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Related Experiment Video

Updated: Jun 16, 2026

An Emerging Target Paradigm to Evoke Fast Visuomotor Responses on Human Upper Limb Muscles

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Published on: August 25, 2020

Emergent flexibility in motor learning.

Rajiv Ranganathan¹, Karl M Newell

¹Department of Kinesiology, The Pennsylvania State University, 266 Recreation Building, University Park, PA 16802-6501, USA. rxr259@psu.edu

Experimental Brain Research

|February 13, 2010

Summary

Practicing with less obstacle variability improved performance in virtual interception tasks. This approach enhanced both accuracy and adaptability, suggesting flexibility emerges from learning key task parameters.

Area of Science:

Motor Learning
Cognitive Psychology
Robotics

Background:

Understanding how practice variability influences motor skill acquisition is crucial for optimizing training protocols.
Interceptive tasks require dynamic adjustments to environmental changes.
Exploring redundant solutions during practice may impact performance flexibility.

Purpose of the Study:

To investigate the impact of practice variability on the flexible use of solutions in a virtual interception task.
To determine if practicing with lower variability enhances adaptability to changing task conditions.

Main Methods:

Three groups practiced a virtual interception task with varying degrees of obstacle position variability (low, medium, high).
Participants attempted to hit a stationary target while navigating around a stationary obstacle.

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Post-practice tests included both fixed and variable obstacle conditions.

Main Results:

The low-variability group demonstrated superior accuracy in both fixed and variable obstacle tests.
This group also exhibited reduced path variability in the fixed test and adaptability in the variable test.
Performance flexibility in interceptive tasks appears linked to learning specific task parameters.

Conclusions:

Practicing with lower variability in obstacle positions can lead to more robust and adaptable performance in interceptive tasks.
Flexibility in these tasks may not solely depend on exploring diverse solutions but on mastering critical task-relevant parameters.
Findings suggest optimizing practice design by focusing on essential parameters rather than maximizing solution diversity.