecnico di Milano Milan, Italy
| | - Emilia Ambrosini
- Neuroengineering and Medical Robotics Laboratory, Department of Electronics, Information and Bioengineering, Politecnico di MilanoMilan, Italy; Physical Medicine and Rehabilitation Unit, Scientific Institute of Lissone, Fondazione Salvatore Maugeri (IRCCS)Lissone, Monza Brianza, Italy
| | - Antonio Nardone
- Posture and Movement Laboratory, Division of Physical Medicine and Rehabilitation, Scientific Institute of Veruno, Fondazione Salvatore Maugeri (IRCCS)Veruno, Novara, Italy; Department of Translational Medicine, University of Eastern PiedmontNovara, Italy
| | - Anna M Turcato
- Posture and Movement Laboratory, Division of Physical Medicine and Rehabilitation, Scientific Institute of Veruno, Fondazione Salvatore Maugeri (IRCCS)Veruno, Novara, Italy; Department of Translational Medicine, University of Eastern PiedmontNovara, Italy
| | - Marco Monticone
- Physical Medicine and Rehabilitation Unit, Scientific Institute of Lissone, Fondazione Salvatore Maugeri (IRCCS)Lissone, Monza Brianza, Italy; Department of Public Health, Clinical and Molecular Medicine, University of CagliariCagliari, Italy
| | - Giancarlo Ferrigno
- Neuroengineering and Medical Robotics Laboratory, Department of Electronics, Information and Bioengineering, Politecnico di Milano Milan, Italy
| | - Alessandra Pedrocchi
- Neuroengineering and Medical Robotics Laboratory, Department of Electronics, Information and Bioengineering, Politecnico di Milano Milan, Italy
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Lappi O. Eye movements in the wild: Oculomotor control, gaze behavior & frames of reference. Neurosci Biobehav Rev 2016; 69:49-68. [PMID: 27461913 DOI: 10.1016/j.neubiorev.2016.06.006] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2015] [Revised: 05/14/2016] [Accepted: 06/08/2016] [Indexed: 11/19/2022]
Abstract
Understanding the brain's capacity to encode complex visual information from a scene and to transform it into a coherent perception of 3D space and into well-coordinated motor commands are among the outstanding questions in the study of integrative brain function. Eye movement methodologies have allowed us to begin addressing these questions in increasingly naturalistic tasks, where eye and body movements are ubiquitous and, therefore, the applicability of most traditional neuroscience methods restricted. This review explores foundational issues in (1) how oculomotor and motor control in lab experiments extrapolates into more complex settings and (2) how real-world gaze behavior in turn decomposes into more elementary eye movement patterns. We review the received typology of oculomotor patterns in laboratory tasks, and how they map onto naturalistic gaze behavior (or not). We discuss the multiple coordinate systems needed to represent visual gaze strategies, how the choice of reference frame affects the description of eye movements, and the related but conceptually distinct issue of coordinate transformations between internal representations within the brain.
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Affiliation(s)
- Otto Lappi
- Cognitive Science, Institute of Behavioural Sciences, PO BOX 9, 00014 University of Helsinki, Finland.
