Structure, function, and control of the human musculoskeletal network

Human Posture: Concept Analysis With Roy's Model Using Walker and Avant's Approach

The significance of human posture extends beyond mere body stance to its profound impact on long-term physical well-being. Guided by the Roy adaptation model and Walker and Avant's approach, in this paper the author presents a concept analysis of posture, which resulted in a proposed explanatory theory of postural functional status. By identifying attributes of posture (alignment, adaptation, and awareness), its antecedents (body parts, force of gravity, and musculoskeletal system), and consequences, this concept analysis offers fresh ideas to promote and shape postural future in nursing, wellness, and public health, with an aim to sustain the quality-of-life for individuals of all ages.

Advances in wearable electronics for monitoring human organs: Bridging external and internal health assessments

Devices used for diagnosing disease are often large, expensive, and require operation by trained professionals, which can result in delayed diagnosis and missed opportunities for timely treatment. However, wearable devices are being recognized as a new approach to overcoming these difficulties, as they are small, affordable, and easy to use. Recent advancements in wearable technology have made monitoring information possible from the surface of organs like the skin and eyes, enabling accurate diagnosis of the user's internal status. In this review, we categorize the body's organs into external (e.g., eyes, oral cavity, neck, and skin) and internal (e.g., heart, brain, lung, stomach, and bladder) organ systems and introduce recent developments in the materials and designs of wearable electronics, including electrochemical and electrophysiological sensors applied to each organ system. Further, we explore recent innovations in wearable electronics for monitoring of deep internal organs, such as the heart, brain, and nervous system, using ultrasound, electrical impedance tomography, and temporal interference stimulation. The review also addresses the current challenges in wearable technology and explores future directions to enhance the effectiveness and applicability of these devices in medical diagnostics. This paper establishes a framework for correlating the design and functionality of wearable electronics with the physiological characteristics and requirements of various organ systems.

Alterations of upper-extremity functional muscle networks in chronic stroke survivors

Current clinical assessment tools don't fully capture the genuine neural deficits experienced by chronic stroke survivors and, consequently, they don't fully explain motor function throughout everyday life. Towards addressing this problem, here we aimed to characterise post-stroke alterations in upper-limb control from a novel perspective to the muscle synergy by applying, for the first time, a computational approach that quantifies diverse types of functional muscle interactions (i.e. functionally-similar (redundant), -complementary (synergistic) and -independent (unique)). From single-trials of a simple forward pointing movement, we extracted networks of functionally diverse muscle interactions from chronic stroke survivors and unimpaired controls, identifying shared and group-specific modules across each interaction type (i.e. redundant, synergistic and unique). Reconciling previous studies, we found evidence for both the concurrent preservation of healthy functional modules post-stroke and muscle network structure alterations underpinned by systemic muscle interaction re-weighting and functional reorganisation across all interaction types. Cluster analysis of stroke survivors revealed two distinct patient subgroups from each interaction type that all distinguished less impaired individuals who were able to adopt novel motor patterns different to unimpaired controls from more severely impaired individuals who did not. Our work here provides a nuanced account of post-stroke functional impairment and, in doing so, paves new avenues towards progressing the clinical use case of muscle synergy analysis.

Hypergraph modeling of complex interactions: Applications from human musculoskeletal structures to complex system dynamics

The musculoskeletal network is a complex system of different types of nodes and edges interacting with each other. Although there is a wealth of knowledge about the anatomical components of the human body and the connections between them, the interdependence of these components as a system remains largely unexplored. This study aims to understand the structure of musculoskeletal networks by using hypergraphs as a model of the musculoskeletal system with many-to-many connections. We used both pairwise and hypergraph-based embedding methods to learn the connectivity of muscles. Experiments demonstrated the superiority of the proposed hypergraph-based method over pairwise methods in distinguishing the specific roles of the muscles connecting different body parts.

An inclusive anatomical network analysis of human craniocerebral topology

The human brain's complex morphology is spatially constrained by numerous intrinsic and extrinsic physical interactions. Spatial constraints help to identify the source of morphological variability and can be investigated by employing anatomical network analysis. Here, a model of human craniocerebral topology is presented, based on the bony elements of the skull at birth and a previously designed model of the brain. The goal was to investigate the topological components fundamental to the craniocerebral geometric balance, to identify underlying phenotypic patterns of spatial arrangement, and to understand how these patterns might have influenced the evolution of human brain morphology. Analysis of the craniocerebral network model revealed that the combined structure of the body and lesser wings of the sphenoid bone, the parahippocampal gyrus, and the parietal and ethmoid bones are susceptible to sustain and apply major spatial constraints that are likely to limit or channel their morphological evolution. The results also showcase a high level of global integration and efficient diffusion of biomechanical forces across the craniocerebral system, a fundamental aspect of morphological variability in terms of plasticity. Finally, community detection in the craniocerebral system highlights the concurrence of a longitudinal and a vertical modular partition. The former reflects the distinct morphogenetic environments of the three endocranial fossae, while the latter corresponds to those of the basicranium and calvaria.

