I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

Principles of Neural Science

Dynamic simulations of movement allow one to study neuromuscular coordination, analyze athletic performance, and estimate internal loading of the musculoskeletal system. Simulations can also be used to identify the sources of pathological movement and establish a scientific basis for treatment planning. We have developed a freely available, open-source software system (OpenSim) that lets users develop models of musculoskeletal structures and create dynamic simulations of a wide variety of movements. We are using this system to simulate the dynamics of individuals with pathological gait and to explore the biomechanical effects of treatments. OpenSim provides a platform on which the biomechanics community can build a library of simulations that can be exchanged, tested, analyzed, and improved through a multi-institutional collaboration. Developing software that enables a concerted effort from many investigators poses technical and sociological challenges. Meeting those challenges will accelerate the discovery of principles that govern movement control and improve treatments for individuals with movement pathologies.

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OpenSim: Open-Source Software to Create and Analyze Dynamic Simulations of Movement

BackgroundFemale athletes participating in high-risk sports suffer anterior cruciate ligament injury at a 4- to 6-fold greater rate than do male athletes.HypothesisPrescreened female athletes with subsequent anterior cruciate ligament injury will demonstrate decreased neuromuscular control and increased valgus joint loading, predicting anterior cruciate ligament injury risk.Study DesignCohort study; Level of evidence, 2.MethodsThere were 205 female athletes in the high-risk sports of soccer, basketball, and volleyball prospectively measured for neuromuscular control using 3-dimensional kinematics (joint angles) and joint loads using kinetics (joint moments) during a jump-landing task. Analysis of variance as well as linear and logistic regression were used to isolate predictors of risk in athletes who subsequently ruptured the anterior cruciate ligament.ResultsNine athletes had a confirmed anterior cruciate ligament rupture; these 9 had significantly different knee posture and loading compared to the 196 ...

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Biomechanical Measures of Neuromuscular Control and Valgus Loading of the Knee Predict Anterior Cruciate Ligament Injury Risk in Female Athletes A Prospective Study

Osteoarthritis is the most common form of arthritis, affecting millions of people in the United States. It is a complex disease whose etiology bridges biomechanics and biochemistry. Evidence is growing for the role of systemic factors (such as genetics, dietary intake, estrogen use, and bone density) and of local biomechanical factors (such as muscle weakness, obesity, and joint laxity). These risk factors are particularly important in weightbearing joints, and modifying them may present opportunities for prevention of osteoarthritis-related pain and disability. Major advances in management to reduce pain and disability are yielding a panoply of available treatments ranging from nutriceuticals to chondrocyte transplantation, new oral anti-inflammatory medications, and health education. This article is part 1 of a two-part summary of a National Institutes of Health conference. The conference brought together experts on osteoarthritis from diverse backgrounds and provided a multidisciplinary and comprehensive summary of recent advances in the prevention of osteoarthritis onset, progression, and disability. Part 1 focuses on a new understanding of what osteoarthritis is and on risk factors that predispose to disease occurrence. It concludes with a discussion of the impact of osteoarthritis on disability. Ann Intern Med. 2000;133:635-646. www.annals.org For author affiliations and current addresses, see end of text.

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Osteoarthritis: New Insights Part 1: The Disease and Its Risk Factors

Osteoarthritis (OA) is the most common form of arthritis and a major cause of pain and disability in older adults (1) Often OA is referred to as degenerative joint disease “(DJD)” This is a misnomer because OA is not simply a process of wear and tear but rather abnormal remodeling of joint tissues driven by a host of inflammatory mediators within the affected joint The most common risk factors for OA include age, gender, prior joint injury, obesity, genetic predisposition, and mechanical factors, including malalignment and abnormal joint shape (2, 3) Despite the multifactorial nature of OA, the pathological changes seen in osteoarthritic joints have common features that affect the entire joint structure resulting in pain, deformity and loss of function

