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An Emerging Target Paradigm to Evoke Fast Visuomotor Responses on Human Upper Limb Muscles
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Speeded reaching movements around invisible obstacles.

Todd E Hudson1, Uta Wolfe, Laurence T Maloney

  • 1Department of Psychology, New York University, New York, New York, USA. hudson@cns.nyu.edu

Plos Computational Biology
|October 3, 2012
PubMed
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This study models obstacle avoidance using Bayesian decision theory. Human movement planning aligns well with an ideal Bayesian model, especially when considering rewards and noise.

Area of Science:

  • Cognitive Neuroscience
  • Motor Control
  • Decision Theory

Background:

  • Obstacle avoidance is a fundamental aspect of goal-directed movement.
  • Understanding the computational principles underlying human motor control is crucial.

Purpose of the Study:

  • To analyze obstacle avoidance through a Bayesian decision-theoretic lens.
  • To compare human reach performance to a Bayesian ideal movement planner.

Main Methods:

  • Experimental task involving reaching around virtual obstacles on an upright monitor.
  • Subjects received rewards for target acquisition and penalties for obstacle collision.
  • Bayesian ideal movement planner model used for comparison via the Dominance Test.

Main Results:

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Methods to Explore the Influence of Top-down Visual Processes on Motor Behavior
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Methods to Explore the Influence of Top-down Visual Processes on Motor Behavior

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Frame-by-Frame Video Analysis of Idiosyncratic Reach-to-Grasp Movements in Humans
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Frame-by-Frame Video Analysis of Idiosyncratic Reach-to-Grasp Movements in Humans

Published on: January 15, 2018

Related Experiment Videos

Last Updated: May 18, 2026

An Emerging Target Paradigm to Evoke Fast Visuomotor Responses on Human Upper Limb Muscles
09:27

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

Published on: August 25, 2020

Methods to Explore the Influence of Top-down Visual Processes on Motor Behavior
09:49

Methods to Explore the Influence of Top-down Visual Processes on Motor Behavior

Published on: April 16, 2014

Frame-by-Frame Video Analysis of Idiosyncratic Reach-to-Grasp Movements in Humans
10:51

Frame-by-Frame Video Analysis of Idiosyncratic Reach-to-Grasp Movements in Humans

Published on: January 15, 2018

  • Human performance showed good agreement with the Bayesian ideal movement planner model.
  • Deviations from the model were observed in specific experimental conditions.
  • The model accounts for noise inherent in human motor execution.

Conclusions:

  • Bayesian decision theory provides a valuable framework for understanding human obstacle avoidance.
  • The ideal observer model offers insights into optimal motor planning under uncertainty.
  • Further research is needed to explain discrepancies in certain conditions.