TY - JOUR
T1 - Computational mechanisms of sensorimotor control
AU - Franklin, David W.
AU - Wolpert, Daniel M.
N1 - Funding Information:
This work was supported by the Wellcome Trust.
PY - 2011/11/3
Y1 - 2011/11/3
N2 - In order to generate skilled and efficient actions, the motor system must find solutions to several problems inherent in sensorimotor control, including nonlinearity, nonstationarity, delays, redundancy, uncertainty, and noise. We review these problems and five computational mechanisms that the brain may use to limit their deleterious effects: optimal feedback control, impedance control, predictive control, Bayesian decision theory, and sensorimotor learning. Together, these computational mechanisms allow skilled and fluent sensorimotor behavior.
AB - In order to generate skilled and efficient actions, the motor system must find solutions to several problems inherent in sensorimotor control, including nonlinearity, nonstationarity, delays, redundancy, uncertainty, and noise. We review these problems and five computational mechanisms that the brain may use to limit their deleterious effects: optimal feedback control, impedance control, predictive control, Bayesian decision theory, and sensorimotor learning. Together, these computational mechanisms allow skilled and fluent sensorimotor behavior.
UR - http://www.scopus.com/inward/record.url?scp=83455172803&partnerID=8YFLogxK
U2 - 10.1016/j.neuron.2011.10.006
DO - 10.1016/j.neuron.2011.10.006
M3 - Review article
C2 - 22078503
AN - SCOPUS:83455172803
SN - 0896-6273
VL - 72
SP - 425
EP - 442
JO - Neuron
JF - Neuron
IS - 3
ER -