Online versus offline processing of visual feedback in the control of movement amplitude

Khan, Michael A.; Lawrence, Gavin P.; Fourkas, Alissa D.; Franks, Ian M.; Elliott, Digby; Pembroke, Samantha

doi:10.1016/s0001-6918(02)00156-7

Cited by 86 publications

(79 citation statements)

References 25 publications

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“…Once again the adjustments to the limb trajectory were more continuous than discrete, suggesting a graded feedback-based response to the unfolding movement trajectory rather than the implementation of a single corrective submovement (see also Cressman et al, 2006). These sorts of graded adjustments to the primary submovement following perturbations to perceived movement velocity (e.g., Proteau & Masson, 1997) and direction (e.g., Hansen et al, 2007;Saunders & Knill, 2003) are consistent with the large reductions in trial-to-trial spatial variability one normally sees between peak deceleration and the end of the movement when full visual feedback is available (e.g., Hansen, Elliott, & Khan, 2008;Khan, Elliott, Coull, Chua, & Lyons, 2002;Khan et al, 2003;see Khan et al, 2006, for a review). Moreover, they are consistent with the finding that the provision of visual feedback, as early as peak velocity, decreases endpoint aiming error and variability (e.g., Heath, 2005).…”

Section: Early Online Controlmentioning

confidence: 65%

Goal-directed aiming: Two components but multiple processes.

Elliott

Hansen²,

Grierson

et al. 2010

Psychological Bulletin

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351

312

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This article reviews the behavioral literature on the control of goal-directed aiming and presents a multiple-process model of limb control. The model builds on recent variants of Woodworth's (1899) two-component model of speed-accuracy relations in voluntary movement and incorporates ideas about dynamic online limb control based on prior expectations about the efferent and afferent consequences of a planned movement. The model considers the relationship between movement speed and accuracy, and how performers adjust their trial-to-trial aiming behavior to find a safe, but fast, zone for movement execution. The model also outlines how the energy and safety costs associated with different movement outcomes contribute to movement planning processes and the control of aiming trajectories. Our theoretical position highlights the importance of advance knowledge about the sensory information that will be available for online control and the need to develop a robust internal representation of expected sensory consequences. We outline how early practice contributes to optimizing strategic planning to avoid worst-case outcomes associated with inherent neural-motor variability. Our model considers the role of both motor development and motor learning in refining feed-forward and online control. The model reconciles procedural and representational accounts of the specificity-of-learning phenomenon. Finally, we examine the breakdown of perceptual-motor precision in several special populations (i.e., Down syndrome, Williams syndrome, autism spectrum disorder, normal aging) within the framework of a multiple-process approach to goal-directed aiming.

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Section: Early Online Controlmentioning

confidence: 65%

Goal-directed aiming: Two components but multiple processes.

Elliott

Hansen²,

Grierson

et al. 2010

Psychological Bulletin

Self Cite

351

312

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show abstract

“…The discrete visual-processing paradigm tends to emphasize the determination of the minimal feedback loop time that influences the control of movement kinematics, but this approach does not rule out the possible feedforward anticipatory uses of vision (Khan et al, 2003). Indeed, in many tasks, both feedback and feedforward processes are in effect, and so visual motor control involves multiple processes and time scales beyond that of just reflecting the minimal movement time that is uninfluenced by vision (Desmurget & Grafton, 2000;Newell, Slobounov, Slobounova, & Molenaar, 1997).…”

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confidence: 99%

Intermittent visual information and the multiple time scales of visual motor control of continuous isometric force production

Sosnoff

Newell

2005

Perception & Psychophysics

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In an experiment, we examined the effect of intermittency (from 25.6 Hz to 0.2 Hz) of visual information on continuous isometric force production as a function of force level (5%, 10%, 25%, and 50% of maximal voluntary contraction [MVC]). The amount of force variability decreased and the irregularity of force output increased as a function of increased visual intermittency rate. Vision was found to have an influence on the frequency structure of force output up to 12 Hz, and the 25% MVC force level had more high-frequency modulations with higher rates of visual information. The effective use of intermittent visual information is mediated nonlinearly by force level, and there are multiple time scales of visual control (range, ∼0-12 Hz) that are postulated to be a function of both feedback and feedforward control processes.

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“…This type of finding has motivated researchers to consider methodological approaches that do not depend on the identification of discrete discontinuities in aiming profiles. Khan and colleagues have championed an approach to movement analysis that examines trial-to-trial spatial variability as movements unfold (e.g., Khan et al, 2002;Khan et al, 2006;Khan et al, 2003). The primary assumption of this approach is that there is neural-motor noise associated with the execution of any goal-directed movement.…”

Section: Outcome Differencesmentioning

confidence: 99%

“…The general approach taken by Khan and colleagues (Khan et al, 2002;Khan et al, 1998;Khan et al, 2003) has been to examine the standard deviation of the limb's spatial position at the specific kinematic markers mentioned above (i.e., PA, PV, and PD) as well as at the end of the movement. When the movements are made in 3-D space (e.g., Khan et al, 2002), the general procedure has been to use resultant kinematic markers as reference points, but to separately examine spatial variability in the primary direction of the movement (i.e., amplitude variability) and perpendicular to the primary direction of the movement (i.e., directional variability).…”

Section: Discontinuities In the Trajectory And Their Effectivenessmentioning

confidence: 99%

Visual regulation of manual aiming: A comparison of methods

Elliott

Hansen

2010

Behavior Research Methods

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Visual regulation of upper limb movements occurs throughout the trajectory and is not confined to discrete control in the target area. Early control is based on the dynamic relationship between the limb, the target, and the environment. Despite robust outcome differences between protocols involving visual manipulations, it remains difficult to identify the kinematic events that characterize these differences. In this study, participants performed manual aiming movements with and without vision. We compared several traditional approaches to movement analysis with two new methods of quantifying online limb regulation. As expected, participants undershot the target and their movement endpoints were more variable when vision was not available. Although traditional measures such as reaction time, time after peak velocity, and the presence of discontinuities in acceleration were sensitive to the visual manipulation, measures quantifying the trial-to-trial spatial variability throughout the trajectory were the most effective in isolating the time course of online regulation.

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Online versus offline processing of visual feedback in the control of movement amplitude

Cited by 86 publications

References 25 publications

Goal-directed aiming: Two components but multiple processes.

Goal-directed aiming: Two components but multiple processes.

Intermittent visual information and the multiple time scales of visual motor control of continuous isometric force production

Visual regulation of manual aiming: A comparison of methods

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