Ten simple rules to study distractor suppression

Wöstmann, Malte; Störmer, Viola S.; Obleser, Jonas; Addleman, Douglas A.; Andersen, Søren H.; Gaspelin, Nick; Geng, Joy J.; Luck, Steven J.; Noonan, MaryAnn P.; Slagter, Heleen A.; Theeuwes, Jan · 2021 · OpenAlex-citations

DOI: 10.31234/osf.io/vu2k3

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Summary

This paper addresses the lack of a unified framework for studying distractor suppression, a critical component of selective attention that filters out task-irrelevant information. Despite growing interest in how the brain suppresses distractions, progress has been hindered by conflicting definitions, undefined concepts, and methodological inconsistencies across sub-disciplines. To resolve these issues, the authors propose ten simple rules designed to standardize experimental design, distinguish between types of suppression, and clarify statistical and theoretical evaluations. The goal is to facilitate communication between fields and advance the establishment of coherent models of selective attention. The authors organize the rules into three categories. Rules 1–3 focus on experimental design, emphasizing that researchers must first verify that a stimulus has the potency to distract, often by comparing performance in distractor-present versus distractor-absent trials or using independent detection tasks. Crucially, Rule 2 mandates that distractors and targets be manipulated independently to isolate suppression from target enhancement, a common confound in spatial attention studies. Rule 3 requires demonstrating that distractor processing falls below a neutral baseline, rather than merely showing reduced interference, to confirm true suppression. Rules 4–6 distinguish between intention-driven suppression (based on explicit instructions) and experience-driven suppression (learned through statistical regularities or inter-trial priming), urging researchers to isolate these mechanisms. Rules 7–10 address theoretical models, statistical considerations, and the translation of laboratory findings to ecologically valid scenarios. Key findings and recommendations include the necessity of orthogonal manipulation of targets and distractors to unambiguously attribute neural or behavioral effects to suppression. The paper highlights that many studies fail to demonstrate true suppression because they lack a proper baseline, potentially conflating suppression with the upweighting of target features. It also clarifies that learned suppression can arise from short-term priming or long-term statistical learning, requiring careful experimental controls to distinguish these sources. The authors note that while some neural markers, such as the distractor positivity component, are associated with suppression, they do not always provide direct evidence of below-baseline processing without corroborating data. The significance of this work lies in its provision of a comprehensive, actionable framework for future research. By adhering to these rules, researchers can avoid common pitfalls, such as misinterpreting non-distracting stimuli as suppressed or conflating enhancement with suppression. This standardization is expected to improve the integration of empirical findings into coherent theories of attention, enhance reproducibility, and foster collaboration across diverse sub-disciplines studying cognitive control and neural mechanisms of distraction.

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• attention selective divided