Damage explains function in spiking neural networks representing central pattern generator.

Complex biological systems have evolved to control movement dynamics despite noisy and unpredictable inputs and processing delays that necessitate forward predictions. The staple example in vertebrates is the locomotor control emerging from interactions between multiple systems-from passive dynamics of inverted pendulum governing body motion to coupled neural oscillators that integrate predictive forward and sensory feedback signals. These neural dynamic computations are expressed in the rhythmogenic spinal network known as the central pattern generator (CPG).

Muscle anatomy is reflected in the spatial organization of the spinal motoneuron pools.

Neural circuits embed limb dynamics for motor control and sensorimotor integration. The somatotopic organization of motoneuron pools in the spinal cord may support these computations. Here, we tested if the spatial organization of motoneurons is related to the musculoskeletal anatomy.

Artificial physics engine for real-time inverse dynamics of arm and hand movement.

Simulating human body dynamics requires detailed and accurate mathematical models. When solved inversely, these models provide a comprehensive description of force generation that considers subject morphology and can be applied to control real-time assistive technology, for example, orthosis or muscle/nerve stimulation. Yet, model complexity hinders the speed of its computations and may require approximations as a mitigation strategy.

Does joint impedance improve dynamic leg simulations with explicit and implicit solvers?

The nervous system predicts and executes complex motion of body segments actuated by the coordinated action of muscles. When a stroke or other traumatic injury disrupts neural processing, the impeded behavior has not only kinematic but also kinetic attributes that require interpretation. Biomechanical models could allow medical specialists to observe these dynamic variables and instantaneously diagnose mobility issues that may otherwise remain unnoticed.

Surface Electromyography Provides Neuromuscular Insights for Skill Acquisition in Microgravity.

The human motor system has evolved to perform efficient motor control in Earth's gravity. Altered gravity environments, such as microgravity and hypergravity, pose unique challenges for performing fine motor tasks with object manipulation. Altered gravity has been shown to reduce the speed and accuracy of complex manual tasks.

Does joint impedance improve dynamic leg simulations with explicit and implicit solvers?

The nervous system predicts and executes complex motion of body segments actuated by the coordinated action of muscles. When a stroke or other traumatic injury disrupts neural processing, the impeded behavior has not only kinematic but also kinetic attributes that require interpretation. Biomechanical models could allow medical specialists to observe these dynamic variables and instantaneously diagnose mobility issues that may otherwise remain unnoticed.

Young adults perceive small disturbances to their walking balance even when distracted.

Background: The ability to perceive disturbances to ongoing locomotion (e.g., slips and trips) may play an important role in walking balance control.

Quantifying Performance in Robotic Surgery Training Using Muscle-Based Activity Metrics.

Training to perform robotic surgery is time-consuming with uncertain metrics of the level of achieved skill. We tested the feasibility of using muscle co-contraction as a metric to quantify robotic surgical skill in a virtual simulation environment. We recruited six volunteers with varying skill levels in robotic surgery.

Solving musculoskeletal biomechanics with machine learning.

Deep learning is a relatively new computational technique for the description of the musculoskeletal dynamics. The experimental relationships of muscle geometry in different postures are the high-dimensional spatial transformations that can be approximated by relatively simple functions, which opens the opportunity for machine learning (ML) applications. In this study, we challenged general ML algorithms with the problem of approximating the posture-dependent moment arm and muscle length relationships of the human arm and hand muscles.

Compensatory Strategies Due to Knee Flexion Constraint during Gait of Non-Disabled Adults.

Constraining knee flexion of non-disabled individuals could further our understanding regarding the importance of knee joint during gait, which is a common disturbance in individuals with gait impairment. In this study we investigated whether a mechanical constraint of knee flexion in non-disabled adults would lead to compensatory strategies. Eleven non-disabled male adults walked without and with an orthosis that permitted full extension and limited knee flexion up to either 45° or 30°.

A segmented forearm model of hand pronation-supination approximates joint moments for real time applications.

Musculoskeletal modeling is a new computational tool to reverse engineer human control systems, which require efficient algorithms running in real-time. Human hand pronation-supination movement is accomplished by movement of the radius and ulna bones relative to each other via the complex proximal and distal radioulnar joints, each with multiple degrees of freedom (DOFs). Here, we report two simplified models of this complex kinematic transformation implemented as a part of a 20 DOF model of the hand and forearm.

Approximating complex musculoskeletal biomechanics using multidimensional autogenerating polynomials.

Computational models of the musculoskeletal system are scientific tools used to study human movement, quantify the effects of injury and disease, plan surgical interventions, or control realistic high-dimensional articulated prosthetic limbs. If the models are sufficiently accurate, they may embed complex relationships within the sensorimotor system. These potential benefits are limited by the challenge of implementing fast and accurate musculoskeletal computations.

Computational evidence for nonlinear feedforward modulation of fusimotor drive to antagonistic co-contracting muscles.