A comparative anatomical network analysis of the human and chimpanzee brains

Spatial interactions among anatomical elements help to identify topological factors behind morphological variation and can be investigated through network analysis. Here, a whole-brain network model of the chimpanzee (Pan troglodytes, Blumenbach 1776) is presented, based on macroanatomical divisions, and compared with a previous equivalent model of the human brain. The goal was to contrast which regions are essential in the geometric balance of the brains of the two species, to compare underlying phenotypic patterns of spatial variation, and to understand how these patterns might have influenced the evolution of human brain morphology. The human and chimpanzee brains share morphologically complex inferior-medial regions and a topological organization that matches the spatial constraints exerted by the surrounding braincase. These shared topological features are interesting because they can be traced back to the Chimpanzee-Human Last Common Ancestor, 7-10 million years ago. Nevertheless, some key differences are found in the human and chimpanzee brains. In humans, the temporal lobe, particularly its deep and medial limbic aspect (the parahippocampal gyrus), is a crucial node for topological complexity. Meanwhile, in chimpanzees, the cerebellum is, in this sense, more embedded in an intricate spatial position. This information helps to interpret brain macroanatomical change in fossil hominids.

Orthopedic Research Funding: Assessing the Relationship between Investments and Breakthroughs

Orthopedic research plays a crucial role in improving patient outcomes for musculoskeletal disorders. This narrative review explores the intricate interplay between funding patterns and the trajectory of breakthroughs achieved in this dynamic field. A meticulous search strategy identified studies illuminating the diverse sources of orthopedic research funding, including public funding (government agencies), philanthropic organizations, private sector investment, and international funding bodies. The review further delved into the spectrum of breakthroughs, encompassing fundamental scientific discoveries, technological advancements, and personalized medicine approaches. Public funding emerged as a significant pillar, supporting foundational research that lays the groundwork for future advancements. Philanthropic organizations addressed specific musculoskeletal disorders, often focusing on patient-centric applications. International funding bodies played a role in supporting research in low- and middle-income countries. Breakthroughs extended beyond cutting-edge prosthetics and minimally invasive surgeries, encompassing fundamental discoveries in areas like gene therapy and biomaterials science. Technological advancements included brain-computer interface prosthetics and 3D-printed implants. Personalized medicine offered the potential for tailored treatments based on individual needs and genetic profiles. This review underscores the complex interplay between funding patterns and breakthroughs in orthopedic research. A multifaceted approach is essential for continued progress. Fostering collaboration, optimizing funding models, and prioritizing both foundational and translational research hold the key to unlocking the true potential of orthopedic research and transforming the lives of patients suffering from musculoskeletal disorders.

Modularity and community detection in human brain morphology

Humans possess morphologically complex brains, which are spatially constrained by their many intrinsic and extrinsic physical interactions. Anatomical network analysis can be used to study these constraints and their implications. Modularity is a key issue in this framework, namely, the presence of groups of elements that undergo morphological evolution in a concerted way. An array of community detection algorithms was tested on a previously designed anatomical network model of the human brain in order to provide a detailed assessment of modularity in this context. The algorithms that provide the highest quality partitions also reveal general phenotypic patterns underlying the topology of human brain morphology. Taken together, the community detection algorithms highlight the simultaneous presence of a longitudinal and a vertical modular partition of the brain's topology, the combination of which matches the organization of the enveloping braincase. Specifically, the longitudinal organization is in line with the different morphogenetic environments of the three endocranial fossae, while the vertical arrangement corresponds to the distinct developmental processes associated with the cranial base and vault, respectively. The results are robust and have the potential to be compared with equivalent network models of other species. Furthermore, they suggest a degree of concerted topological reciprocity in the spatial organization of brain and skull elements, and posit questions about the extent to which geometrical constraints of the cranial base and the modular partition of the corresponding brain regions may channel both evolutionary and developmental trajectories.

