Document Detail


Dynamic primitives of motor behavior.
MedLine Citation:
PMID:  23124919     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
We present in outline a theory of sensorimotor control based on dynamic primitives, which we define as attractors. To account for the broad class of human interactive behaviors-especially tool use-we propose three distinct primitives: submovements, oscillations, and mechanical impedances, the latter necessary for interaction with objects. Owing to the fundamental features of the neuromuscular system-most notably, its slow response-we argue that encoding in terms of parameterized primitives may be an essential simplification required for learning, performance, and retention of complex skills. Primitives may simultaneously and sequentially be combined to produce observable forces and motions. This may be achieved by defining a virtual trajectory composed of submovements and/or oscillations interacting with impedances. Identifying primitives requires care: in principle, overlapping submovements would be sufficient to compose all observed movements but biological evidence shows that oscillations are a distinct primitive. Conversely, we suggest that kinematic synergies, frequently discussed as primitives of complex actions, may be an emergent consequence of neuromuscular impedance. To illustrate how these dynamic primitives may account for complex actions, we briefly review three types of interactive behaviors: constrained motion, impact tasks, and manipulation of dynamic objects.
Authors:
Neville Hogan; Dagmar Sternad
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S.; Review     Date:  2012-11-03
Journal Detail:
Title:  Biological cybernetics     Volume:  106     ISSN:  1432-0770     ISO Abbreviation:  Biol Cybern     Publication Date:  2012 Dec 
Date Detail:
Created Date:  2012-11-29     Completed Date:  2013-05-10     Revised Date:  2013-08-12    
Medline Journal Info:
Nlm Unique ID:  7502533     Medline TA:  Biol Cybern     Country:  Germany    
Other Details:
Languages:  eng     Pagination:  727-39     Citation Subset:  IM    
Affiliation:
Department of Mechanical Engineering, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. neville@mit.edu
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MeSH Terms
Descriptor/Qualifier:
Animals
Biomechanics
Humans
Learning
Models, Neurological*
Movement / physiology*
Nonlinear Dynamics*
Periodicity
Primates / physiology*
Grant Support
ID/Acronym/Agency:
R01 HD045639/HD/NICHD NIH HHS; R01-HD045639/HD/NICHD NIH HHS
Comments/Corrections

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