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31
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Stramandinoli F, Marocco D, Cangelosi A. Making sense of words: a robotic model for language abstraction. Auton Robots 2016. [DOI: 10.1007/s10514-016-9587-8] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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33
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Huang FC, Patton JL. Movement distributions of stroke survivors exhibit distinct patterns that evolve with training. J Neuroeng Rehabil 2016; 13:23. [PMID: 26961682 PMCID: PMC4785660 DOI: 10.1186/s12984-016-0132-y] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2014] [Accepted: 02/29/2016] [Indexed: 11/15/2022] Open
Abstract
Background While clinical assessments provide tools for characterizing abilities in motor-impaired individuals, concerns remain over their repeatability and reliability. Typical robot-assisted training studies focus on repetition of prescribed actions, yet such movement data provides an incomplete account of abnormal patterns of coordination. Recent studies have shown positive effects from self-directed movement, yet such a training paradigm leads to challenges in how to quantify and interpret performance. Methods With data from chronic stroke survivors (n = 10, practicing for 3 days), we tabulated histograms of the displacement, velocity, and acceleration for planar motion, and examined whether modeling of distributions could reveal changes in available movement patterns. We contrasted these results with scalar measures of the range of motion. We performed linear discriminant analysis (LDA) classification with selected histogram features to compare predictions versus actual subject identifiers. As a basis of comparison, we also present an age-matched control group of healthy individuals (n = 10, practicing for 1 day). Results Analysis of range of motion did not show improvement from self-directed movement training for the stroke survivors in this study. However, examination of distributions indicated that increased multivariate normal components were needed to accurately model the patterns of movement after training. Stroke survivors generally exhibited more complex distributions of motor exploration compared to the age-matched control group. Classification using linear discriminant analysis revealed that movement patterns were identifiable by individual. Individuals in the control group were more difficult to identify using classification methods, consistent with the idea that motor deficits contribute significantly to unique movement signatures. Conclusions Distribution analysis revealed individual patterns of abnormal coordination in stroke survivors and changes in these patterns with training. These findings were not apparent from scalar metrics that simply summarized properties of motor exploration. Our results suggest new methods for characterizing motor capabilities, and could provide the basis for powerful tools for designing customized therapy.
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Affiliation(s)
- Felix C Huang
- Sensory Motor Performance Program, Rehabilitation Institute of Chicago, 345 E, Superior Street, Suite 1406, Chicago, IL, 60611, USA.
| | - James L Patton
- Department of Bioengineering, University of Illinois at Chicago, 851 S. Morgan Street, Room 222, Chicago, IL, 60612, USA.
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34
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Reversible Deactivation of Motor Cortex Reveals Functional Connectivity with Posterior Parietal Cortex in the Prosimian Galago (Otolemur garnettii). J Neurosci 2016; 35:14406-22. [PMID: 26490876 DOI: 10.1523/jneurosci.1468-15.2015] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
UNLABELLED We examined the functional macrocircuitry of frontoparietal networks in the neocortex of prosimian primates (Otolemur garnettii) using a microfluidic thermal regulator to reversibly deactivate selected regions of motor cortex (M1). During deactivation of either forelimb or mouth/face movement domains within M1, we used long-train intracortical microstimulation techniques to evoke movements from the rostral division of posterior parietal cortex (PPCr). We found that deactivation of M1 movement domains in most instances abolished movements evoked in PPCr. The most common effect of deactivating M1 was to abolish evoked movements in a homotopic domain in PPCr. For example, deactivating M1 forelimb lift domains resulted in loss of evoked movement in forelimb domains in PPCr. However, at some sites, we also observed heterotopic effects; deactivating a specific domain in M1 (e.g., forelimb lift) resulted in loss of evoked movement in a different movement domain in PPCr (e.g., hand-to-mouth or eye-blink). At most sites examined in PPCr, rewarming M1 resulted in a reestablishment of the baseline movement at the same amplitude as that observed before cooling. However, at some sites, reactivation did not result in a return to baseline movement or to the full amplitude of the baseline movement. We discuss our findings in the context of frontoparietal circuits and how they may subserve a repertoire of ecologically relevant behaviors. SIGNIFICANCE STATEMENT The posterior parietal cortex (PPC) of primates integrates sensory information used to guide movements. Different modules within PPC and motor cortex (M1) appear to control various motor behaviors (e.g., reaching, defense, and feeding). How these modules work together may vary across species and may explain differences in dexterity and even the capacity for tool use. We investigated the functional connectivity of these modules in galagos, a prosimian primate with relatively simple frontoparietal circuitry. By deactivating a reaching module in M1, we interfered with the function of similar PPC modules and occasionally unrelated PPC modules as well (e.g., eye blink). This circuitry in galagos, therefore, is more complex than in nonprimates, indicating that it has been altered with the expansion of primate PPC.
