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Updated: Jun 6, 2026
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Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity
Published on: March 18, 2019
Knowing the future: partial foreknowledge effects on the programming of prosaccades and antisaccades
Mathias Abegg1, Dara S Manoach, Jason J S Barton
1University Eye Hospital, Department of Ophthalmology, Inselspital, University of Bern, Switzerland. mhabegg@hispeed.ch
Vision Research
|November 25, 2010
Summary
Knowing parts of a future trial improves performance. Response foreknowledge significantly boosts saccadic efficiency, similar to complete foreknowledge, while stimulus location knowledge offers no benefit.
Area of Science:
- Cognitive Neuroscience
- Experimental Psychology
Background:
- Behavioral responses can be optimized with foreknowledge of upcoming trials.
- Partial foreknowledge, where some but not all trial aspects are known, is systematically investigated.
Purpose of the Study:
- To investigate the benefits of partial foreknowledge on behavioral responses.
- To determine how different types of foreknowledge impact saccadic efficiency and switch costs.
Main Methods:
- Utilized an ocular motor paradigm with horizontal prosaccades and antisaccades.
- Created three partial foreknowledge conditions (stimulus location, task set, response direction) contrasted with no-foreknowledge and complete foreknowledge.
Main Results:
- Foreknowledge about stimulus location had no effect on saccadic efficiency.
- Foreknowledge about task set had a moderate effect, while response foreknowledge was as effective as complete foreknowledge.
- Foreknowledge differentially affected efficiency, with response foreknowledge yielding the greatest benefit.
Conclusions:
- Partial foreknowledge differentially impacts efficiency, suggesting preparatory activation of motor schemas.
- Response foreknowledge is particularly effective, enhancing performance on both switched and repeated trials.
- Findings support the role of predictive processing in optimizing motor control.
