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Attending is not enough: Responding to targets is needed for across-trial statistical learning
Ai-Su Li1,2, Dirk van Moorselaar3, Jan Theeuwes3,4
1Department of Psychology, Soochow University, Suzhou, China. aisuli.psy@gmail.com.
Attention, Perception & Psychophysics
|August 30, 2024
Summary
Statistical learning of across-trial regularities requires active response execution to both targets in a pair. Simply attending to target locations is insufficient for this type of learning to occur.
Area of Science:
- Cognitive Psychology
- Perception and Attention
- Human Learning
Background:
- Observers can learn across-trial regularities, demonstrated by faster responses to predicted target locations.
- Previous research indicated learning occurred when responses were made to both targets in a predictive pair.
Purpose of the Study:
- To investigate whether active response execution to both targets in a pair is necessary for across-trial regularity learning.
- To determine if merely attending to target locations is sufficient for statistical learning.
Main Methods:
- Participants performed a visual search task for a shape singleton target, responding to an internal feature.
- Two across-trial regularities concerning target locations were implemented.
- Experiments manipulated response requirements, with some pairs requiring responses to both targets and others to only one.
Main Results:
- Across-trial learning occurred only when responses were required for both targets in a predictive pair (Experiment 1).
- Withholding a response to one target in a pair prevented learning.
- This learning deficit was not due to carry-over inhibition, as learning persisted when response requirements were later altered (Experiment 2).
Conclusions:
- The execution of a simple motor response to both targets in a pair is essential for across-trial statistical learning.
- Attentional capture by target locations alone does not facilitate this form of learning.
- Active response engagement is a critical factor in learning sequential environmental regularities.
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