Concurrent and continuous estimation of multi-finger forces by synergy mapping and reconstruction: a pilot study

Objective.The absence of intuitive control in present myoelectric interfaces makes it a challenge for users to communicate with assistive devices efficiently in real-world conditions. This study aims to tackle this difficulty by incorporating neurophysiological entities, namely muscle and force synergies, onto multi-finger force estimation to allow intuitive myoelectric control.Approach. Eleven healthy subjects performed six isometric grasping tasks at three muscle contraction levels. The exerted fingertip forces were collected concurrently with the surface electromyographic (sEMG) signals from six extrinsic and intrinsic muscles of hand. Muscle synergies were then extracted from recorded sEMG signals, while force synergies were identified from measured force data. Afterwards, a linear regressor was trained to associate the two types of synergies. This would allow us to predict multi-finger forces simply by multiplying the activation signals derived from muscle synergies with the weighting matrix of initially identified force synergies. To mitigate the false activation of unintended fingers, the force predictions were finally corrected by a finger state recognition procedure.Main results. We found that five muscle synergies and four force synergies are able to make a tradeoff between the computation load and the prediction accuracy for the proposed model; When trained and tested on all six grasping tasks, our method (SYN-II) achieved better performance (R2= 0.80 ± 0.04, NRMSE = 0.19 ± 0.01) than conventional sEMG amplitude-based method; Interestingly, SYN-II performed better than all other methods when tested on two unknown tasks outside the four training tasks (R2= 0.74 ± 0.03, NRMSE = 0.22 ± 0.02), which indicated better generalization ability.Significance. This study shows the first attempt to link between muscle and force synergies to allow concurrent and continuous estimation of multi-finger forces from sEMG. The proposed approach may lay the foundation for high-performance myoelectric interfaces that allow users to control robotic hands in a more natural and intuitive manner.

A roadmap for delivering a human musculoskeletal cell atlas

Advances in single-cell technologies have transformed the ability to identify the individual cell types present within tissues and organs. The musculoskeletal bionetwork, part of the wider Human Cell Atlas project, aims to create a detailed map of the healthy musculoskeletal system at a single-cell resolution throughout tissue development and across the human lifespan, with complementary generation of data from diseased tissues. Given the prevalence of musculoskeletal disorders, this detailed reference dataset will be critical to understanding normal musculoskeletal function in growth, homeostasis and ageing. The endeavour will also help to identify the cellular basis for disease and lay the foundations for novel therapeutic approaches to treating diseases of the joints, soft tissues and bone. Here, we present a Roadmap delineating the critical steps required to construct the first draft of a human musculoskeletal cell atlas. We describe the key challenges involved in mapping the extracellular matrix-rich, but cell-poor, tissues of the musculoskeletal system, outline early milestones that have been achieved and describe the vision and directions for a comprehensive musculoskeletal cell atlas. By embracing cutting-edge technologies, integrating diverse datasets and fostering international collaborations, this endeavour has the potential to drive transformative changes in musculoskeletal medicine.

Effects of tDCS on Foot Biomechanics: A Narrative Review and Clinical Applications

In recent years, neuro-biomechanical enhancement techniques, such as transcranial direct current stimulation (tDCS), have been widely used to improve human physical performance, including foot biomechanical characteristics. This review aims to summarize research on the effects of tDCS on foot biomechanics and its clinical applications, and further analyze the underlying ergogenic mechanisms of tDCS. This review was performed for relevant papers until July 2023 in the following databases: Web of Science, PubMed, and EBSCO. The findings demonstrated that tDCS can improve foot biomechanical characteristics in healthy adults, including proprioception, muscle strength, reaction time, and joint range of motion. Additionally, tDCS can be effectively applied in the field of foot sports medicine; in particular, it can be combined with functional training to effectively improve foot biomechanical performance in individuals with chronic ankle instability (CAI). The possible mechanism is that tDCS may excite specific task-related neurons and regulate multiple neurons within the system, ultimately affecting foot biomechanical characteristics. However, the efficacy of tDCS applied to rehabilitate common musculoskeletal injuries (e.g., CAI and plantar fasciitis) still needs to be confirmed using a larger sample size. Future research should use multimodal neuroimaging technology to explore the intrinsic ergogenic mechanism of tDCS.

A comprehensive anatomical network analysis of human brain topology

A network approach to the macroscopic anatomy of the human brain can be used to model physical interactions among regions in order to study their topological properties, as well as the topological properties of the overall system. Here, a comprehensive model of human brain topology is presented, based on traditional macroanatomical divisions of the whole brain, which includes its subcortical regions. The aim was to localise anatomical elements that are essential for the geometric balance of the brain, as to identify underlying phenotypic patterns of spatial arrangement and understand how these patterns may influence brain morphology in ontogeny and phylogeny. The model revealed that the parahippocampal gyrus, the anterior lobe of the cerebellum and the ventral portion of the midbrain are subjected to major topological constraints that are likely to limit or channel their morphological evolution. The present model suggests that the brain can be divided into a superior and an inferior morphological block, linked with extrinsic topological constraints imposed by the surrounding braincase. This information should be considered duly both in ontogenetic and phylogenetic studies of primate neuroanatomy.

