Super rapid learning of new attentional sets

TL;DR

The study shows that humans can quickly adapt their attention to new visual targets when the context changes, using memory to update task priorities.

Contribution

The study introduces a novel visual search paradigm to investigate rapid relearning of attentional sets with probabilistic target-color mappings.

Findings

Participants relearned new target-color probabilities faster than their initial learning.

Relearning speed was higher when new and old attentional sets had less conflict.

Memory-guided attention continuously updates task-relevant probabilities.

Abstract

Humans guide attention to different targets as they navigate (e.g., going from a school zone to a construction zone while driving). To understand how observers shift focus between different sets of targets when the context shifts, we had observers perform a new visual search paradigm where target shapes are presented in multiple possible colors with distinct probabilities (e.g., 33%, 26%, 19%, 12%, and 10% baseline colors), such that some target colors are more task-relevant than others. Participants learned to prioritize the target colors that appeared with the target shape most often. We then scrambled the color-probability mapping to assess how quickly people could relearn a new set of target probabilities. Participants relearned these new colors significantly faster than their first set of colors, especially when there was less conflict between the new and old attentional sets. Our findings suggest that memory-guided attention is rapidly and continuously relearning to update task-relevant probabilities.

Figures