The pathologic changes seen in OA joints (Figures 1 and ​and2)2) include degradation of the articular cartilage, thickening of the subchondral bone, osteophyte formation, variable degrees of synovial inflammation, degeneration of ligaments and, in the knee, the menisci, and hypertrophy of the joint capsule There can also be changes in periarticular muscles, nerves, bursa, and local fat pads that may contribute to OA or the symptoms of OA The findings of pathological changes in all of the joint tissues are the impetus for considering OA as a disease of the joint as an organ resulting in “joint failure” In this review, we will summarize the key features of OA in the various joint tissues affected and provide an overview of the basic mechanisms currently thought to contribute to the pathological changes seen in these tissues






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Figure 1


Sagittal inversion recovery (A–C) and coronal fast spin echo (D–F) images illustrating the magnetic resonance imaging findings of osteoarthritis (A) reactive synovitis (thick white arrow), (B) subchondral cyst formation (white arrow), (C) bone marrow edema (thin white arrows), (D) partial thickness cartilage wear (thick black arrow), (E–F) full thickness cartilage wear (thin black arrows), subchondral sclerosis (arrowhead) and marginal osteophyte formation (double arrow) Image courtesy of Drs Hollis Potter and Catherine Hayter, Hospital for Special Surgery, New York, NY

https://onlinelibrary.wiley.com/doi/pdf/10.1002/art.34453

Osteoarthritis: A Disease of the Joint as an Organ

This paper provides an overview of forward dynamic neuromusculoskeletal modeling The aim of such models is to estimate or predict muscle forces, joint moments, and/or joint kinematics from neural signals This is a four-step process In the first step, muscle activation dynamics govern the transformation from the neural signal to a measure of muscle activation—a time varying parameter between 0 and 1 In the second step, muscle contraction dynamics characterize how muscle activations are transformed into muscle forces The third step requires a model of the musculoskeletal geometry to transform muscle forces to joint moments Finally, the equations of motion allow joint moments to be transformed into joint movements Each step involves complex nonlinear relationships The focus of this paper is on the details involved in the first two steps, since these are the most challenging to the biomechanician The global process is then explained through applications to the study of predicting isometric elbow moments and dynamic knee kinetics

Neuromusculoskeletal Modeling: Estimation of Muscle Forces and Joint Moments and Movements From Measurements of Neural Command

To study abnormal spatial patterns of muscle activation in hemiparetic stroke, we compared EMG activity in paretic and contralateral elbow and shoulder muscles of 10 hemiparetic subjects during 1.5- s voluntary isometric contractions, against five to eight different loads. Isometric forces were generated in eight directions, referenced to a plane orthogonal to the long axis of the forearm, and were recorded by a three degrees of freedom load cell, mounted at the wrist. Surface and intramuscular EMGs of six elbow and six shoulder muscles were recorded from both impaired and contralateral upper extremities of each subject. The spatial characteristics of EMG activation of individual muscles were summarized using two measures. The first, called the ‘net resultant EMG vector’ is a new measure which calculated the vector sum of EMG magnitudes for each of the eight directions, and the second, index of EMG focus, is a measure of the range of EMG activation recorded for each load level. Use of these measures permitted us to describe spatial EMG characteristics quantitatively, which has not been done previously. We observed consistent and statistically significant shifts in the resultant EMG vector directions in the impaired limb, especially in shoulder and other proximal muscles. Significant increases in the angular range of EMG activity were also identified and were most evident at the elbow. Correlation analysis techniques were used to assess the degree of coactivation of different muscle pairs. There were consistent EMG coactivation patterns observed across all subjects (both normal and hemiparetic). However, in spastic-paretic limbs, additional novel coactivational relationships were also recorded, especially between elbow flexors/shoulder abductors and elbow extensors/shoulder adductors. These novel coactivation patterns represent a reduction in the number of possible muscle combinations, or in the number of possible ‘synergies’ in the paretic limb of the stroke subject. This reduction in number of ‘synergies’ could result from a loss of descending command options; from an increased reliance on residual, descending brainstem pathways (such as the reticulospinal and vestibulospinal projections); from changes in spinal interneuronal excitability; or from a combination of several of these factors. The relative merits of these hypotheses are addressed.