Space Environment Impacts Homeostasis: Exposure to Spaceflight Alters Mammary Gland Transportome Genes

Membrane transporters and ion channels that play an indispensable role in metabolite trafficking have evolved to operate in Earth's gravity. Dysregulation of the transportome expression profile at normogravity not only affects homeostasis along with drug uptake and distribution but also plays a key role in the pathogenesis of diverse localized to systemic diseases including cancer. The profound physiological and biochemical perturbations experienced by astronauts during space expeditions are well-documented. However, there is a paucity of information on the effect of the space environment on the transportome profile at an organ level. Thus, the goal of this study was to analyze the effect of spaceflight on ion channels and membrane substrate transporter genes in the periparturient rat mammary gland. Comparative gene expression analysis revealed an upregulation (p < 0.01) of amino acid, Ca²⁺, K⁺, Na⁺, Zn²⁺, Cl^-, PO₄^3-, glucose, citrate, pyruvate, succinate, cholesterol, and water transporter genes in rats exposed to spaceflight. Genes associated with the trafficking of proton-coupled amino acids, Mg²⁺, Fe²⁺, voltage-gated K⁺-Na⁺, cation-coupled chloride, as well as Na⁺/Ca²⁺ and ATP-Mg/Pi exchangers were suppressed (p < 0.01) in these spaceflight-exposed rats. These findings suggest that an altered transportome profile contributes to the metabolic modulations observed in the rats exposed to the space environment.

Body Weight Control Is a Key Element of Motor Control for Toddlers' Walking

New-borns can step when supported for about 70-80% of their own body weight. Gravity-related sensorimotor information might be an important factor in developing the ability to walk independently. We explored how body weight support alters motor control in toddlers during the first independent steps and in toddlers with about half a year of walking experience. Sixteen different typically developing children were assessed during (un)supported walking on a running treadmill. Electromyography of 18-24 bilateral leg and back muscles and vertical ground reaction forces were recorded. Strides were grouped into four levels of body weight support ranging from no (<10%), low (10-35%), medium (35-55%), and high (55-95%) support. We constructed muscle synergies and muscle networks and assessed differences between levels of support and between groups. In both groups, muscle activities could be described by four synergies. As expected, the mean activity decreased with body weight support around foot strikes. The younger first-steps group showed changes in the temporal pattern of the synergies when supported for more than 35% of their body weight. In this group, the muscle network was dense with several interlimb connections. Apparently, the ability to process gravity-related information is not fully developed at the onset of independent walking causing motor control to be fairly disperse. Synergy-specific sensitivity for unloading implies distinct neural mechanisms underlying (the emergence of) these synergies.

Cranial Anatomical Integration and Disparity Among Bones Discriminate Between Primates and Non-primate Mammals

The primate skull hosts a unique combination of anatomical features among mammals, such as a short face, wide orbits, and big braincase. Together with a trend to fuse bones in late development, these features define the anatomical organization of the skull of primates—which bones articulate to each other and the pattern this creates. Here, I quantified the anatomical organization of the skull of 17 primates and 15 non-primate mammals using anatomical network analysis to assess how the skulls of primates have diverged from those of other mammals, and whether their anatomical differences coevolved with brain size. Results show that primates have a greater anatomical integration of their skulls and a greater disparity among bones than other non-primate mammals. Brain size seems to contribute in part to this difference, but its true effect could not be conclusively proven. This supports the hypothesis that primates have a distinct anatomical organization of the skull, but whether this is related to their larger brains remains an open question.

An Emerging Preventive Mental Health Care Strategy: The Neurobiological and Functional Basis of Positive Psychological Traits

Even with the expanding burden of the COVID-19 pandemic on mental health, our approach to mental health care remains largely reactive rather than preventive. This trend is problematic because the majority of outpatient visits to primary care providers across the country is related to unmet mental health needs. Positive psychology has the potential to address these issues within mental health care and provide primary care providers with strategies to serve their patients more effectively. Positive psychology has many frameworks like hope, which can be measured using simple questionnaires in the waiting room. Moreover, there is a growing body of neurobiological evidence that lends credence to positive psychology concepts in the context of differential neuronal activation patterns. Many positive psychological instruments not only have high construct validity but also have connections to observable neurobiological differences tied to differences in psychosocial functioning. Despite the current evidence, we still need robust research that explores if such psychometric measurements and related interventions lead to clinically significant and favorable health outcomes in patients outside of controlled environments.

Clarifying the Biomechanical Concept of Coordination Through Comparison With Coordination in Motor Control

Coordination is a multidisciplinary concept in human movement science, particularly in the field of biomechanics and motor control. However, the term is not used synonymously by researchers and has substantially different meanings depending on the studies. Therefore, it is necessary to clarify the meaning of coordination to avoid confusion. The meaning of coordination in motor control from computational and ecological perspectives has been clarified, and the meanings differed between them. However, in biomechanics, each study has defined the meaning of the term and the meanings are diverse, and no study has attempted to bring together the diversity of the meanings of the term. Therefore, the purpose of this study is to provide a summary of the different meanings of coordination across the theoretical landscape and clarify the meaning of coordination in biomechanics. We showed that in biomechanics, coordination generally means the relation between elements that act toward the achievement of a motor task, which we call biomechanical coordination. We also showed that the term coordination used in computational and ecological perspectives has two different meanings, respectively. Each one had some similarities with biomechanical coordination. The findings of this study lead to an accurate understanding of the concept of coordination, which would help researchers formulate their empirical arguments for coordination in a more transparent manner. It would allow for accurate interpretation of data and theory development. By comprehensively providing multiple perspectives on coordination, this study intends to promote coordination studies in biomechanics.

