Optimality principles in sensorimotor control. Todorov, E. Nat Neurosci, 7(9):907-15, 2004. doi abstract bibtex The sensorimotor system is a product of evolution, development, learning and adaptation-which work on different time scales to improve behavioral performance. Consequently, many theories of motor function are based on 'optimal performance': they quantify task goals as cost functions, and apply the sophisticated tools of optimal control theory to obtain detailed behavioral predictions. The resulting models, although not without limitations, have explained more empirical phenomena than any other class. Traditional emphasis has been on optimizing desired movement trajectories while ignoring sensory feedback. Recent work has redefined optimality in terms of feedback control laws, and focused on the mechanisms that generate behavior online. This approach has allowed researchers to fit previously unrelated concepts and observations into what may become a unified theoretical framework for interpreting motor function. At the heart of the framework is the relationship between high-level goals, and the real-time sensorimotor control strategies most suitable for accomplishing those goals.
@Article{Todorov2004,
author = {Emanuel Todorov},
journal = {Nat Neurosci},
title = {Optimality principles in sensorimotor control.},
year = {2004},
number = {9},
pages = {907-15},
volume = {7},
abstract = {The sensorimotor system is a product of evolution, development, learning
and adaptation-which work on different time scales to improve behavioral
performance. Consequently, many theories of motor function are based
on 'optimal performance': they quantify task goals as cost functions,
and apply the sophisticated tools of optimal control theory to obtain
detailed behavioral predictions. The resulting models, although not
without limitations, have explained more empirical phenomena than
any other class. Traditional emphasis has been on optimizing desired
movement trajectories while ignoring sensory feedback. Recent work
has redefined optimality in terms of feedback control laws, and focused
on the mechanisms that generate behavior online. This approach has
allowed researchers to fit previously unrelated concepts and observations
into what may become a unified theoretical framework for interpreting
motor function. At the heart of the framework is the relationship
between high-level goals, and the real-time sensorimotor control
strategies most suitable for accomplishing those goals.},
doi = {10.1038/nn1309},
keywords = {Adaptation, Afferent Pathways, Algorithms, Animals, Arm, Artifacts, Central Nervous System, Computer Simulation, Efferent Pathways, Extramural, Feedback, Humans, Linear Models, Models, Movement, N.I.H., Neurological, Normal Distribution, P.H.S., Physiological, Psychomotor Performance, Research Support, Stochastic Processes, U.S. Gov't, 15332089},
}
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