Amending Ongoing Upper-Limb Reaches: Visual and Proprioceptive Contributions?

in Multisensory Research
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In order to maximize the precise completion of voluntary actions, humans can theoretically utilize both visual and proprioceptive information to plan and amend ongoing limb trajectories. Although vision has been thought to be a more dominant sensory modality, research has shown that sensory feedback may be processed as a function of its relevance and reliability. As well, theoretical models of voluntary action have suggested that both vision and proprioception can be used to prepare online trajectory amendments. However, empirical evidence regarding the use of proprioception for online control has come from indirect manipulations from the sensory feedback (i.e., without directly perturbing the afferent information; e.g., visual–proprioceptive mismatch). In order to directly assess the relative contributions of visual and proprioceptive feedback to the online control of voluntary actions, direct perturbations to both vision (i.e., liquid crystal goggles) and proprioception (i.e., tendon vibration) were implemented in two experiments. The first experiment employed the manipulations while participants simply performed a rapid goal-directed movement (30 cm amplitude). Results from this first experiment yielded no significant evidence that proprioceptive feedback contributed to online control processes. The second experiment employed an imperceptible target jump to elicit online trajectory amendments. Without or with tendon vibration, participants still corrected for the target jumps. The current study provided more evidence of the importance of vision for online control but little support for the importance of proprioception for online limb–target regulation mechanisms.

Multisensory Research

A Journal of Scientific Research on All Aspects of Multisensory Processing



AsheJ.GeorgopoulosA. P. (1994). Movement parameters and neural activity in motor cortex and area 5, Cereb. Cortex 4, 590600.

BagesteiroL. B.SarlegnaF. R.SainburgR. L. (2006). Differential influence of vision and proprioception on control of movement distance, Exp. Brain Res. 171, 358370.

BardC.TurrellY.FleuryM.TeasdaleN.LamarreY.MartinO. (1999). Deafferentation and pointing with visual double-step perturbations, Exp. Brain Res. 125, 410416.

BernierP. M.GauthierG. M.BlouinJ. (2007). Evidence for distinct, differentially adaptable sensorimotor transformations for reaches to visual and proprioceptive targets, J. Neurophysiol. 98, 18151819.

CapadayC.CookeJ. D. (1981). The effects of muscle vibration on the attainment of intended final position during voluntary human arm movements, Exp. Brain Res. 42, 228230.

ChuaR.ElliottD. (1993). Visual regulation of manual aiming, Hum. Mov. Sci. 12, 365401.

ChurchlandM. M.SanthanamG.ShenoyK. V. (2006). Preparatory activity in premotor and motor cortex reflects the speed of the upcoming reach, J. Neurophysiol. 96, 31303146.

CressmanE. K.CameronB. D.LamM. Y.FranksI. M.ChuaR. (2010). Movement duration does not affect automatic online control, Hum. Mov. Sci. 29, 871881.

de GrosboisJ.TremblayL. (2015). Quantifying online visuomotor feedback utilization in the frequency domain, Behav. Res. Meth.

ElliottD.CarsonR. G.GoodmanD.ChuaR. (1991). Discrete vs. continuous visual control of manual aiming, Hum. Mov. Sci. 10, 393418.

ElliottD.HansenS.GriersonL. E. M.LyonsJ.BennettS. J.HayesS. J. (2010). Goal-directed aiming: two components but multiple processes, Psychol. Bull. 136, 10231044.

ErnstM. O.BülthoffH. H. (2004). Merging the senses into a robust percept, Trends Cogn. Sci. 8, 162169.

FittsP. M. (1954). The information capacity of the human motor system in controlling the amplitude of movement, J. Exp. Psychol. 47, 381391.

GardnerE. P.JohnsonK. O. (2013). The somatosensory system: receptors and central pathways, in: Principles of Neural Science, Vol. 5, KandelE. R.SchwartzJ. H.JessellT. M.SiegelbaumS. A.HudspethA. J. (Eds), pp.  475495. McGraw-Hill, New York, NY, USA.

GhezC.GordonJ.GhilardiM. F. (1995). Impairments of reaching movements in patients without proprioception. II. Effects of visual information on accuracy, J. Neurophysiol. 73, 361372.

GoodaleM.PélissonD.PrablancC. (1986). Large adjustments in visually guided reaching do not depend on vision of the hand or perception of target displacement, Nature 320, 748750.

GoodmanR. (2015). Online multisensory control processes assessed with proprioceptive and visual manipulations, Master’s Thesis, University of Toronto. Retrieved from the University of Toronto T-Space.

GoodwinG. M.McCloskeyD. I.MatthewsP. B. C. (1972). Proprioceptive illusions induced by muscle vibration: contribution by muscle spindles to perception? Science 175, 13821384.

GriersonL. E.ElliottD. (2008). Kinematic analysis of goal-directed aims made against early and late perturbations: an investigation of the relative influence of two online control processes, Hum. Mov. Sci. 27, 839856.

GriersonL. E.ElliottD. (2009). Goal-directed aiming and the relative contribution of two online control processes, Am. J. Psychol. 122, 309324.