Direct Myoelectric Control Modifies Lower Limb Functional Connectivity: A Case Study

Prostheses with direct EMG control could restore amputee's biomechanics structure and residual muscle functions by using efferent signals to drive prosthetic ankle joint movements. Because only feedforward control is restored, it is unclear 1) what neuromuscular control mechanisms are used in coordinating residual and intact muscle activities and 2) how this mechanism changes over guided training with the prosthetic ankle. To address these questions, we applied functional connectivity analysis to an individual with unilateral lower-limb amputation during postural sway task. We built functional connectivity networks of surface EMGs from eleven lower-limb muscles during three sessions to investigate the coupling among different function modules. We observed that functional network was reshaped by training and we identified a stronger connection between residual and intact below knee modules with improved bilateral symmetry after amputee acquired skills to better control the powered prosthetic ankle. The evaluation session showed that functional connectivity was largely preserved even after nine months interval. This preliminary study might inform a unique way to unveil the potential neuromechanic changes that occur after extended training with direct EMG control of a powered prosthetic ankle.

Primitive muscle synergies reflect different modes of coordination in upper limb motions

The motor system relies on the recruitment of motor modules to perform various movements. Muscle synergies are the modules used by the central nervous system to simplify the control of complex motor tasks. In this paper, we aim to explore the primitive synergies to reflect different modes of coordination in upper limb motions. Muscle synergies and corresponding activation coefficients were extracted via non-negative matrix factorization from the electromyography signals of three basic and four complex upper limb motions in sagittal plane and coronal plane. Similarities of muscle synergies and activation coefficients between different tasks and different subjects were compared. Moreover, we used network theory to assess the coordination between multiple muscles and to elucidate the neural implementation of muscle synergies. The results showed that the combination of different sets of primitive muscle synergies can achieve complex motions in different planes. The muscle synergy network topology differed significantly between different tasks. We also demonstrated the potential of this study for the understanding of human motor control mechanism and implications for neurorehabilitation.

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. We used two types of algorithms, light gradient boosting machine (LGB) and fully connected artificial neural network (ANN) solving the wrapping kinematics of 33 muscles spanning up to six degrees of freedom (DOF) each for the arm and hand model with 18 DOFs. The input-output training and testing datasets, where joint angles were the input and the muscle length and moment arms were the output, were generated by our previous phenomenological model based on the autogenerated polynomial structures. Both models achieved a similar level of errors: ANN model errors were 0.08 ± 0.05% for muscle lengths and 0.53 ± 0.29% for moment arms, and LGB model made similar errors-0.18 ± 0.06% and 0.13 ± 0.07%, respectively. LGB model reached the training goal with only 103 samples, while ANN required 106 samples; however, LGB models were about 39 times slower than ANN models in the evaluation. The sufficient performance of developed models demonstrates the future applicability of ML for musculoskeletal transformations in a variety of applications, such as in advanced powered prosthetics.

Soft Robotic Gripper Based on Multi-Layers of Dielectric Elastomer Actuators

Dielectric elastomer actuators (DEAs) are a promising technology for soft robotics. The use of DEAs has many advantages, including light weight, resilience, and fast response for its applications, such as grippers, artificial muscles, and heel strike generators. Grippers are commonly used as grasping devices. In this study, we focus on DEA applications and propose a technology to expand the applicability of a soft gripper. The advantages of gripper-based DEAs include light weight, fast response, and low cost. We fabricated soft grippers using multiple DEA layers. The grippers successfully held or gripped an object, and we investigated the response time of the grippers and their angle characteristics. We studied the relationship between the number of DEA layers and the performance of our grippers. Our experimental results show that the multi-layered DEAs have the potential to be strong grippers.

