Human muscle spindles act as forward sensory models.
Modern theories of motor control incorporate forward models that combine sensory information and motor commands to predict future sensory states. Such models circumvent unavoidable neural delays associated with on-line feedback control. Here we show that signals in human muscle spindle afferents during unconstrained wrist and finger movements predict future kinematic states of their parent muscle. Specifically, we show that the discharges of type Ia afferents are best correlated with the velocity of length changes in their parent muscles approximately 100-160 ms in the future and that their discharges vary depending on motor sequences in a way that cannot be explained by the state of their parent muscle alone. We therefore conclude that muscle spindles can act as "forward sensory models": they are affected both by the current state of their parent muscle and by efferent (fusimotor) control, and their discharges represent future kinematic states. If this conjecture is correct, then sensorimotor learning implies learning how to control not only the skeletal muscles but also the fusimotor system.
Dimitriou
Michael
M
Computational and Biological Learning Laboratory, Department of Engineering, University of Cambridge, CB2 1PZ, UK.
Edin
Benoni B
BB
D001696:Biomechanical Phenomena; D004576:Electromyography; D006801:Humans; D009068:Movement / Q000502:physiology*; D009470:Muscle Spindles / Q000502:physiology*; D018482:Muscle, Skeletal / Q000166:cytology / Q000502:physiology*