Statistical learning of distractor locations is dependent on task context

Jasper de Waard*, Dirk van Moorselaar, Louisa Bogaerts, Jan Theeuwes

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Through statistical learning, humans can learn to suppress visual areas that often contain distractors. Recent findings suggest that this form of learned suppression is insensitive to context, putting into question its real-life relevance. The current study presents a different picture: we show context-dependent learning of distractor-based regularities. Unlike previous studies which typically used background cues to differentiate contexts, the current study manipulated task context. Specifically, the task alternated from block to block between a compound search and a detection task. In both tasks, participants searched for a unique shape, while ignoring a uniquely colored distractor item. Crucially, a different high-probability distractor location was assigned to each task context in the training blocks, and all distractor locations were made equiprobable in the testing blocks. In a control experiment, participants only performed a compound search task such that the contexts were made indistinguishable, but the high-probability locations changed in exactly the same way as in the main experiment. We analyzed response times for different distractor locations and show that participants can learn to suppress a location in a context-dependent way, but suppression from previous task contexts lingers unless a new high-probability location is introduced.

Original languageEnglish
Article number11234
Pages (from-to)1-12
Number of pages12
JournalScientific Reports
Volume13
DOIs
Publication statusPublished - 11 Jul 2023

Bibliographical note

Funding Information:
All authors were supported by a European Research Council (ERC) advanced grant 833029 – [LEARNATTEND]. LB was also supported by an Odysseus grant from Research Foundation Flanders (FWO) [G0F3121N].

Publisher Copyright:
© 2023, The Author(s).

Funding

All authors were supported by a European Research Council (ERC) advanced grant 833029 – [LEARNATTEND]. LB was also supported by an Odysseus grant from Research Foundation Flanders (FWO) [G0F3121N].

FundersFunder number
European Research Council
Horizon 2020 Framework Programme833029
Fonds Wetenschappelijk OnderzoekG0F3121N

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