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Mangin O, Filliat D, ten Bosch L, Oudeyer PY. MCA-NMF: Multimodal Concept Acquisition with Non-Negative Matrix Factorization. PLoS One 2015; 10:e0140732. [PMID: 26489021 PMCID: PMC4619362 DOI: 10.1371/journal.pone.0140732] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2015] [Accepted: 09/28/2015] [Indexed: 11/19/2022] Open
Abstract
In this paper we introduce MCA-NMF, a computational model of the acquisition of multimodal concepts by an agent grounded in its environment. More precisely our model finds patterns in multimodal sensor input that characterize associations across modalities (speech utterances, images and motion). We propose this computational model as an answer to the question of how some class of concepts can be learnt. In addition, the model provides a way of defining such a class of plausibly learnable concepts. We detail why the multimodal nature of perception is essential to reduce the ambiguity of learnt concepts as well as to communicate about them through speech. We then present a set of experiments that demonstrate the learning of such concepts from real non-symbolic data consisting of speech sounds, images, and motions. Finally we consider structure in perceptual signals and demonstrate that a detailed knowledge of this structure, named compositional understanding can emerge from, instead of being a prerequisite of, global understanding. An open-source implementation of the MCA-NMF learner as well as scripts and associated experimental data to reproduce the experiments are publicly available.
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Affiliation(s)
- Olivier Mangin
- Flowers Team, Inria, Bordeaux, France
- U2IS, ENSTA ParisTech, Université Paris Saclay, Saclay, France
- * E-mail:
| | - David Filliat
- Flowers Team, Inria, Bordeaux, France
- U2IS, ENSTA ParisTech, Université Paris Saclay, Saclay, France
| | - Louis ten Bosch
- Centre for Language and Speech Technology, Radboud University, Nijmegen, Netherlands
| | - Pierre-Yves Oudeyer
- Flowers Team, Inria, Bordeaux, France
- U2IS, ENSTA ParisTech, Université Paris Saclay, Saclay, France
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Sawers A, Allen JL, Ting LH. Long-term training modifies the modular structure and organization of walking balance control. J Neurophysiol 2015; 114:3359-73. [PMID: 26467521 DOI: 10.1152/jn.00758.2015] [Citation(s) in RCA: 96] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2015] [Accepted: 10/13/2015] [Indexed: 01/08/2023] Open
Abstract
How does long-term training affect the neural control of movements? Here we tested the hypothesis that long-term training leading to skilled motor performance alters muscle coordination during challenging, as well as nominal everyday motor behaviors. Using motor module (a.k.a., muscle synergy) analyses, we identified differences in muscle coordination patterns between professionally trained ballet dancers (experts) and untrained novices that accompanied differences in walking balance proficiency assessed using a challenging beam-walking test. During beam walking, we found that experts recruited more motor modules than novices, suggesting an increase in motor repertoire size. Motor modules in experts had less muscle coactivity and were more consistent than in novices, reflecting greater efficiency in muscle output. Moreover, the pool of motor modules shared between beam and overground walking was larger in experts compared with novices, suggesting greater generalization of motor module function across multiple behaviors. These differences in motor output between experts and novices could not be explained by differences in kinematics, suggesting that they likely reflect differences in the neural control of movement following years of training rather than biomechanical constraints imposed by the activity or musculoskeletal structure and function. Our results suggest that to learn challenging new behaviors, we may take advantage of existing motor modules used for related behaviors and sculpt them to meet the demands of a new behavior.
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Affiliation(s)
- Andrew Sawers
- Department of Kinesiology, University of Illinois at Chicago, Chicago, Illinois; and
| | - Jessica L Allen
- Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, Georgia
| | - Lena H Ting
- Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, Georgia
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Kaas JH, Stepniewska I. Evolution of posterior parietal cortex and parietal-frontal networks for specific actions in primates. J Comp Neurol 2015; 524:595-608. [PMID: 26101180 DOI: 10.1002/cne.23838] [Citation(s) in RCA: 81] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2015] [Revised: 06/16/2015] [Accepted: 06/16/2015] [Indexed: 12/21/2022]
Abstract
Posterior parietal cortex (PPC) is an extensive region of the human brain that develops relatively late and is proportionally large compared with that of monkeys and prosimian primates. Our ongoing comparative studies have led to several conclusions about the evolution of this posterior parietal region. In early placental mammals, PPC likely was a small multisensory region much like PPC of extant rodents and tree shrews. In early primates, PPC likely resembled that of prosimian galagos, in which caudal PPC (PPCc) is visual and rostral PPC (PPCr) has eight or more multisensory domains where electrical stimulation evokes different complex motor behaviors, including reaching, hand-to-mouth, looking, protecting the face or body, and grasping. These evoked behaviors depend on connections with functionally matched domains in premotor cortex (PMC) and motor cortex (M1). Domains in each region compete with each other, and a serial arrangement of domains allows different factors to influence motor outcomes successively. Similar arrangements of domains have been retained in New and Old World monkeys, and humans appear to have at least some of these domains. The great expansion and prolonged development of PPC in humans suggest the addition of functionally distinct territories. We propose that, across primates, PMC and M1 domains are second and third levels in a number of parallel, interacting networks for mediating and selecting one type of action over others.
