Salient distractions in the environment compete for attention and have the potential to interfere with our goals. An abundance of research has therefore examined how we learn to prevent distraction by salient stimuli. There is growing consensus that salient stimuli can be suppressed to mitigate distraction. However, many questions about distractor suppression have been difficult to resolve in typical studies that use small sample sizes. The current study is a pooled analysis of several previous eye-tracking studies (N = 354) which resulted in a large data set of more than a half-million eye movements. This large data set was used to uncover new findings that improve our understanding of the attentional processes involved in distractor suppression. We also evaluated several new findings related to how attentional suppression is learned and is influenced by selection history. Altogether, these findings highlight the need for a hybrid model of attention that includes both bottom-up and top-down components. Moreover, this large publicly available dataset can be used by future research to investigate other questions related to attentional capture and distractor suppression.
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