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      Spinal Mechanisms May Provide a Combination of Intermittent and Continuous Control of Human Posture: Predictions from a Biologically Based Neuromusculoskeletal Model

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          Several models have been employed to study human postural control during upright quiet stance. Most have adopted an inverted pendulum approximation to the standing human and theoretical models to account for the neural feedback necessary to keep balance. The present study adds to the previous efforts in focusing more closely on modelling the physiological mechanisms of important elements associated with the control of human posture. This paper studies neuromuscular mechanisms behind upright stance control by means of a biologically based large-scale neuromusculoskeletal (NMS) model. It encompasses: i) conductance-based spinal neuron models (motor neurons and interneurons); ii) muscle proprioceptor models (spindle and Golgi tendon organ) providing sensory afferent feedback; iii) Hill-type muscle models of the leg plantar and dorsiflexors; and iv) an inverted pendulum model for the body biomechanics during upright stance. The motor neuron pools are driven by stochastic spike trains. Simulation results showed that the neuromechanical outputs generated by the NMS model resemble experimental data from subjects standing on a stable surface. Interesting findings were that: i) an intermittent pattern of muscle activation emerged from this posture control model for two of the leg muscles (Medial and Lateral Gastrocnemius); and ii) the Soleus muscle was mostly activated in a continuous manner. These results suggest that the spinal cord anatomy and neurophysiology (e.g., motor unit types, synaptic connectivities, ordered recruitment), along with the modulation of afferent activity, may account for the mixture of intermittent and continuous control that has been a subject of debate in recent studies on postural control. Another finding was the occurrence of the so-called “paradoxical” behaviour of muscle fibre lengths as a function of postural sway. The simulations confirmed previous conjectures that reciprocal inhibition is possibly contributing to this effect, but on the other hand showed that this effect may arise without any anticipatory neural control mechanism.

          Author Summary

          The control of upright stance is a challenging task since the objective is to maintain the equilibrium of an intrinsically unstable biomechanical system. Somatosensory information is used by the central nervous system to modulate muscle contraction, which prevents the body from falling. While the visual and vestibular systems also provide important additional sensory information, a human being with only somatosensory inputs is able to maintain an upright stance. In this study, we used a biologically-based large-scale neuromusculoskeletal model driven only by somatosensory feedback to investigate human postural control from a neurophysiological point of view. No neural structures above the spinal cord were included in the model. The results showed that the model based on a spinal control of posture can reproduce several neuromechanical outcomes previously reported in the literature, including an intermittent muscle activation. Since this intermittent muscular recruitment is an emergent property of this spinal-like controller, we argue that the so-called intermittent control of upright stance might be produced by an interplay between spinal cord properties and modulated sensory inflow.

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          Most cited references 65

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          Measures of postural steadiness: differences between healthy young and elderly adults.

          Measures of postural steadiness are used to characterize the dynamics of the postural control system associated with maintaining balance during quiet standing. The objective of this study was to evaluate the relative sensitivity of center-of-pressure (COP)-based measures to changes in postural steadiness related to age. A variety of time and frequency domain measures of postural steadiness were compared between a group of twenty healthy young adults (21-35 years) and a group of twenty healthy elderly adults (66-70 years) under both eyes-open and eyes-closed conditions. The measures that identified differences between the eyes-open and eyes-closed conditions in the young adult group were different than those that identified differences between the eye conditions in the elderly adult group. Mean velocity of the COP was the only measure that identified age-related changes in both eye conditions, and differences between eye conditions in both groups. The results of this study will be useful to researchers and clinicians using COP-based measures to evaluate postural steadiness.
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            A large-scale model of the functioning brain.

            A central challenge for cognitive and systems neuroscience is to relate the incredibly complex behavior of animals to the equally complex activity of their brains. Recently described, large-scale neural models have not bridged this gap between neural activity and biological function. In this work, we present a 2.5-million-neuron model of the brain (called "Spaun") that bridges this gap by exhibiting many different behaviors. The model is presented only with visual image sequences, and it draws all of its responses with a physically modeled arm. Although simplified, the model captures many aspects of neuroanatomy, neurophysiology, and psychological behavior, which we demonstrate via eight diverse tasks.
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              Cortical control of postural responses.

              This article reviews the evidence for cortical involvement in shaping postural responses evoked by external postural perturbations. Although responses to postural perturbations occur more quickly than the fastest voluntary movements, they have longer latencies than spinal stretch reflexes, suggesting greater potential for modification by the cortex. Postural responses include short, medium and long latency components of muscle activation with increasing involvement of the cerebral cortex as latencies increase. Evidence suggests that the cortex is also involved in changing postural responses with alterations in cognitive state, initial sensory-motor conditions, prior experience, and prior warning of a perturbation, all representing changes in "central set." Studies suggest that the cerebellar-cortical loop is responsible for adapting postural responses based on prior experience and the basal ganglia-cortical loop is responsible for pre-selecting and optimizing postural responses based on current context. Thus, the cerebral cortex likely influences longer latency postural responses both directly via corticospinal loops and shorter latency postural responses indirectly via communication with the brainstem centers that harbor the synergies for postural responses, thereby providing both speed and flexibility for pre-selecting and modifying environmentally appropriate responses to a loss of balance.

                Author and article information

                Role: Editor
                PLoS Comput Biol
                PLoS Comput. Biol
                PLoS Computational Biology
                Public Library of Science (San Francisco, USA )
                November 2014
                13 November 2014
                : 10
                : 11
                Biomedical Engineering Laboratory, Escola Politécnica, University of Sao Paulo, Sao Paulo, Brazil
                University of Southern California, United States of America
                Author notes

                The authors have declared that no competing interests exist.

                Conceived and designed the experiments: LAE AFK. Performed the experiments: LAE RNW. Analyzed the data: LAE RNW AFK. Contributed reagents/materials/analysis tools: LAE RNW. Wrote the paper: LAE RNW AFK.


                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Page count
                Pages: 18
                This study was funded by Grants from Sao Paulo Research Foundation (FAPESP - and CNPq (Brazilian NSF - LAE received a PhD scholarship (Grant no. 2009/15802-0) and a Post-Doctoral Grant (Grant no. 2013/1043301) from FAPESP. RNW holds a PhD scholarship from FAPESP (Grant no. 2011/21103-7). AFK was funded by a Grant from CNPq (Grant no. 303313/2011-0). The funders had no role in study design, data collections and analysis, decision to publish, or preparation of the manuscript.
                Research Article
                Biology and Life Sciences
                Nervous System
                Motor System
                Computational Biology
                Computational Neuroscience
                Sensory Systems
                Somatosensory System
                Engineering and Technology
                Custom metadata
                The authors confirm that all data underlying the findings are fully available without restriction. All data files and source codes are available from the figshare database (DOIs 10.6084/m9.figshare.1029085, 10.6084/m9.figshare.1027609, 10.6084/m9.figshare.1029084).

                Quantitative & Systems biology


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