scholarly journals A Multi-Systems Approach to Human Movement after ACL Reconstruction: The Nervous System

2022 ◽  
Author(s):  
Meredith Chaput ◽  
Brandon M Ness ◽  
Kathryn Lucas ◽  
Kory J Zimney
Keyword(s):  
Nervous System ◽  
Acl Reconstruction ◽  
Systems Approach ◽  
Human Movement

scholarly journals A Multi-Systems Approach to Human Movement after ACL Reconstruction: The Musculoskeletal System

2021 ◽  
Author(s):  
Daniel Larson ◽  
Vien Vu ◽  
Brandon M Ness ◽  
Elizabeth Wellsandt ◽  
Scot Morrison
Keyword(s):  
Acl Reconstruction ◽  
Musculoskeletal System ◽  
Systems Approach ◽  
Human Movement

scholarly journals Trial-by-Trial Adaptation of Movements during Mental Practice under Force Field

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Muhammad Nabeel Anwar ◽  
Salman Hameed Khan
Keyword(s):  
Nervous System ◽  
Force Field ◽  
Motor Imagery ◽  
Internal Model ◽  
Human Movement ◽  
Mental Practice ◽  
Higher Learning ◽  
Reaching Movements ◽  
Adaptive Compensation ◽  
Human Nervous System

Human nervous system tries to minimize the effect of any external perturbing force by bringing modifications in the internal model. These modifications affect the subsequent motor commands generated by the nervous system. Adaptive compensation along with the appropriate modifications of internal model helps in reducing human movement errors. In the current study, we studied how motor imagery influences trial-to-trial learning in a robot-based adaptation task. Two groups of subjects performed reaching movements with or without motor imagery in a velocity-dependent force field. The results show that reaching movements performed with motor imagery have relatively a more focused generalization pattern and a higher learning rate in training direction.

scholarly journals Overview of the modeling of complex biological systems and its role in neurosurgery

2021 ◽  
Vol 12 ◽  
pp. 433
Author(s):  
Zaid Aljuboori
Keyword(s):  
Nervous System ◽  
Complex Systems ◽  
Biomedical Research ◽  
Systems Approach ◽  
Biological Systems ◽  
Self Organization ◽  
Human Biology ◽  
Linear Approach ◽  
Human Nervous System

Biological systems are complex with distinct characteristics such as nonlinearity, adaptability, and self-organization. Biomedical research has helped in advancing our understanding of certain components the human biology but failed to illustrate the behavior of the biological systems within. This failure can be attributed to the use of the linear approach, which reduces the system to its components then study each component in isolation. This approach assumes that the behavior of complex systems is the result of the sum of the function of its components. The complex systems approach requires the identification of the components of the system and their interactions with each other and with the environment. Within neurosurgery, this approach has the potential to advance our understanding of the human nervous system and its subsystems.

The trajectory of human wrist movements

1988 ◽  
Vol 59 (6) ◽  
pp. 1814-1830 ◽  
Author(s):  
R. B. Stein ◽  
F. W. Cody ◽  
C. Capaday
Keyword(s):  
Nervous System ◽  
Energy Consumption ◽  
Human Movement ◽  
Normal Subjects ◽  
Kinematic Variable ◽  
Wrist Flexion ◽  
Movement Trajectories ◽  
Minimum Jerk ◽  
Inertial Loading ◽  
Third Derivative

1. To determine the form of human movement trajectories and the factors that determine this form, normal subjects performed wrist flexion movements against various elastic, viscous, and inertial loads. The subjects were instructed with visual and auditory feedback to make a movement of prescribed amplitude in a present period of time, but were free to choose any trajectory that fulfilled these constraints. 2. The trajectories were examined critically to determine if they corresponded to those which would minimize the root mean square (RMS) value of some kinematic variable or of energy consumption. The data agreed better with the trajectory that minimized the RMS value of jerk (the third derivative of length) than that of acceleration. However, systematic deviations from the minimum jerk predictions were consistently observed whenever movements were made against elastic and viscous loads. 3. Improved agreement could generally be obtained by assuming that the velocity profile varied according to a normal (Gaussian) curve. We conclude that minimization of jerk is not a general principle used by the nervous system in organizing voluntary movements, although movements may approach the predicted form, particularly under inertial loading conditions. 4. The EMG of the agonist muscles consisted of relatively simple waveforms containing ramplike increases and approximately exponential decays. The form of the movements could often be predicted quite well by using the EMG as an input to a linear second-order model of the muscle plus load. Rather than rigorously minimizing a kinematic variable or energy consumption, the nervous system may generate simple waveforms and adjust the parameters of these waveforms by trial and error until a trajectory is achieved that meets the requirements for a given load.

