Statistical learning of across-trial regularities during serial search

Area of Science:

• Cognitive Psychology
• Visual Perception
• Attention Studies

Background:

• Attention is biased by target and distractor locations.
• Across-trial statistical learning aids visual search, but only shown for parallel search.
• Previous research demonstrated learning of regularities across trials for pop-out targets.

Purpose of the Study:

• Investigate across-trial statistical learning in serial visual search.
• Determine if learned regularities persist when search type changes.
• Explore automatic and implicit learning mechanisms in visual attention.

Main Methods:

• Used a T-among-Ls visual search task.
• Manipulated target salience (color vs. gray) to induce feature vs. serial search.
• Assessed learning of across-trial regularities in target location prediction.

Main Results:

• Participants did not learn across-trial regularities in serial search with gray targets.
• Learning occurred during initial feature search (red targets) and persisted into serial search.
• Learned biases were implicit, as participants were unaware of the regularities.

Conclusions:

• Across-trial statistical learning can occur implicitly during feature search.
• Learned associations create a flexible priority map influencing subsequent search.
• This priority map remains active, affecting search even when task demands change from parallel to serial.