Abnormal Muscle Coactivation Patterns During Isometric Torque Generation at the Elbow and Shoulder in Hemiparetic Subjects

Some individuals can stabilize their knees following anterior cruciate ligament rupture even during activities involving cutting and pivoting (copers), others have instability with daily activities (non-copers). Movement and muscle activation patterns of 11 copers, ten non-copers and ten uninjured subjects were studied during walking and jogging. Results indicate that distinct gait adaptations appeared primarily in the non-copers. Copers used joint ranges of motion, moments and muscle activation patterns similar to uninjured subjects. Non-copers reduced their knee motion, and external knee flexion moments that correlated well with quadriceps strength. Non-copers also achieved peak hamstring activity later in the weight acceptance phase and used a strategy involving more generalized co-contraction. Both copers and non-copers had high levels of quadriceps femoris muscle activity. The reduced knee moment in the involved limbs of the non-copers did not represent "quadriceps avoidance" but rather represented a strategy of general co-contraction with a greater relative contribution from the hamstring muscles.

Dynamic stability in the anterior cruciate ligament deficient knee.

Variation of muscle moment arms with elbow and forearm position.

We studied the patterns of EMG activity in elbow muscles in three normal human subjects. The myoelectrical activity of 7-10 muscles that act across the human elbow joint was simultaneously recorded with intramuscular electrodes during isometric joint torques exerted over a range of directions. These directions included flexion, extension, varus (internal humeral rotation), valgus (external humeral rotation), and several intermediate directions. The forces developed at the wrist covered a range of 360 degrees, all orthogonal to the long axis of the forearm. The levels of EMG activity were observed to increase with increasing joint torque in an approximately linear manner. All muscles were active for ranges less than 360 degrees and most were active for less than 180 degrees. The EMG activity was observed to vary in a systematic manner with changes in torque direction and, when examined over the full angular range at a variety of torque levels, is simply scaled with increasing torque magnitude. There were no torque directions or torque magnitudes for which a single muscle was observed to be active alone. In all cases, joint torque appeared to be produced by a combination of muscles. The direction for which the EMG of a muscle reached a maximum value was observed to correspond to the direction of greatest mechanical advantage as predicted by a simple mechanical model of the elbow and relevant muscles. Muscles were relatively inactive during varus torques. This implies that the muscles were not acting to stabilize the joint in this direction and could have been allowing ligaments to carry the load. Plots of EMG activity in one muscle against EMG activity in another demonstrate some instances of pure synergies, but patterns of coactivation for most muscles are more complicated and vary with torque direction. The complexity of these patterns raises the possibility that synergies are determined by the task and may have no independent existence. Activity in two heads of triceps brachii (medial head--a single-joint muscle and long head--a two-joint muscle) covaried closely for a range of torque magnitudes and directions, though shoulder torque and hence the forces experienced by the long head of the triceps undoubtedly varied. The similarity of activation patterns indicates that elbow torque was the principal determining factor. The origins of muscle synergies are discussed. It is suggested that they are best understood on the basis of a model which encodes limb torque in premotor neurons.(ABSTRACT TRUNCATED AT 400 WORDS)

Thomas S. Buchanan

Papers

Neuromusculoskeletal Modeling: Estimation of Muscle Forces and Joint Moments and Movements From Measurements of Neural Command

Abnormal Muscle Coactivation Patterns During Isometric Torque Generation at the Elbow and Shoulder in Hemiparetic Subjects

Dynamic stability in the anterior cruciate ligament deficient knee.

Variation of muscle moment arms with elbow and forearm position.

Characteristics of synergic relations during isometric contractions of human elbow muscles