- Oral presentation
- Open Access
Model-based prediction of fusimotor activity during active wrist movements
BMC Neuroscience volume 14, Article number: O16 (2013)
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 . However, task-dependent fusimotor drive remains largely unknown , 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.
Our conceptually simple computational model (an adaptation of ) 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 .
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.
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.
Prochazka A: Proprioceptive feedback and movement regulation. Handbook of Physiology Exercise: Regulation and Integration of Multiple Systems. Bethesda, MD, Am Physiol Soc, sect. 12, part I, p. 89-127
Windhorst U: Muscle spindles are multi-functional (Technical comment). Brain Res Bull. 2008, 75: 507-508. 10.1016/j.brainresbull.2007.11.009.
Maltenfort MG, Burke RE: Spindle model responsive to mixed fusimotor inputs and testable predictions of beta feedback effects. J Neurophysiol. 2003, 89 (5): 2797-2809. 10.1152/jn.00942.2002.
Hulliger M, Matthews PBC, Noth J: Static and dynamic fusimotor action on the response of Ia fibres to low frequency sinusoidal stretching of widely ranging amplitudes. J Physiol (Lond). 1977, 267: 811-836.
Flament D, Fortier PA, Fetz EE: Response patterns and post-spike effects of peripheral afferents in dorsal root ganglia of behaving monkeys. J Neurophysiol. 1992, 67: 875-889.
About this article
Cite this article
Grandjean, B., Maier, M.A. Model-based prediction of fusimotor activity during active wrist movements. BMC Neurosci 14, O16 (2013). https://0-doi-org.brum.beds.ac.uk/10.1186/1471-2202-14-S1-O16
- Muscle Spindle
- Wrist Movement
- Movement Position
- Direct Quantification
- Forward Calculation