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Decoding go/no-go decisions from eye movements.

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Human Motor Control

Background:

  • Neural activity in eye-movement control areas predicts perceptual decisions.
  • Real-world decisions often involve characteristic eye-movement behaviors.

Purpose of the Study:

  • To investigate if human eye-movement kinematics can predict decision outcomes in a go/no-go task.
  • To assess the sensitivity of eye movements as a readout of internal decision-making.

Main Methods:

  • Participants (n=45) performed a rapid interceptive go/no-go task with a disappearing moving target.
  • Eye-position error and targeting-saccade dynamics were analyzed to predict trial-by-trial decisions.

Main Results:

  • Go/no-go decisions were reflected in distinct eye-movement responses.
  • Eye-position error and saccade dynamics predicted decision outcomes with 76% accuracy.
  • Prediction accuracy correlated with decision accuracy across task difficulties.

Conclusions:

  • Eye movements provide a sensitive, continuous readout of internal neural decision-making.
  • Eye-movement kinematics reflect decision-task requirements in human observers.
  • This study links motor control signals to perceptual decision outcomes.