A computational scheme for internal models not requiring precise system parameters
PublisherPublic Library of Science
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AbstractUtilization by humans of a precise and adaptable internal model of the dynamics of the body in generating movements is a well-supported concept. The prevailing opinion is that such an internal model ceaselessly develops through long-term repetition and accumulation in the central nervous system (CNS). However, a long-term learning process would not be absolutely necessary for the formation of internal models. It is possible to estimate the dynamics of the system by using a motor command and its resulting output, instead of constructing a model of the dynamics with precise parameters. In this study, a computational model is proposed that uses a motor command and its corresponding output to estimate the dynamics of the system and it is examined whether the proposed model is capable of describing a series of empirical movements. The proposed model was found to be capable of describing humans' fast movements which require compensation for system dynamics as well as sensory delays. In addition, the proposed model shows equifinality under inertial perturbations as seen in several experimental studies. This satisfactory reproducibility of the proposed computation raises the possibility that humans make a movement by estimating the system dynamics with a copy of motor command and sensory output on a momentary basis, without the need to identify precise system parameters. ©2019 Dongwon Kim. 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.
SponsorsThe author received no specific funding for this work. I would like to express my heart-felt gratitude to Prof. Bernard J. Martin at the University of Michigan and Prof. William Z. Rymer at Northwestern University for their insight and advice toward this study. Also, I deeply thank Prof. Dinant Kistemaker for generously providing his experimental data.
Identifier to cite or link to this itemhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85062184147&doi=10.1371%2fjournal.pone.0210616&partnerID=40&md5=1d9b3456c3b060035dcd6a64e8635ec2; http://hdl.handle.net/10713/8530