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Affiliation(s)
- Jon H Kaas
- Department of Psychology, Vanderbilt University, Nashville, Tennessee, 37240
| | - Iwona Stepniewska
- Department of Psychology, Vanderbilt University, Nashville, Tennessee, 37240
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Jarc AM, Nisky I. Robot-assisted surgery: an emerging platform for human neuroscience research. Front Hum Neurosci 2015; 9:315. [PMID: 26089785 PMCID: PMC4455232 DOI: 10.3389/fnhum.2015.00315] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2015] [Accepted: 05/18/2015] [Indexed: 12/26/2022] Open
Abstract
Classic studies in human sensorimotor control use simplified tasks to uncover fundamental control strategies employed by the nervous system. Such simple tasks are critical for isolating specific features of motor, sensory, or cognitive processes, and for inferring causality between these features and observed behavioral changes. However, it remains unclear how these theories translate to complex sensorimotor tasks or to natural behaviors. Part of the difficulty in performing such experiments has been the lack of appropriate tools for measuring complex motor skills in real-world contexts. Robot-assisted surgery (RAS) provides an opportunity to overcome these challenges by enabling unobtrusive measurements of user behavior. In addition, a continuum of tasks with varying complexity-from simple tasks such as those in classic studies to highly complex tasks such as a surgical procedure-can be studied using RAS platforms. Finally, RAS includes a diverse participant population of inexperienced users all the way to expert surgeons. In this perspective, we illustrate how the characteristics of RAS systems make them compelling platforms to extend many theories in human neuroscience, as well as, to develop new theories altogether.
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Affiliation(s)
- Anthony M Jarc
- Medical Research, Intuitive Surgical, Inc. Sunnyvale, CA, USA
| | - Ilana Nisky
- Biomedical Engineering, Ben-Gurion University of the Negev Beer Sheva, Israel
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Sosnik R, Chaim E, Flash T. Stopping is not an option: the evolution of unstoppable motion elements (primitives). J Neurophysiol 2015; 114:846-56. [PMID: 26041827 DOI: 10.1152/jn.00341.2015] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2015] [Accepted: 06/01/2015] [Indexed: 11/22/2022] Open
Abstract
Stopping performance is known to depend on low-level motion features, such as movement velocity. It is not known, however, whether it is also subject to high-level motion constraints. Here, we report results of 15 subjects instructed to connect four target points depicted on a digitizing tablet and stop "as rapidly as possible" upon hearing a "stop" cue (tone). Four subjects connected target points with straight paths, whereas 11 subjects generated movements corresponding to coarticulation between adjacent movement components. For the noncoarticulating and coarticulating subjects, stopping performance was not correlated or only weakly correlated with motion velocity, respectively. The generation of a straight, point-to-point movement or a smooth, curved trajectory was not disturbed by the occurrence of a stop cue. Overall, the results indicate that stopping performance is subject to high-level motion constraints, such as the completion of a geometrical plan, and that globally planned movements, once started, must run to completion, providing evidence for the definition of a motion primitive as an unstoppable motion element.
