Sensory Agreement Guides Kinetic Energy Optimization of Arm Movements during Object Manipulation.
Identifieur interne : 000057 ( PubMed/Curation ); précédent : 000056; suivant : 000058Sensory Agreement Guides Kinetic Energy Optimization of Arm Movements during Object Manipulation.
Auteurs : Ali Farshchiansadegh [États-Unis] ; Alejandro Melendez-Calderon [États-Unis] ; Rajiv Ranganathan [États-Unis] ; Todd D. Murphey [États-Unis] ; Ferdinando A. Mussa-Ivaldi [États-Unis]Source :
- PLoS computational biology [ 1553-7358 ] ; 2016.
Abstract
The laws of physics establish the energetic efficiency of our movements. In some cases, like locomotion, the mechanics of the body dominate in determining the energetically optimal course of action. In other tasks, such as manipulation, energetic costs depend critically upon the variable properties of objects in the environment. Can the brain identify and follow energy-optimal motions when these motions require moving along unfamiliar trajectories? What feedback information is required for such optimal behavior to occur? To answer these questions, we asked participants to move their dominant hand between different positions while holding a virtual mechanical system with complex dynamics (a planar double pendulum). In this task, trajectories of minimum kinetic energy were along curvilinear paths. Our findings demonstrate that participants were capable of finding the energy-optimal paths, but only when provided with veridical visual and haptic information pertaining to the object, lacking which the trajectories were executed along rectilinear paths.
DOI: 10.1371/journal.pcbi.1004861
PubMed: 27035587
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<front><div type="abstract" xml:lang="en">The laws of physics establish the energetic efficiency of our movements. In some cases, like locomotion, the mechanics of the body dominate in determining the energetically optimal course of action. In other tasks, such as manipulation, energetic costs depend critically upon the variable properties of objects in the environment. Can the brain identify and follow energy-optimal motions when these motions require moving along unfamiliar trajectories? What feedback information is required for such optimal behavior to occur? To answer these questions, we asked participants to move their dominant hand between different positions while holding a virtual mechanical system with complex dynamics (a planar double pendulum). In this task, trajectories of minimum kinetic energy were along curvilinear paths. Our findings demonstrate that participants were capable of finding the energy-optimal paths, but only when provided with veridical visual and haptic information pertaining to the object, lacking which the trajectories were executed along rectilinear paths.</div>
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