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Updated: May 28, 2026
09:49
Methods to Explore the Influence of Top-down Visual Processes on Motor Behavior
Published on: April 16, 2014
Mechanisms of Visuomotor Interception
Inmaculada Márquez1,2,3, Mario Treviño1
1Laboratorio de Plasticidad Cortical y Aprendizaje Perceptual, Instituto de Neurociencias, Universidad de Guadalajara, Francisco de Quevedo 180, Arcos Vallarta, Guadalajara 44130, Jalisco, Mexico.
Brain Sciences
|May 27, 2026
Summary
Visuomotor interception involves a dynamic interplay between predictive control and online corrections, not solely one or the other. This interaction is crucial for aligning actions with moving targets despite sensory and motor delays.
Area of Science:
- Neuroscience
- Motor Control
- Human Factors
Background:
- Visuomotor interception requires precise action-target alignment under sensory and motor delays.
- This process serves as a model for understanding predictive and feedback-driven control interactions.
Purpose of the Study:
- To review theoretical and empirical findings on visuomotor interception.
- To examine the integration of predictive and online control mechanisms at behavioral and neural levels.
Main Methods:
- Narrative synthesis of behavioral, eye-tracking, computational, and neurophysiological studies.
- Literature search across major databases (PubMed, Web of Science, Google Scholar).
- Comparison of internal model, ecological, and hybrid frameworks, organizing evidence by spatial and temporal control components.
Main Results:
- Interception behavior results from continuous interaction between anticipatory guidance and online correction.
- Spatial and temporal control components show partial dissociation.
- Distributed neural circuits (parietal, frontal, cerebellar, subcortical) and eye movements are actively involved.
Conclusions:
- Interception arises from interacting biological, environmental, and learned constraints.
- Distinct mechanisms can produce similar behavioral outcomes, refuting a single unified account.
- Future progress necessitates integrating behavioral, model-based, and neural approaches.
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