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Related Experiment Video

Updated: May 18, 2026

Movement Retraining using Real-time Feedback of Performance

Movement Retraining using Real-time Feedback of Performance

Published on: January 17, 2013

Dynamic estimation of task-relevant variance in movement under risk.

Michael S Landy¹, Julia Trommershäuser, Nathaniel D Daw

¹Department of Psychology and Center for Neural Science, New York University, New York, New York 10003, USA. landy@nyu.edu

The Journal of Neuroscience : the Official Journal of the Society for Neuroscience

|September 14, 2012

Summary

People adjust their movements based on uncertainty, avoiding penalties when risk increases. They dynamically estimate uncertainty using recent movement errors, prioritizing newer information for better decision-making.

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Area of Science:

Neuroscience
Cognitive Science
Motor Control

Background:

Human movement planning incorporates self-generated variability and outcome consequences.
Previous research focused on steady-state responses to movement risk, not dynamic strategy adjustment.

Purpose of the Study:

Investigate how humans dynamically adjust movement strategies under changing uncertainty in a visuomotor task.
Examine if strategy adjustment relies on outcome mean or outcome uncertainty estimates.

Main Methods:

Visuomotor decision task with reward and penalty regions.
Manipulated uncertainty levels during reaching movements.
Analyzed strategy adjustments based on recent outcome uncertainty (squared error).

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Last Updated: May 18, 2026

Movement Retraining using Real-time Feedback of Performance

Movement Retraining using Real-time Feedback of Performance

Published on: January 17, 2013

Estimating Vestibular Perceptual Thresholds Using a Six-Degree-Of-Freedom Motion Platform

Estimating Vestibular Perceptual Thresholds Using a Six-Degree-Of-Freedom Motion Platform

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Setup for the Quantitative Assessment of Motion and Muscle Activity During a Virtual Modified Box and Block Test

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Main Results:

Subjects adopted more conservative movement strategies towards penalty regions when uncertainty increased.
The estimated uncertainty was a weighted average of recent squared errors.
More recent trials received higher weights in the uncertainty estimation.

Conclusions:

Human motor control strategy adjustment is sensitive to outcome uncertainty, not just mean outcomes.
A dynamic estimation of uncertainty, weighting recent errors more heavily, underlies adaptive movement planning.