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Affiliation(s)
- Ronen Sosnik
- Faculty of Electrical, Electronics and Communication Engineering, Holon Institute of Technology, Holon, Israel; and
| | - Eliyahu Chaim
- Faculty of Electrical, Electronics and Communication Engineering, Holon Institute of Technology, Holon, Israel; and
| | - Tamar Flash
- Department of Applied Math and Computer Science, Weizmann Institute of Science, Rehovot, Israel
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Pezzulo G, Donnarumma F, Iodice P, Prevete R, Dindo H. The role of synergies within generative models of action execution and recognition: a computational perspective: comment on "Grasping synergies: a motor-control approach to the mirror neuron mechanism" by A. D'Ausilio et al. Phys Life Rev 2015; 12:114-7. [PMID: 25659528 DOI: 10.1016/j.plrev.2015.01.021] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2015] [Accepted: 01/13/2015] [Indexed: 11/27/2022]
Affiliation(s)
- Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy.
| | - Francesco Donnarumma
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
| | - Pierpaolo Iodice
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy
| | - Roberto Prevete
- Dipartimento di Ingegneria Elettrica e delle Tecnologie dell'Informazione (DIETI), Università di Napoli Federico II, Naples, Italy
| | - Haris Dindo
- Computer Science Engineering, University of Palermo, Palermo, Italy
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Kurtzer IL. Long-latency reflexes account for limb biomechanics through several supraspinal pathways. Front Integr Neurosci 2015; 8:99. [PMID: 25688187 PMCID: PMC4310276 DOI: 10.3389/fnint.2014.00099] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2014] [Accepted: 12/21/2014] [Indexed: 12/01/2022] Open
Abstract
Accurate control of body posture is enforced by a multitude of corrective actions operating over a range of time scales. The earliest correction is the short-latency reflex (SLR) which occurs between 20–45 ms following a sudden displacement of the limb and is generated entirely by spinal circuits. In contrast, voluntary reactions are generated by a highly distributed network but at a significantly longer delay after stimulus onset (greater than 100 ms). Between these two epochs is the long-latency reflex (LLR) (around 50–100 ms) which acts more rapidly than voluntary reactions but shares some supraspinal pathways and functional capabilities. In particular, the LLR accounts for the arm’s biomechanical properties rather than only responding to local muscle stretch like the SLR. This paper will review how the LLR accounts for the arm’s biomechanical properties and the supraspinal pathways supporting this ability. Relevant experimental paradigms include clinical studies, non-invasive brain stimulation, neural recordings in monkeys, and human behavioral studies. The sum of this effort indicates that primary motor cortex and reticular formation (RF) contribute to the LLR either by generating or scaling its structured response appropriate for the arm’s biomechanics whereas the cerebellum scales the magnitude of the feedback response. Additional putative pathways are discussed as well as potential research lines.
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Affiliation(s)
- Isaac L Kurtzer
- Department of Biomedical Sciences, New York Institute of Technology - College of Osteopathic Medicine Old Westbury, NY, USA
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43
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Volitional walking via upper limb muscle-controlled stimulation of the lumbar locomotor center in man. J Neurosci 2014; 34:11131-42. [PMID: 25122909 DOI: 10.1523/jneurosci.4674-13.2014] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Gait disturbance in individuals with spinal cord lesion is attributed to the interruption of descending pathways to the spinal locomotor center, whereas neural circuits below and above the lesion maintain their functional capability. An artificial neural connection (ANC), which bridges supraspinal centers and locomotor networks in the lumbar spinal cord beyond the lesion site, may restore the functional impairment. To achieve an ANC that sends descending voluntary commands to the lumbar locomotor center and bypasses the thoracic spinal cord, upper limb muscle activity was converted to magnetic stimuli delivered noninvasively over the lumbar vertebra. Healthy participants were able to initiate and terminate walking-like behavior and to control the step cycle through an ANC controlled by volitional upper limb muscle activity. The walking-like behavior stopped just after the ANC was disconnected from the participants even when the participant continued to swing arms. Furthermore, additional simultaneous peripheral electrical stimulation to the foot via the ANC enhanced this walking-like behavior. Kinematics of the induced behaviors were identical to those observed in voluntary walking. These results demonstrate that the ANC induces volitionally controlled, walking-like behavior of the legs. This paradigm may be able to compensate for the dysfunction of descending pathways by sending commands to the preserved locomotor center at the lumbar spinal cord and may enable individuals with paraplegia to regain volitionally controlled walking.
