The temporal dynamics of visual attention

• Published in: Journal of experimental psychology. General Vol. 154; no. 2; p. 435
• Main Authors: Zhang, Han, Sellers, Jacob, Lee, Taraz G, Jonides, John
• Format: Journal Article
• Language: English
• Published: United States 01.02.2025
• Subjects: Adult; Attention - physiology; Female; Humans; Male; Reaction Time - physiology; Saccades - physiology; Time Factors; Visual Perception - physiology; Young Adult
• DOI: 10.1037/xge0001661

Researchers have long debated how humans select relevant objects amid physically salient distractions. An increasingly popular view holds that the key to avoiding distractions lies in suppressing the attentional priority of a salient distractor. However, the precise mechanisms of distractor suppression remain elusive. Because the computation of attentional priority is a time-dependent process, distractor suppression must be understood within these temporal dynamics. In four experiments, we tracked the temporal dynamics of visual attention using a novel forced-response method, by which participants were required to express their latent attentional priority at varying processing times via saccades. We show that attention could be biased either toward or away from a salient distractor depending on the timing of observation, with these temporal dynamics varying substantially across experiments. These dynamics were explained by a computational model assuming the distractor and target priority signals arrive asynchronously in time and with different influences on saccadic behavior. The model suggests that distractor signal suppression can be achieved via a "slow" mechanism in which the distractor priority signal dictates saccadic behavior until a late-arriving priority signal overrides it, or a "fast" mechanism which directly suppresses the distractor priority signal's behavioral expression. The two mechanisms are temporally dissociable and can work collaboratively, resulting in time-dependent patterns of attentional allocation. The current work underscores the importance of considering the temporal dynamics of visual attention and provides a computational architecture for understanding the mechanisms of distractor suppression. (PsycInfo Database Record (c) 2025 APA, all rights reserved).