Article

Human muscle spindles act as forward sensory models.

Computational and Biological Learning Laboratory, Department of Engineering, University of Cambridge, CB2 1PZ, UK.
Current biology: CB (Impact Factor: 9.92). 10/2010; 20(19):1763-7. DOI: 10.1016/j.cub.2010.08.049
Source: PubMed

ABSTRACT 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.

0 Followers
 · 
126 Views
  • Source
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The idea that intentions make the difference between voluntary and non- voluntary behaviors is simple and intuitive. At the same time, we lack an understanding of how voluntary actions actually come about, and the unquestioned appeal to inten- tions as discrete causes of actions offers little if anything in the way of an answer. We cite evidence suggesting that the origin of actions varies depending on context and effector, and argue that actions emerge from a causal web in the brain, rather than a central origin of intentional action. We argue that this causal web need not be confined to the central nervous system, and that proprioceptive feedback might play a counter- intuitive role in the decision process. Finally we argue that the complex and dynamic origins of voluntary action and their interplay with the brain’s propensity to predict the immediate future are better studied using a dynamical systems approach.
    Review of Philosophy and Psychology 03/2015; in press. DOI:10.1007/s13164-014-0223-2
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: We present a cerebellar architecture with two main characteristics. The first one is that complex spikes respond to increases in sensory errors. The second one is that cerebellar modules associate particular contexts where errors have increased in the past with corrective commands that stop the increase in error. We analyze our architecture formally and computationally for the case of reaching in a 3D environment. In the case of motor control, we show that there are synergies of this architecture with the Equilibrium-Point hypothesis, leading to novel ways to solve the motor error and distal learning problems. In particular, the presence of desired equilibrium lengths for muscles provides a way to know when the error is increasing, and which corrections to apply. In the context of Threshold Control Theory and Perceptual Control Theory we show how to extend our model so it implements anticipative corrections in cascade control systems that span from muscle contractions to cognitive operations.
    Frontiers in Computational Neuroscience 01/2015; 9:39. DOI:10.3389/fncom.2015.00039 · 2.23 Impact Factor

Full-text

Download
66 Downloads
Available from
Jun 3, 2014