Sensor-Motor Maps for Describing Linear Reflex Composition in Hopping

In human and animal motor control several sensory organs contribute to a network of sensory pathways modulating the motion depending on the task and the phase of execution to generate daily motor tasks such as locomotion. To better understand the individual and joint contribution of reflex pathways...

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Main Authors: Christian Schumacher, André Seyfarth
Format: Article
Language:English
Published: Frontiers Media S.A. 2017-11-01
Series:Frontiers in Computational Neuroscience
Subjects:
Online Access:http://journal.frontiersin.org/article/10.3389/fncom.2017.00108/full
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spelling doaj-adc2da58bbb44ec3a46ea47d1f921a502020-11-24T21:40:18ZengFrontiers Media S.A.Frontiers in Computational Neuroscience1662-51882017-11-011110.3389/fncom.2017.00108251326Sensor-Motor Maps for Describing Linear Reflex Composition in HoppingChristian SchumacherAndré SeyfarthIn human and animal motor control several sensory organs contribute to a network of sensory pathways modulating the motion depending on the task and the phase of execution to generate daily motor tasks such as locomotion. To better understand the individual and joint contribution of reflex pathways in locomotor tasks, we developed a neuromuscular model that describes hopping movements. In this model, we consider the influence of proprioceptive length (LFB), velocity (VFB) and force feedback (FFB) pathways of a leg extensor muscle on hopping stability, performance and efficiency (metabolic effort). Therefore, we explore the space describing the blending of the monosynaptic reflex pathway gains. We call this reflex parameter space a sensor-motor map. The sensor-motor maps are used to visualize the functional contribution of sensory pathways in multisensory integration. We further evaluate the robustness of these sensor-motor maps to changes in tendon elasticity, body mass, segment length and ground compliance. The model predicted that different reflex pathway compositions selectively optimize specific hopping characteristics (e.g., performance and efficiency). Both FFB and LFB were pathways that enable hopping. FFB resulted in the largest hopping heights, LFB enhanced hopping efficiency and VFB had the ability to disable hopping. For the tested case, the topology of the sensor-motor maps as well as the location of functionally optimal compositions were invariant to changes in system designs (tendon elasticity, body mass, segment length) or environmental parameters (ground compliance). Our results indicate that different feedback pathway compositions may serve different functional roles. The topology of the sensor-motor map was predicted to be robust against changes in the mechanical system design indicating that the reflex system can use different morphological designs, which does not apply for most robotic systems (for which the control often follows a specific design). Consequently, variations in body mechanics are permitted with consistent compositions of sensory feedback pathways. Given the variability in human body morphology, such variations are highly relevant for human motor control.http://journal.frontiersin.org/article/10.3389/fncom.2017.00108/fullfeedback pathwayshoppingmotor controlfunctional decompositionneuromechanicsmultisensory integration
collection DOAJ
language English
format Article
sources DOAJ
author Christian Schumacher
André Seyfarth
spellingShingle Christian Schumacher
André Seyfarth
Sensor-Motor Maps for Describing Linear Reflex Composition in Hopping
Frontiers in Computational Neuroscience
feedback pathways
hopping
motor control
functional decomposition
neuromechanics
multisensory integration
author_facet Christian Schumacher
André Seyfarth
author_sort Christian Schumacher
title Sensor-Motor Maps for Describing Linear Reflex Composition in Hopping
title_short Sensor-Motor Maps for Describing Linear Reflex Composition in Hopping
title_full Sensor-Motor Maps for Describing Linear Reflex Composition in Hopping
title_fullStr Sensor-Motor Maps for Describing Linear Reflex Composition in Hopping
title_full_unstemmed Sensor-Motor Maps for Describing Linear Reflex Composition in Hopping
title_sort sensor-motor maps for describing linear reflex composition in hopping
publisher Frontiers Media S.A.
series Frontiers in Computational Neuroscience
issn 1662-5188
publishDate 2017-11-01
description In human and animal motor control several sensory organs contribute to a network of sensory pathways modulating the motion depending on the task and the phase of execution to generate daily motor tasks such as locomotion. To better understand the individual and joint contribution of reflex pathways in locomotor tasks, we developed a neuromuscular model that describes hopping movements. In this model, we consider the influence of proprioceptive length (LFB), velocity (VFB) and force feedback (FFB) pathways of a leg extensor muscle on hopping stability, performance and efficiency (metabolic effort). Therefore, we explore the space describing the blending of the monosynaptic reflex pathway gains. We call this reflex parameter space a sensor-motor map. The sensor-motor maps are used to visualize the functional contribution of sensory pathways in multisensory integration. We further evaluate the robustness of these sensor-motor maps to changes in tendon elasticity, body mass, segment length and ground compliance. The model predicted that different reflex pathway compositions selectively optimize specific hopping characteristics (e.g., performance and efficiency). Both FFB and LFB were pathways that enable hopping. FFB resulted in the largest hopping heights, LFB enhanced hopping efficiency and VFB had the ability to disable hopping. For the tested case, the topology of the sensor-motor maps as well as the location of functionally optimal compositions were invariant to changes in system designs (tendon elasticity, body mass, segment length) or environmental parameters (ground compliance). Our results indicate that different feedback pathway compositions may serve different functional roles. The topology of the sensor-motor map was predicted to be robust against changes in the mechanical system design indicating that the reflex system can use different morphological designs, which does not apply for most robotic systems (for which the control often follows a specific design). Consequently, variations in body mechanics are permitted with consistent compositions of sensory feedback pathways. Given the variability in human body morphology, such variations are highly relevant for human motor control.
topic feedback pathways
hopping
motor control
functional decomposition
neuromechanics
multisensory integration
url http://journal.frontiersin.org/article/10.3389/fncom.2017.00108/full
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AT andreseyfarth sensormotormapsfordescribinglinearreflexcompositioninhopping
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