Can I read Feedforward Impedance Control Efficiently Reduce Motor Variability on EtoBox?

Feedforward Impedance Control Efficiently Reduce Motor Variability by Rieko Osu; Ken-ichi Morishige; Hiroyuki Miyamoto; Mitsuo Kawato is a Neuroscience article available to read on EtoBox.

What is Feedforward Impedance Control Efficiently Reduce Motor Variability about?

Despite the existence of neural noise, which leads variability in motor commands, the central nervous system can effectively reduce movement variance at the end effector to meet task requirements. Although online correction based on feedback information is essential for reducing error, feedforward impedance control is another way to regulate motor variability. This Update Article reviews key studies examining the relation between task constraints and impedance control for human arm movement. When a smaller reaching target is given as a task constraint, flexor and extensor muscles are co-activated, and positional variance is decreased around the task constraint. Trial-by-trial muscle activations revealed no on-line feedback correction, indicating that humans are able to regulate their impedance in advance. These results demonstrate that not only on-line feedback correction, but also feedforward impedance control, helps reduce the motor variability caused by internal noise to realize dexterous movements of human arms. A computational model of movement planning considering the presence of signal-dependent noise provides a unifying framework that potentially accounts for optimizing imp

Who reads Feedforward Impedance Control Efficiently Reduce Motor Variability?

Author

Rieko Osu; Ken-ichi Morishige; Hiroyuki Miyamoto; Mitsuo Kawato

Publisher

Elsevier BV

Published

2009

Language

EN

Field

Neuroscience (Life Sciences)