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Huang FC, Patton JL. Individual patterns of motor deficits evident in movement distribution analysis. IEEE Int Conf Rehabil Robot 2014; 2013:6650430. [PMID: 24187248 DOI: 10.1109/icorr.2013.6650430] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Recent studies in rehabilitation have shown potential benefits of patient-initiated exploratory practice. Such findings, however, lead to new challenges in how to quantify and interpret movement patterns. We posit that changes in coordination are most evident in statistical distributions of movements. In a test on 10 chronic stroke subjects practicing for 3 days, we found that inter-quartile range of motion did not show improvement. However, a multivariate Gaussians analysis required more complexity at the end of training. Beyond simply characterizing movement, linear discriminant classification of each patient's movement distribution also identified that each patient's motor deficit left a unique signature. The greatest distinctions were observed in the space of accelerations (rather than position or velocity). These results suggest that unique deficits are best detected with such a distribution analysis, and also point to the need for customized interventions that consider such patient-specific motor deficits.
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Abstract
SUMMARYThe issue of the operation method for dual-arm rescue construction machinery is investigated in this paper. To increase its operational efficiency and to save more time at rescue sites, some operating strategies of the human arm are employed to design a novel operation method for construction machinery. On the basis of that, a novel and anthropomorphic task-motion planning and performing framework for rescue construction machinery is established. Firstly, the main tasks construction machinery encounter are summarized, and then, these tasks are decomposed to several manipulation and movement sequences. Finally, several frequently used movements, which consist of some basic movement elements, are designed to be intuitive movement primitives coordinating related movement elements simultaneously to improve the operational efficiency, which forms a novel operation method for rescue construction machinery. Additionally, in order to avoid the potential collision between the dual arms, a self-collision avoidance surveillance method is proposed to guarantee the safety of the novel operation method. An application case is presented to introduce the proposed method specifically, and a typical simulation of a dual-arm grip-and-cut task is carried out to verify the feasibility and effectiveness of the framework.
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Moore JD, Kleinfeld D, Wang F. How the brainstem controls orofacial behaviors comprised of rhythmic actions. Trends Neurosci 2014; 37:370-80. [PMID: 24890196 DOI: 10.1016/j.tins.2014.05.001] [Citation(s) in RCA: 121] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2013] [Revised: 04/29/2014] [Accepted: 05/02/2014] [Indexed: 01/23/2023]
Abstract
Mammals perform a multitude of well-coordinated orofacial behaviors such as breathing, sniffing, chewing, licking, swallowing, vocalizing, and in rodents, whisking. The coordination of these actions must occur without fault to prevent fatal blockages of the airway. Deciphering the neuronal circuitry that controls even a single action requires understanding the integration of sensory feedback and executive commands. A far greater challenge is to understand the coordination of multiple actions. Here, we focus on brainstem circuits that drive rhythmic orofacial actions. We discuss three neural computational mechanisms that may enable circuits for different actions to operate without interfering with each other. We conclude with proposed experimental programs for delineating the neural control principles that have evolved to coordinate orofacial behaviors.
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Affiliation(s)
- Jeffrey D Moore
- Graduate Program in Neurosciences, UC San Diego, La Jolla, CA 92093, USA; Department of Physics, UC San Diego, La Jolla, CA 92093, USA.
| | - David Kleinfeld
- Graduate Program in Neurosciences, UC San Diego, La Jolla, CA 92093, USA; Department of Physics, UC San Diego, La Jolla, CA 92093, USA; Section on Neurobiology, UC San Diego, La Jolla, CA 92093, USA
| | - Fan Wang
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27710, USA.