The Neuromuscular Transform: The Dynamic, Nonlinear Link Between Motor Neuron Firing Patterns and Muscle Contraction in Rhythmic Behaviors

2000 ◽  
Vol 83 (1) ◽  
pp. 207-231 ◽  
Author(s):  
Vladimir Brezina ◽  
Irina V. Orekhova ◽  
Klaudiusz R. Weiss
Keyword(s):  
Nervous System ◽  
Motor Neuron ◽  
Muscle Contraction ◽  
Firing Pattern ◽  
Systems Approach ◽  
Muscle Contractions ◽  
Neuron Firing ◽  
Firing Patterns ◽  
Motor Commands ◽  
Rhythmic Behaviors

The nervous system issues motor commands to muscles to generate behavior. All such commands must, however, pass through a filter that we call here the neuromuscular transform (NMT). The NMT transforms patterns of motor neuron firing to muscle contractions. This work is motivated by the fact that the NMT is far from being a straightforward, transparent link between motor neuron and muscle. The NMT is a dynamic, nonlinear, and modifiable filter. Consequently motor neuron firing translates to muscle contraction in a complex way. This complexity must be taken into account by the nervous system when issuing its motor commands, as well as by us when assessing their significance. This is the first of three papers in which we consider the properties and the functional role of the NMT. Physiologically, the motor neuron–muscle link comprises multiple steps of presynaptic and postsynaptic Ca2+ elevation, transmitter release, and activation of the contractile machinery. The NMT formalizes all these into an overall input-output relation between patterns of motor neuron firing and shapes of muscle contractions. We develop here an analytic framework, essentially an elementary dynamical systems approach, with which we can study the global properties of the transformation. We analyze the principles that determine how different firing patterns are transformed to contractions, and different parameters of the former to parameters of the latter. The key properties of the NMT are its nonlinearity and its time dependence, relative to the time scale of the firing pattern. We then discuss issues of neuromuscular prediction, control, and coding. Does the firing pattern contain a code by means of which particular parameters of motor neuron firing control particular parameters of muscle contraction? What information must the motor neuron, and the nervous system generally, have about the periphery to be able to control it effectively? We focus here particularly on cyclical, rhythmic contractions which reveal the principles particularly clearly. Where possible, we illustrate the principles in an experimentally advantageous model system, the accessory radula closer (ARC)–opener neuromuscular system of Aplysia. In the following papers, we use the framework developed here to examine how the properties of the NMT govern functional performance in different rhythmic behaviors that the nervous system may command.

scholarly journals Viewpoint: What the Marine Mollusc Aplysia Can Tell the Neurologist About Behavioral Neurophysiology

1981 ◽  
Vol 8 (4) ◽  
pp. 275-280 ◽  
Author(s):  
Peter Ruben ◽  
Jeff Goldberg ◽  
Jon Edstrom ◽  
Karen Voshart ◽  
Ken Lukowiak
Keyword(s):  
Nervous System ◽  
Behavioral Plasticity ◽  
Systems Approach ◽  
Neural Substrates ◽  
Realistic Model ◽  
Model Systems ◽  
Neural Function ◽  
Experimental Conditions ◽  
Nervous Systems ◽  
Physical And Chemical