The sensorimotor integration during unconstrained reaching movements in the presence of variable environmental forces remains poorly understood. The objective of this study was to quantify how much the primary afferent activity of muscle spindles can contribute to shaping muscle coactivation patterns during reaching movements with complex dynamics. To achieve this objective, we designed a virtual reality task that guided healthy human participants through a set of planar reaching movements with controlled kinematic and dynamic conditions that were accompanied by variable muscle co-contraction.

Analytical CPG model driven by limb velocity input generates accurate temporal locomotor dynamics.

The ability of vertebrates to generate rhythm within their spinal neural networks is essential for walking, running, and other rhythmic behaviors. The central pattern generator (CPG) network responsible for these behaviors is well-characterized with experimental and theoretical studies, and it can be formulated as a nonlinear dynamical system. The underlying mechanism responsible for locomotor behavior can be expressed as the process of leaky integration with resetting states generating appropriate phases for changing body velocity.

Correction: Biomechanical Constraints Underlying Motor Primitives Derived from the Musculoskeletal Anatomy of the Human Arm.

[This corrects the article DOI: 10.1371/journal.pone.

A novel method of identifying motor primitives using wavelet decomposition.

This study reports a new technique for extracting muscle synergies using continuous wavelet transform. The method allows to quantify coincident activation of muscle groups caused by the physiological processes of fixed duration, thus enabling the extraction of wavelet modules of arbitrary groups of muscles. Hierarchical clustering and identification of the repeating wavelet modules across subjects and across movements, was used to identify consistent muscle synergies.

Model of a bilateral Brown-type central pattern generator for symmetric and asymmetric locomotion.

The coordinated activity of muscles is produced in part by spinal rhythmogenic neural circuits, termed central pattern generators (CPGs). A classical CPG model is a system of coupled oscillators that transform locomotor drive into coordinated and gait-specific patterns of muscle recruitment. The network properties of this conceptual model can be simulated by a system of ordinary differential equations with a physiologically inspired coupling locus of interactions capturing the timing relationship for bilateral coordination of limbs in locomotion.

Biomechanical Constraints Underlying Motor Primitives Derived from the Musculoskeletal Anatomy of the Human Arm.

Neural control of movement can only be realized though the interaction between the mechanical properties of the limb and the environment. Thus, a fundamental question is whether anatomy has evolved to simplify neural control by shaping these interactions in a beneficial way. This inductive data-driven study analyzed the patterns of muscle actions across multiple joints using the musculoskeletal model of the human upper limb.

Asymmetric Walkway: A Novel Behavioral Assay for Studying Asymmetric Locomotion.

Behavioral assays are commonly used for the assessment of sensorimotor impairment in the central nervous system (CNS). The most sophisticated methods for quantifying locomotor deficits in rodents is to measure minute disturbances of unconstrained gait overground (e.g.

Similar Motor Cortical Control Mechanisms for Precise Limb Control during Reaching and Locomotion.

Throughout the course of evolution there has been a parallel development of the complexity and flexibility of the nervous system and the skeletomuscular system that it controls. This development is particularly evident for the cerebral cortical areas and the transformation of the use of the upper limbs from a purely locomotor function to one including, or restricted to, reaching and grasping. This study addresses the issue of whether the control of reaching has involved the development of new cortical circuits or whether the same neurons are used to control both locomotion and reaching.

Automated assessment of upper extremity movement impairment due to stroke.

Current diagnosis and treatment of movement impairment post-stroke is based on the subjective assessment of select movements by a trained clinical specialist. However, modern low-cost motion capture technology allows for the development of automated quantitative assessment of motor impairment. Such outcome measures are crucial for advancing post-stroke treatment methods.

Chapter 10--a hierarchical perspective on rhythm generation for locomotor control.

The control of locomotion is a complex dynamic task solved with apparent ease by our body. How this is accomplished still remains an intriguing mystery. This chapter first describes classical and recent findings relevant to understanding the complexity of the question on the verge of several fields of neurophysiology, biomechanics, and computational neuroscience.

Sequential activation of motor cortical neurons contributes to intralimb coordination during reaching in the cat by modulating muscle synergies.

We examined the contribution of the motor cortex to the control of intralimb coordination during reaching in the standing cat. We recorded the activity of 151 pyramidal tract neurons (PTNs) in the forelimb representation of three cats during a task in which the cat reached forward from a standing position to press a lever. We simultaneously recorded the activity of muscles in the contralateral forelimb acting around each of the major joints.

A motor cortical contribution to the anticipatory postural adjustments that precede reaching in the cat.

We tested the hypothesis that pyramidal tract neurons (PTNs) in the motor cortex contribute to the anticipatory postural adjustments (APAs) that precede the onset of a reach in the standing cat. We recorded the discharge activity of 151 PTNs in area 4 of the pericruciate cortex during reaches of both the contralateral and the ipsilateral limbs in an instructed delay task. A total of 70/151 PTNs were identified as showing an initial short-latency period of discharge following the Go signal.