Morphometric analysis of vastus medialis oblique muscle and its influence on anterior knee pain

Healthy knees require full range squatting movements. Vastus medialis (VM) muscle regulates and adjusts the extensor apparatus that influences the patellofemoral function. This work was designed to investigate the anatomy and morphometry of vastus medialis oblique (VMO) muscle by widely used imaging techniques and investigate how VMO muscle participates in anterior knee pain. Ten dissected cadaveric specimens were examined, focusing on fiber orientations, origin, insertions and nerve supply of VMO muscle. Magnetic resonance imaging and ultrasound of VMO muscle were recorded. Anatomical cross-sectional areas of VMO muscle were determined in painless and painful knees and statistically analyzed. In cadaveric specimens, there was distinct separation between VM longus and VMO (change in fiber angle or fibro-fascial plane). VMO inserted directly into the medial proximal margin of the patella, capsule of the knee joint and continuous with the patellar tendon. Separate branch of femoral nerve run along the anteromedial border of the muscle. Anatomical cross-sectional area was significantly decreased in painful knee by -17.2%±11.0% at lower end of shaft of femur, -21.1%±6.0% at upper border of patella, -36.7%±11.0% at mid-patellar level. VMO is distinct muscle within quadriceps femoris group. VMO muscle would track the patella medially and participate in last phase of knee extension. Assessment of the VMO muscle anatomical cross-sectional area by ultrasonography may constitute promising and reliable tool to evaluate patellofemoral pain syndrome staging.

Mapping the rest of the human connectome: Atlasing the spinal cord and peripheral nervous system

The emergence of diffusion, structural, and functional neuroimaging methods has enabled major multi-site efforts to map the human connectome, which has heretofore been defined as containing all neural connections in the central nervous system (CNS). However, these efforts are not structured to examine the richness and complexity of the peripheral nervous system (PNS), which arguably forms the (neglected) rest of the connectome. Despite increasing interest in an atlas of the spinal cord (SC) and PNS which is simultaneously stereotactic, interactive, electronically dissectible, scalable, population-based and deformable, little attention has thus far been devoted to this task of critical importance. Nevertheless, the atlasing of these complete neural structures is essential for neurosurgical planning, neurological localization, and for mapping those components of the human connectome located outside of the CNS. Here we recommend a modification to the definition of the human connectome to include the SC and PNS, and argue for the creation of an inclusive atlas to complement current efforts to map the brain's human connectome, to enhance clinical education, and to assist progress in neuroscience research. In addition to providing a critical overview of existing neuroimaging techniques, image processing methodologies and algorithmic advances which can be combined for the creation of a full connectome atlas, we outline a blueprint for ultimately mapping the entire human nervous system and, thereby, for filling a critical gap in our scientific knowledge of neural connectivity.

Community detection in bipartite networks with stochastic block models

In bipartite networks, community structures are restricted to being disassortative, in that nodes of one type are grouped according to common patterns of connection with nodes of the other type. This makes the stochastic block model (SBM), a highly flexible generative model for networks with block structure, an intuitive choice for bipartite community detection. However, typical formulations of the SBM do not make use of the special structure of bipartite networks. Here we introduce a Bayesian nonparametric formulation of the SBM and a corresponding algorithm to efficiently find communities in bipartite networks which parsimoniously chooses the number of communities. The biSBM improves community detection results over general SBMs when data are noisy, improves the model resolution limit by a factor of sqrt[2], and expands our understanding of the complicated optimization landscape associated with community detection tasks. A direct comparison of certain terms of the prior distributions in the biSBM and a related high-resolution hierarchical SBM also reveals a counterintuitive regime of community detection problems, populated by smaller and sparser networks, where nonhierarchical models outperform their more flexible counterpart.

A node-based informed modularity strategy to identify organizational modules in anatomical networks

The study of morphological modularity using anatomical networks is growing in recent years. A common strategy to find the best network partition uses community detection algorithms that optimize the modularity Q function. Because anatomical networks and their modules tend to be small, this strategy often produces two problems. One is that some algorithms find inexplicable different modules when one inputs slightly different networks. The other is that algorithms find asymmetric modules in otherwise symmetric networks. These problems have discouraged researchers to use anatomical network analysis and boost criticisms to this methodology. Here, I propose a node-based informed modularity strategy (NIMS) to identify modules in anatomical networks that bypass resolution and sensitivity limitations by using a bottom-up approach. Starting with the local modularity around every individual node, NIMS returns the modular organization of the network by merging non-redundant modules and assessing their intersection statistically using combinatorial theory. Instead of acting as a black box, NIMS allows researchers to make informed decisions about whether to merge non-redundant modules. NIMS returns network modules that are robust to minor variation and does not require optimization of a global modularity function. NIMS may prove useful to identify modules also in small ecological and social networks.

Summary: A new method to identify modules in anatomical networks without optimization and statistically assess their degree of overlap. This method will assist researchers in identifying meaningful biological modules.

