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Volume 14 Supplement 1

Abstracts from the Twenty Second Annual Computational Neuroscience Meeting: CNS*2013

Model-based prediction of fusimotor activity during active wrist movements

BMC Neuroscience volume 14, Article number: O16 (2013) Cite this article

Introduction

Muscle spindles, whose activity is determined by muscle length changes and by fusimotor drive (i.e. γ-drive), provide critical information about movement position and velocity [1]. However, task-dependent fusimotor drive remains largely unknown [2], since no fusimotor neurons have ever been recorded during active, voluntary upper limb movements, whether in animals nor in humans. So far an estimation of γ-drive could only be obtained through an indirect inference of fusimotor activity from observed muscle spindle activity. Our aim was to model the effect of γ-drive on muscle spindles and to simulate voluntary wrist movements for which the spindle responses are empirically known.

Methods

Our conceptually simple computational model (an adaptation of [3]) allows for a direct quantification of γ-drive. A forward calculation predicts spindle responses based on time-varying γ-drive and muscle length changes. This computational model thus links a biomechanical (musculo-tendon) wrist model to length- and γ-drive-dependent transfer functions of group Ia and group II muscle spindles. These transfer functions were calibrated (Figure 1A) with extant data from passive movements in the cat [4].

Figure 1
figure1

A. Fit between passive [4](dotted lines) and simulated (lines) Ia responses during sinusoidal stretch under constant γ D -drive (125 Hz) and 4 different rates of γ S -drive (top to bottom: 125, 75, 50, 0 Hz). B. Simulated Ia responses (left column) during active muscle contraction for 4 different γS-drives (right column): no, phasic, tonic and phasic-tonic drive. * indicates simulated responses similar to empirically observed Ia responses [5].

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Results

Our simulations suggest that (i) empirically observed muscle spindle activity profiles can to a large part be explained by a strongly task-dependent γ-drive (Figure 1B), (ii) observed differences between individual muscle spindle response profiles can be explained by a corresponding variability in the γ-drive (Figure 1B), and (iii) observed phase advance of spindle responses can to a large part be explained by appropriate γ-drive.

Conclusion

Our simulation predicts that γ-drive is strongly modulated and task-dependent and that appropriate γ-drive can explain many empirically observed aspects of group Ia and II muscle spindle responses during active movements.

References

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Author information

Affiliations

  1. CNRS UMR 8194, Université Paris Descartes, Sorbonne Paris Cité, Paris, F-75006, France

    Bernard Grandjean & Marc A Maier

  2. Univ Paris Diderot, Sorbonne Paris Cité, Paris, F-75013, France

    Marc A Maier

Authors
  1. Bernard Grandjean
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  2. Marc A Maier
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Corresponding author

Correspondence to Marc A Maier.

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This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Grandjean, B., Maier, M.A. Model-based prediction of fusimotor activity during active wrist movements. BMC Neurosci 14, O16 (2013). https://doi.org/10.1186/1471-2202-14-S1-O16

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Keywords

  • Muscle Spindle
  • Wrist Movement
  • Movement Position
  • Direct Quantification
  • Forward Calculation

BMC Neuroscience

ISSN: 1471-2202

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