August 2023
Volume 23, Issue 9
Open Access
Vision Sciences Society Annual Meeting Abstract  |   August 2023
How we learn to ignore singleton distractors: Suppressing saliency signals or specific features?
Author Affiliations & Notes
  • Isaac Savelson
    The Ohio State University
  • Andrew B. Leber
    The Ohio State University
  • Footnotes
    Acknowledgements  This work was supported by NSF BCS-2021038 to ABL
Journal of Vision August 2023, Vol.23, 5753. doi:
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      Isaac Savelson, Andrew B. Leber; How we learn to ignore singleton distractors: Suppressing saliency signals or specific features?. Journal of Vision 2023;23(9):5753.

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      © ARVO (1962-2015); The Authors (2016-present)

  • Supplements

Humans have an impressive ability to engage feature-based suppression to avoid processing irrelevant information. However, when the irrelevant information is salient, it is unclear whether feature suppression is sufficient to avoid distraction, or if an additional suppression of saliency signals is necessary. To test between these alternatives, we employed the learned distractor rejection paradigm (Vatterott and Vecera, 2012). With this paradigm, we can examine what conditions are sufficient for individuals to learn to suppress salient, irrelevant distractors. Participants searched for a consistent target across pairs of learning and test blocks. We manipulated the salience of the to-be-ignored distractors during the learning block, as follows. In singleton blocks, we presented a single salient distractor; in tripleton blocks, we presented three non-salient distractors. Test blocks always contained singleton distractors and shared the distractor feature (color) of the corresponding learning block. In all cases, distractors were presented on half of trials. If rejection of a salient item requires experience with salience, then greater attentional capture should be observed in test blocks following a tripleton learning block. If, however, experience with the distractor feature is sufficient to learn rejection of a salient distractor, then attentional capture should be equal across learning conditions. Results showed that, in the singleton learning blocks, we replicated the attenuation of capture over time, albeit with a smaller effect size than was originally reported. Singleton presence costs were significantly smaller in test blocks compared to the singleton learning block, indicating learned distractor rejection. However, test blocks did not significantly differ as a function of the associated learning block condition. In fact, singleton presence costs were numerically larger following a singleton than a tripleton learning block. These results indicate that experience with non-salient distractor features is sufficient to elicit learned rejection of salient distractors.


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