Sensorimotor delays in tracking may be compensated by negative feedback control of motion-extrapolated position

Parker, Maximilian G.; Weightman, Andrew; Tyson, Sarah; Abbott, Bruce; Mansell, Warren

doi:10.1007/s00221-020-05962-0

Cited by 6 publications

(5 citation statements)

References 69 publications

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“…The absence of aftereffects for those participants tracking the variable target motion implies that the VF rotation was not learned. Our results are in line with previous studies showing that learning to track a target moving in a pseudorandom pattern is not possible because both the amplitude and velocity of the target motion changes from one cycle to the next necessitating continuous closed loop control (Parker et al, 2021). It is possible that the sustained perception (feedback) based action for tracking the variable target motion does not allow the development of structural knowledge of the visuomotor rotation.…”

Section: Discussionsupporting

confidence: 92%

Goalkeepers’ plasticity during learning of a whole‐body visuomotor rotation in a stable or variable environment

Vouras

Chatzinikolaou

Sotirakis

et al. 2023

European Journal of Sport Science

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Postural adjustments performed in anticipation of uncertain visual events is a common sensorimotor control problem in open sport skills. In this study, we examined how expert soccer goalkeepers and non-athletes learn a whole body visuomotor rotation during postural tracking of constant and variable visual target motions. Twenty-one (21) soccer goalkeepers (18 ± 15 years, 75 ± 12 kg) and 25 age-matched non-athletes (18 ± 12 years, 75 ± 15 kg) practiced lateral weight shifting on a dual force platform while tracking the motion of a constant (11 goalkeepers and 12 non-athletes) or a variable (10 goalkeepers and 13 non-athletes) visual target with provision of online visual feedback (VF). After 40s of tracking (baseline), the visual presentation of the VF signal reversed direction relative to the participant's motion (180°visuomotor rotation) for 60s (adaptation) and then returned to its veridical direction for another 20s (washout). During adaptation, goalkeepers reduced the spatiotemporal error to baseline levels at an earlier time block (3rd block) compared to non-athletes (6th block), but this difference was significant only for groups tracking of the constant and not the variable target motion. Only the groups tracking the constant target increased the spatiotemporal error during the 1st washout block demonstrating a significant aftereffect. It is concluded that goalkeepers adapt faster to the feedback rotation due to their prior field knowledge of relevant visuomotor transformations in anticipation of deceptive visual cues. This expertise advantage however is present only in a stable visual environment possibly because learning is compromised when tracking uncertain motion cues requiring closed loop control.

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Section: Discussionsupporting

confidence: 92%

Goalkeepers’ plasticity during learning of a whole‐body visuomotor rotation in a stable or variable environment

Vouras

Chatzinikolaou

Sotirakis

et al. 2023

European Journal of Sport Science

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“…Alternatively, path accuracy might be controlled more locally, by perceiving the distance between the cursor and the path, and altering the direction of movement. The velocity of the target itself might play a role, as in one-dimensional sinewave tracking (Parker et al, 2021). An additional control variable in the task might be the center of the oscillation.…”

Section: Discussionmentioning

confidence: 99%

Visuomotor phase-locked loop reproduces elliptic hand trajectories across different rhythms

Matic

2022

Preprint

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A well-known phenomenon in human hand movement is the correlation between speed and curvature, also known as the speed-curvature power law (V≈kCβ). In drawing elliptic shapes, the exponent is often found to be β ≈ -1/3, however it is not clear why the power law appears and why the exponent is near -1/3. More fundamentally, it is not clear how do people track elliptic targets. In answering these questions, I’ve analyzed trajectories of participants’ cursors while they tracked visual targets moving along elliptical paths, across different target speed profiles and cycle frequencies. The speed-curvature power law emerged when drawing ellipses at about 1 Hz or faster, regardless of the target speed profile, and it did not emerge for lower frequency movements. Analysis of the position frequency spectrum shows that the target-cursor trajectory transformation may be seen as a low-pass filter. Comparison of different hypothetical salient features of the visual field shows that phase difference (angular difference between the cursor and the target) and size difference (difference in the sizes of the elliptic paths) are the features most likely used in the task. The next experiment confirmed that phase and size difference could be controlled variables because participants kept them stable even under direct pseudorandom disturbances. A numerical model simulating the sensorimotor processes of the participant, similar to a phase-locked loop, using the visual features of phase and size difference as controlled variables, performed the same target tracking tasks as the participants. When fitted, the model closely replicated position and speed profiles of the participants across all trials, as well as the emergence of the power law at high frequencies. The model also reproduced the trajectories of participants in the experiment with direct pseudorandom disturbances. In conclusion (1) the speed-curvature power law emerges as a side effect of movement system properties, namely low-pass filtering in the sensorimotor loop; (2) people could be tracking elliptical targets by varying the frequency and amplitude of an internal pattern generator until the produced phase and shape size match the target’s phase and shape size. The model generates new hypotheses about the neural mechanisms of rhythmic movement control.

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“…Furthermore, during periodic target tracking such as that used in a circular tracking task, the CNS acquires information (i.e., position and velocity) on target motion by applying an inverse model in which the hand position is compared with the desired target state based on feedback error learning [ 33 , 34 ]. The results of this study suggest that FB control under the VIS(1) target-visible phase prediction is governed more by the prospective forward model than by the retrospective inverse model as the former allows for accurate comparison of the states (position and velocity) of the target and tracer during on-line target tracking movement [ 35 – 38 ]. By contrast, under the target-invisible VIS(2) phase the significance of the FF controller using the inverse model exceeds that of the FB controller using the forward mode because comparison of the tracer and target states is impossible as all target visual information has been removed.…”

Section: Discussionmentioning

confidence: 99%

Visuomotor control of intermittent circular tracking movements with visually guided orbits in 3D VR environment

Choi

Yanagihara

Li³

et al. 2021

PLoS ONE

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The analysis of visually guided tracking movements is important to the understanding of imitation exercises and movements carried out using the human visuomotor control system. In this study, we analyzed the characteristics of visuomotor control in the intermittent performance of circular tracking movements by applying a system that can differentiate between the conditions of invisible and visible orbits and visible and invisible target phases implemented in a 3D VR space. By applying visuomotor control based on velocity control, our study participants were able to track objects with visible orbits with a precision of approximately 1.25 times greater than they could track objects with invisible orbits. We confirmed that position information is an important parameter related to intermittent motion at low speeds (below 0.5 Hz) and that tracked target velocity information could be obtained more precisely than position information at speeds above 0.5 Hz. Our results revealed that the feedforward (FF) control corresponding to velocity was delayed under the visible-orbit condition at speeds over 0.5 Hz, suggesting that, in carrying out imitation exercises and movements, the use of visually presented 3D guides can interfere with exercise learning and, therefore, that the effects of their use should be carefully considered.

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Sensorimotor delays in tracking may be compensated by negative feedback control of motion-extrapolated position

Cited by 6 publications

References 69 publications

Goalkeepers’ plasticity during learning of a whole‐body visuomotor rotation in a stable or variable environment

Goalkeepers’ plasticity during learning of a whole‐body visuomotor rotation in a stable or variable environment

Visuomotor phase-locked loop reproduces elliptic hand trajectories across different rhythms

Visuomotor control of intermittent circular tracking movements with visually guided orbits in 3D VR environment

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