Caring Stroke Patients with Musculoskeletal Problem: A Narrative Review

Background: The purpose of this paper is to narratively review the literature on caring for stroke patients with a musculoskeletal problem which involves rehabilitation of nursing and health care. Through the review, this paper addresses five questions: What are the typical difficulties of a stroke patient? What are the effects of a stroke on the musculoskeletal system? How to take care of musculoskeletal problem and pain? What is good musculoskeletal care for patients with stroke? How to take care of the musculoskeletal problem through active rehabilitation? Method: The relevant articles published between 2010-2020 were identified through searches in PubMed, Google Scholar, CINAHL, PsychInfo and by inspecting the reference list using keywords of ‘stroke’ and ‘musculoskeletal’.  Result: A total of 19 selected address this topic and consequently answer the questions posed. Findings flow with the typical difficulties of a stroke patient, the effects of a stroke on the musculoskeletal system, caring for musculoskeletal problem and pain, good musculoskeletal care for patients with stroke and caring for the musculoskeletal problem through active rehabilitation. Conclusion: This paper highlights that stroke patients with the musculoskeletal problem have restricted day-to-day movement functions and needed interdisciplinary care approaches from nursing, physical and occupational therapies, and other health care professionals. Stroke patients may need a structured programme to improve the outcome of stroke rehabilitation for the musculoskeletal problem.  

Muscle Synergies and Coherence Networks Reflect Different Modes of Coordination During Walking

When walking speed is increased, the frequency ratio between the arm and leg swing switches spontaneously from 2:1 to 1:1. We examined whether these switches are accompanied by changes in functional connectivity between multiple muscles. Subjects walked on a treadmill with their arms swinging along their body while kinematics and surface electromyography (EMG) of 26 bilateral muscles across the body were recorded. Walking speed was varied from very slow to normal. We decomposed EMG envelopes and intermuscular coherence spectra using non-negative matrix factorization (NMF), and the resulting modes were combined into multiplex networks and analyzed for their community structure. We found five relevant muscle synergies that significantly differed in activation patterns between 1:1 and 2:1 arm-leg coordination and the transition period between them. The corresponding multiplex network contained a single module indicating pronounced muscle co-activation patterns across the whole body during a gait cycle. NMF of the coherence spectra distinguished three EMG frequency bands: 4-8, 8-22, and 22-60 Hz. The community structure of the multiplex network revealed four modules, which clustered functional and anatomical linked muscles across modes of coordination. Intermuscular coherence at 4-22 Hz between upper and lower body and within the legs was particularly pronounced for 1:1 arm-leg coordination and was diminished when switching between modes of coordination. These findings suggest that the stability of arm-leg coordination is associated with modulations in long-distant neuromuscular connectivity.

Plasminogen activation in the musculoskeletal acute phase response: Injury, repair, and disease

The musculoskeletal system is critical for movement and the protection of organs. In addition to abrupt injuries, daily physical demands inflict minor injuries, necessitating a coordinated process of repair referred to as the acute-phase response (APR). Dysfunctional APRs caused by severe injuries or underlying chronic diseases are implicated in pathologic musculoskeletal repair, resulting in decreased mobility and chronic pain. The molecular mechanisms behind these phenomena are not well understood, hindering the development of clinical solutions. Recent studies indicate that, in addition to regulating intravascular clotting, the coagulation and fibrinolytic systems are also entrenched in tissue repair. Although plasmin and fibrin are considered antithetical to one another in the context of hemostasis, in a proper APR, they complement one another within a coordinated spatiotemporal framework. Once a wound is contained by fibrin, activation of plasmin promotes the removal of fibrin and stimulates angiogenesis, tissue remodeling, and tissue regeneration. Insufficient fibrin deposition or excessive plasmin-mediated fibrinolysis in early convalescence prevents injury containment, causing bleeding. Alternatively, excess fibrin deposition and/or inefficient plasmin activity later in convalescence impairs musculoskeletal repair, resulting in tissue fibrosis and osteoporosis, while inappropriate fibrin or plasmin activity in a synovial joint can cause arthritis. Together, these pathologic conditions lead to chronic pain, poor mobility, and diminished quality of life. In this review, we discuss both fibrin-dependent and -independent roles of plasminogen activation in the musculoskeletal APR, how dysregulation of these mechanisms promote musculoskeletal degeneration, and the possibility of therapeutically manipulating plasmin or fibrin to treat musculoskeletal disease.

Dynamic Change of Lumbar Structure and Associated Factors: A Retrospective Study

Objective

To determine whether lumbar anatomy parameters are in dynamic change and related factors.

Methods

This is a retrospective study. Participants who did lumbar computed tomography (CT) scanning in Shandong University Qilu Hospital from October 2017 to March 2019 were selected. The 476 participants were randomly selected as male or female, with the age ranging from 17 to 87 years (mean, 55.19; standard deviation, 14.28 years). All the measurements were taken based on the CT scanning image and the measurement of lumbar morphology was conducted using picture archiving and communication systems (PACS). The angle between the horizontal alignment and pedicle center on median sagittal view, the angle between upper endplate and lower endplate on median sagittal view as well as transverse section angle (TSA) using Magerl point in the axial view was determined by reconstructive CT analysis.

