A central problem in motor control is understanding how the many biomechanical
degrees of freedom are coordinated to achieve a common goal. An especially
puzzling aspect of coordination is that behavioral goals are achieved
reliably and repeatedly with movements rarely reproducible in their
detail. Existing theoretical frameworks emphasize either goal achievement
or the richness of motor variability, but fail to reconcile the two.
Here we propose an alternative theory based on stochastic optimal
feedback control. We show that the optimal strategy in the face of
uncertainty is to allow variability in redundant (task-irrelevant)
dimensions. This strategy does not enforce a desired trajectory,
but uses feedback more intelligently, correcting only those deviations
that interfere with task goals. From this framework, task-constrained
variability, goal-directed corrections, motor synergies, controlled
parameters, simplifying rules and discrete coordination modes emerge
naturally. We present experimental results from a range of motor
tasks to support this theory.
%0 Journal Article
%1 Todorov:2002
%A Todorov, Emanuel
%A Jordan, Michael I.
%D 2002
%J Nature Neuroscience
%K control; feedback noise; optimal optimality;
%N 11
%P 1226-1235
%T Optimal feedback control as a theory of motor coordination
%V 5
%X A central problem in motor control is understanding how the many biomechanical
degrees of freedom are coordinated to achieve a common goal. An especially
puzzling aspect of coordination is that behavioral goals are achieved
reliably and repeatedly with movements rarely reproducible in their
detail. Existing theoretical frameworks emphasize either goal achievement
or the richness of motor variability, but fail to reconcile the two.
Here we propose an alternative theory based on stochastic optimal
feedback control. We show that the optimal strategy in the face of
uncertainty is to allow variability in redundant (task-irrelevant)
dimensions. This strategy does not enforce a desired trajectory,
but uses feedback more intelligently, correcting only those deviations
that interfere with task goals. From this framework, task-constrained
variability, goal-directed corrections, motor synergies, controlled
parameters, simplifying rules and discrete coordination modes emerge
naturally. We present experimental results from a range of motor
tasks to support this theory.
@article{Todorov:2002,
abstract = {A central problem in motor control is understanding how the many biomechanical
degrees of freedom are coordinated to achieve a common goal. An especially
puzzling aspect of coordination is that behavioral goals are achieved
reliably and repeatedly with movements rarely reproducible in their
detail. Existing theoretical frameworks emphasize either goal achievement
or the richness of motor variability, but fail to reconcile the two.
Here we propose an alternative theory based on stochastic optimal
feedback control. We show that the optimal strategy in the face of
uncertainty is to allow variability in redundant (task-irrelevant)
dimensions. This strategy does not enforce a desired trajectory,
but uses feedback more intelligently, correcting only those deviations
that interfere with task goals. From this framework, task-constrained
variability, goal-directed corrections, motor synergies, controlled
parameters, simplifying rules and discrete coordination modes emerge
naturally. We present experimental results from a range of motor
tasks to support this theory.},
added-at = {2009-06-26T15:25:19.000+0200},
author = {Todorov, Emanuel and Jordan, Michael I.},
biburl = {https://www.bibsonomy.org/bibtex/2e4652f998073dad1463930d0dd0bf0bc/butz},
comment = {Optimal feedback control besteht darin, nur die relevanten Parameter
anzupassen, um nicht überflüssige motor noise zu erzeugen},
description = {diverse cognitive systems bib},
interhash = {a0ac78c8c879242ddb23359e307fd584},
intrahash = {e4652f998073dad1463930d0dd0bf0bc},
journal = {Nature Neuroscience},
keywords = {control; feedback noise; optimal optimality;},
number = 11,
owner = {martin},
pages = {1226-1235},
timestamp = {2009-06-26T15:25:58.000+0200},
title = {Optimal feedback control as a theory of motor coordination},
volume = 5,
year = 2002
}