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Vato A, Szymanski FD, Semprini M, Mussa-Ivaldi FA, Panzeri S. A bidirectional brain-machine interface algorithm that approximates arbitrary force-fields. PLoS One 2014; 9:e91677. [PMID: 24626393 PMCID: PMC3953591 DOI: 10.1371/journal.pone.0091677] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2013] [Accepted: 02/14/2014] [Indexed: 11/19/2022] Open
Abstract
We examine bidirectional brain-machine interfaces that control external devices in a closed loop by decoding motor cortical activity to command the device and by encoding the state of the device by delivering electrical stimuli to sensory areas. Although it is possible to design this artificial sensory-motor interaction while maintaining two independent channels of communication, here we propose a rule that closes the loop between flows of sensory and motor information in a way that approximates a desired dynamical policy expressed as a field of forces acting upon the controlled external device. We previously developed a first implementation of this approach based on linear decoding of neural activity recorded from the motor cortex into a set of forces (a force field) applied to a point mass, and on encoding of position of the point mass into patterns of electrical stimuli delivered to somatosensory areas. However, this previous algorithm had the limitation that it only worked in situations when the position-to-force map to be implemented is invertible. Here we overcome this limitation by developing a new non-linear form of the bidirectional interface that can approximate a virtually unlimited family of continuous fields. The new algorithm bases both the encoding of position information and the decoding of motor cortical activity on an explicit map between spike trains and the state space of the device computed with Multi-Dimensional-Scaling. We present a detailed computational analysis of the performance of the interface and a validation of its robustness by using synthetic neural responses in a simulated sensory-motor loop.
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Affiliation(s)
- Alessandro Vato
- Department of Robotics, Brain and Cognitive Sciences, Istituto Italiano di Tecnologia, Genova, Italy
| | - Francois D. Szymanski
- Department of Robotics, Brain and Cognitive Sciences, Istituto Italiano di Tecnologia, Genova, Italy
| | - Marianna Semprini
- Department of Robotics, Brain and Cognitive Sciences, Istituto Italiano di Tecnologia, Genova, Italy
| | - Ferdinando A. Mussa-Ivaldi
- Department of Physiology, Northwestern University, Chicago, Illinois, United States of America
- Department of Biomedical Engineering, Northwestern University, Evanston, Illinois, United States of America
- Sensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, Illinois, United States of America
| | - Stefano Panzeri
- Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, United Kingdom
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Abstract
This article reviews the brain structures and neural circuitry underlying the motor system as it pertains to endurance exercise. Some obvious phenomena that occur during endurance racing events that need to be explained neurophysiologically are variable pacing strategies, the end spurt, motivation and the rating of perceived exertion. Understanding the above phenomena physiologically is problematic due to the sheer complexity of obtaining real-time brain measurements during exercise. In those rare instances where brain measurements have been made during exercise, the measurements have usually been limited to the sensory and motor cortices; or the exercise itself was limited to small muscle groups. Without discounting the crucial importance of the primary motor cortex in the execution of voluntary movement, it is surprising that very few exercise studies pay any attention to the complex and dynamic organization of motor action in relation to the subcortical nuclei, given that they are essential for the execution of normal movement patterns. In addition, the findings from laboratory-based exercise performance trials are hampered by the absence of objective measures of the motivational state of subjects. In this review we propose that some of the above phenomena may be explained by distinguishing between voluntary, vigorous and urgent motor behaviours during exercise, given that different CNS structures and neurotransmitters are involved in the execution of these different motor behaviours.
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Waegeman T, Hermans M, Schrauwen B. MACOP modular architecture with control primitives. Front Comput Neurosci 2013; 7:99. [PMID: 23888140 PMCID: PMC3719035 DOI: 10.3389/fncom.2013.00099] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2013] [Accepted: 07/03/2013] [Indexed: 11/30/2022] Open
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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Michel GF, Babik I, Nelson EL, Campbell JM, Marcinowski EC. How the development of handedness could contribute to the development of language. Dev Psychobiol 2013; 55:608-20. [PMID: 23754687 DOI: 10.1002/dev.21121] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2012] [Accepted: 03/25/2013] [Indexed: 11/10/2022]
Abstract
We propose a developmental process which may link the development of handedness with the development of hemispheric specialization for speech processing. Using Arbib's proposed sequence of sensorimotor development of manual skills and gestures (that he considers to be the basis of speech gestures and proto-language), we show how the development of hand-use preferences in proto-reaching skills concatenate into object acquisition skills and eventually into role-differentiated bimanual manipulation skills (that reflect interhemispheric communication and coordination). These latter sensorimotor skills might facilitate the development of speech processing via their influence on the development of tool-using and object management abilities.
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Affiliation(s)
- George F Michel
- Psychology Department, University of North Carolina-Greensboro, Greensboro, NC, USA.
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