Results

In the overall participants, the angle between the horizontal alignment and pedicle center on median sagittal view of lumbar one to three was significantly decreased with aging, from 3.90° ± 2.81° to −4.18° ± 6.86° (P = 0.002), 5.60° ± 2.89° to −4.14° ± 5.90° (P = 0.030), and 4.75° ± 2.95° to −2.87° ± 4.68° (P < 0.001), respectively. Additionally, the angle between the horizontal alignment and pedicle center on median sagittal view in male participants of lumbar two was dramatically decreased, from 4.83° ± 2.79° to −4.45° ± 5.97° (P = 0.30). And that of lumbar three in female participants was significantly decreased, from 4.56° ± 2.52° to −2.88° ± 5.03° (P = 0.029). Furthermore, of the overall participants, the angle between upper endplate and lower endplate on median sagittal view of lumbar one to four was associated with aging (P < 0.001, P < 0.001, P = 0.015, P < 0.001, respectively). The angle of lumbar one, two and four in male participants and lumbar one to four in female participants were all significantly related to aging (all P < 0.05). Moreover, in the participants overall, the TSA of lumbar one to three was significantly associated with aging (P = 0.015, P = 0.006 and P = 0.007, respectively). In addition, this angle in lumbar one to lumbar four in male participants were all negatively associated with aging (P = 0.017, P = 0.001, P = 0.005 and P = 0.036, respectively).

Conclusion

Lumbar anatomy parameters are in dynamic change in an age and gender dependent manner. During spine surgery in elderly patients, more attention should be paid to these anatomic changes.

Anatomical network analysis of the musculoskeletal system reveals integration loss and parcellation boost during the fins-to-limbs transition

Tetrapods evolved from within the lobe-finned fishes around 370 Ma. The evolution of limbs from lobe-fins entailed a major reorganization of the skeletal and muscular anatomy of appendages in early tetrapods. Concurrently, a degree of similarity between pectoral and pelvic appendages also evolved. Here, we compared the anatomy of appendages in extant lobe-finned fishes (Latimeria and Neoceratodus) and anatomically plesiomorphic amphibians (Ambystoma, Salamandra) and amniotes (Sphenodon) to trace and reconstruct the musculoskeletal changes that took place during the fins-to-limbs transition. We quantified the anatomy of appendages using network analysis. First, we built network models-in which nodes represent bones and muscles, and links represent their anatomical connections-and then we measured network parameters related to their anatomical integration, heterogeneity, and modularity. Our results reveal an evolutionary transition toward less integrated, more modular appendages. We interpret this transition as a diversification of muscle functions in tetrapods compared to lobe-finned fishes. Limbs and lobe-fins show also a greater similarity between their pectoral and pelvic appendages than ray-fins do. These findings on extant species provide a basis for future quantitative and comprehensive reconstructions of the anatomy of limbs in early tetrapod fossils, and a way to better understand the fins-to-limbs transition.

Network structure of the human musculoskeletal system shapes neural interactions on multiple time scales

Human motor control requires the coordination of muscle activity under the anatomical constraints imposed by the musculoskeletal system. Interactions within the central nervous system are fundamental to motor coordination, but the principles governing functional integration remain poorly understood. We used network analysis to investigate the relationship between anatomical and functional connectivity among 36 muscles. Anatomical networks were defined by the physical connections between muscles, and functional networks were based on intermuscular coherence assessed during postural tasks. We found a modular structure of functional networks that was strongly shaped by the anatomical constraints of the musculoskeletal system. Changes in postural tasks were associated with a frequency-dependent reconfiguration of the coupling between functional modules. These findings reveal distinct patterns of functional interactions between muscles involved in flexibly organizing muscle activity during postural control. Our network approach to the motor system offers a unique window into the neural circuitry driving the musculoskeletal system.

Brain state flexibility accompanies motor-skill acquisition

Learning requires the traversal of inherently distinct cognitive states to produce behavioral adaptation. Yet, tools to explicitly measure these states with non-invasive imaging – and to assess their dynamics during learning – remain limited. Here, we describe an approach based on a distinct application of graph theory in which points in time are represented by network nodes, and similarities in brain states between two different time points are represented as network edges. We use a graph-based clustering technique to identify clusters of time points representing canonical brain states, and to assess the manner in which the brain moves from one state to another as learning progresses. We observe the presence of two primary states characterized by either high activation in sensorimotor cortex or high activation in a frontal-subcortical system. Flexible switching among these primary states and other less common states becomes more frequent as learning progresses, and is inversely correlated with individual differences in learning rate. These results are consistent with the notion that the development of automaticity is associated with a greater freedom to use cognitive resources for other processes. Taken together, our work offers new insights into the constrained, low dimensional nature of brain dynamics characteristic of early learning, which give way to less constrained, high-dimensional dynamics in later learning.