HeathM. (2005). Role of limb and target vision in the online control of memory-guided reaches, Mot. Control 9, 281309.

KennedyA.BhattacharjeeA.HansenS.ReidC.TremblayL. (2015). Online vision as a function of real-time limb velocity: another case for optimal windows, J. Mot. Behav. 47, 465475.

KhanM. A.FranksI. M. (2003). Online versus offline processing of visual feedback in the production of component submovements, J. Mot. Behav. 35, 285295.

MilgramP. (1987). A spectacle-mounted liquid-crystal tachistoscope, Behav. Res. Methods Instrum. Comput. 19, 449456.

PolitA.BizziE. (1978). Processes controlling arm movements in monkeys, Science 201, 12351237.

PolitA.BizziE. (1979). Characteristics of motor programs underlying arm movements in monkeys, J. Neurophysiol. 42, 183194.

ProteauL.RoujoulaA.MessierJ. (2009). Evidence for continuous processing of visual information in a manual video-aiming task, J. Mot. Behav. 41, 219231.

RedonC.HayL.VelayJ. L. (1991). Proprioceptive control of goal-directed movements in man, studied by means of vibratory muscle tendon stimulation, J. Mot. Behav. 23, 101108.

Ribot-CiscarE.Rossi-DurandC.RollJ. P. (1998). Muscle spindle activity following muscle tendon vibration in man, Neurosci. Lett. 258, 147150.

RockI.VictorJ. (1964). Vision and touch: an experimentally created conflict between the two senses, Science 143, 594596.

RollJ. P.VedelJ. P. (1982). Kinaesthetic role of muscle afferents in man, studied by tendon vibration and microneurography, Exp. Brain Res. 47, 177190.

RollJ. P.VedelJ. P.RibotE. (1989). Alteration of proprioceptive messages induced by tendon vibration in man: a microneurographic study, Exp. Brain Res. 76, 213222.

RossettiY.DesmurgetM.PrablancC. (1995). Vectorial coding of movement: vision, proprioception, or both? J. Neurophysiol. 74, 457463.

SainburgR. L.PoiznerH.GhezC. (1993). Loss of proprioception produces deficits in interjoint coordination, J. Neurophysiol. 70, 21362147.

SalmoniA. W.SchmidtR. A.WalterC. B. (1984). Knowledge of results and motor learning: a review and critical reappraisal, Psychol. Bull. 95, 355.

SarlegnaF. R.MuthaP. K. (2015). The influence of visual target information on the online control of movements, Vision Res. 110, 144154.

SarlegnaF. R.GauthierG. M.BourdinC.VercherJ. L.BlouinJ. (2006). Internally driven control of reaching movements: a study on a proprioceptively deafferented subject, Brain Res. Bull. 69, 404415.

SaundersJ. A.KnillD. C. (2003). Humans use continuous visual feedback from the hand to control fast reaching movements, Exp. Brain Res. 152, 341352.

ScottS. H.CluffT.LowreyC.TakeiT. (2015). Feedback control during voluntary motor actions, Curr. Opin. Neurobiol. 33, 8594.

SoberS. J.SabesP. N. (2003). Multisensory integration during motor planning, J. Neurosci. 23, 69826992. GrosboisJ. (2015). Why encode limb and body displacements in the velocity domain? Neurophysiological and behavioral evidence, in: Advances in Visual Perception Research, HeinenT. (Ed.), pp.  279292. Nova Science Publishers, Hauppauge, NY, USA.

TremblayL.ProteauL. (1998). Specificity of practice: the case of powerlifting, Res. Q. Exercise Sport 69, 284289.

TremblayL.HansenS.KennedyA.ChengD. T. (2013). The utility of vision during action: multiple visuomotor processes? J. Mot. Behav. 45, 9199.

TremblayL.CrainicV. GrosboisJ.BhattacharjeeA.KennedyA.HansenS.WelshT. N. (2017). An optimal velocity for online limb–target regulation processes? Exp. Brain Res. 235, 2940.

WallaceS. A.NewellK. M. (1983). Visual control of discrete aiming movements, Q. J. Exp. Psychol. 35, 311321.

WolpertD. M.GhahramaniZ. (2000). Computational principles of movement neuroscience, Nat. Neurosci. 3, 12121217.

WoodworthR. S. (1899). Accuracy of voluntary movement, Psychol. Rev. 3, 1114.


  • Depiction of the experimental set-up, including the aiming board and the liquid-crystal goggles and tendon vibrators worn by the participant. The simple target experiment only employed the 30 cm target (filled circle) while the target jump experiment also employed the 27 cm target (dashed circle) used during a target jump trial. The arrows indicate the direction of the positive values along primary (Prim) and secondary (Sec) movement axes.

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  • Results from the single-target experiment. Significant differences for endpoint amplitude in the secondary axis between the no-vibration (A) and vibration condition (B), as well as in the primary axis (C and D).

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  • Results from the target jump experiment. Endpoint amplitude in the no-vibration (A) and vibration conditions (B), reveal significant differences at 1.0 m/s. Time after peak velocity revealed differences in all window conditions for the no-vibration (C), and at 1.0 m/s in the vibration condition (D).

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