Only recently has man begun to regard himself as mundane and not divine. This conceptual liberation has allowed him to ask frank questions concerning the physical and chemical mechanisms which determine or affect his behavior. Unfortunately the answers to these questions have been slow in coming. The reasons for this are two-fold: Basic ethical considerations preclude the experiments necessary to investigate the neural substrates of human behavior in man. Further, man’s behavior and nervous system are both so enormously complex and subtle, it is therefore unlikely that much real fundamental knowledge could be gained from such experiments if performed. It is more expedient to study simple behavior in simpler organisms than man to understand how nervous systems operate in general and, it is hoped, to eventually gain a better understanding of the human in particular. This tactic is known as the “model systems” approach. By discovering the strategies adopted by less complex nervous systems to deal with simple situations one can devise a realistic model of the neural mechanisms that control more complex behavior in more advanced animals.Many animals have served as valuable sources of model systems. Among them the marine gastropod mollusc Aplysia has received considerable attention. In comparison to the human nervous system with approximately 50 billion neurons, the Aplysia nervous system contains relatively few neurons — about 20,000. Furthermore the study of the Aplysia nervous system has several other advantageous characteristics. A number of forms of behavioral plasticity that are found in all higher metazoans including man are also found in the Aplysia. These simple but non-trivial types of behavioral plasticity include habituation, sensitization and associative learning as well as easily defined qualities of neural function which we choose to call “behavioral states”. In addition the nervous system is composed of neurons which are large and, in many cases, easily identified by anatomical and physiological criteria so that the “same” cell can be studied in more than one animal under more than one set of experimental conditions. The cell bodies of the neurons in Aplysia, from which electrical recordings can be fairly easily obtained, are electrically close to their dendrites so that changes in postsynaptic potentials occurring during modifications of behavior can be monitored.

scholarly journals A mechatronic system for studying energy optimization during walking.

2018 ◽  
Author(s):  
Surabhi N Simha ◽  
J. Maxwell Donelan
Keyword(s):  
Nervous System ◽  
System Design ◽  
Human Movement ◽  
Human Walking ◽  
Energetic Cost ◽  
Mechatronic System ◽  
Step Frequency ◽  
Coordination Strategies ◽  
Design Build ◽  
Optimal Coordination

A general principle of human movement is that our nervous system is able to learn optimal coordination strategies. However, how our nervous system performs this optimization is not well understood. Here we design, build, and test a mechatronic system to probe the algorithms underlying optimization of energetic cost in walking. The system applies controlled fore-aft forces to a hip-belt worn by a user, decreasing their energetic cost by pulling forward or increasing it by pulling backward. The system controls the forces, and thus energetic cost, as a function of how the user is moving. In testing, we found that the system can quickly, accurately, and precisely apply target forces within a walking step. We next controlled the forces as a function of the user's step frequency and found that we could predictably reshape their energetic cost landscape. Finally, we tested whether users adapted their walking in response to the new cost landscapes created by our system, and found that users shifted their step frequency towards the new energetic minima. Our system design appears to be effective for reshaping energetic cost landscapes in human walking to study how the nervous system optimizes movement.

scholarly journals A dynamic systems approach to bimanual coordination in stroke: implications for rehabilitation and research

Medicina ◽  
2010 ◽  
Vol 46 (6) ◽  
pp. 374 ◽  
Author(s):  
Rita Sleimen-Malkoun ◽  
Jean-Jacques Temprado ◽  
Eric Berton
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Dynamic Systems ◽  
Bimanual Coordination ◽  
Systems Approach ◽  
Neural Basis ◽  
Impaired Limb ◽  
The Central Nervous System ◽  
The One ◽  
Systems View

During the last 30 years, the dynamic systems approach to coordination patterns contributed to shed new lights on the principles governing interlimb coordination, its dynamics, and its neural basis, predominantly in healthy people. In the present paper, we aim to show how these concepts could provide a theoretical and a methodological framework to address bimanual coordination dysfunction and rehabilitation in stroke patients. Compared to conventional approaches to research and rehabilitation in stroke, the one proposed in this paper is original since it seeks to assess and improve the impaired limb through (and in) coordination tasks. We concretely envisage a number of implications of the “dynamic systems” view to understand the behavioral consequences of intrinsic asymmetries (due to central nervous system injury) on bimanual dynamics in stroke and to identify how to exploit the central nervous system plasticity and self-organizing properties for recovering more adaptive coordinated movements. We conclude that more interest should be accorded to bimanual coordination assessment and rehabilitation in stroke. In this respect, the dynamical systems approach provides interesting insights and valuable tools. Experimental and clinical studies are still needed in order to elaborate fi rm and founded guidelines for therapy.

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