Journal article
Learned statistical regularity modulates anticipatory micro-saccades toward suppressed distractor locations
- Abstract:
- Learned statistical regularity enables individuals to suppress locations associated with salient distractors, yet the mechanisms underlying this suppression remain unclear. Proactive accounts propose that suppression operates without prior attentional allocation to distractor locations, whereas reactive accounts suggest that suppression requires covert attention to the distractor location before it can be engaged. To address this ongoing debate, the current study records micro-saccades-an index of covert attention-during the pre-stimulus interval, alongside electroencephalogram (EEG) data collected during a visual search task. Participants are instructed to ignore a salient distractor that occurred more frequently at a specific location, which reduces attentional capture for distractors presented at this high-probability location. Notably, this effect is accompanied by oculomotor markers: micro-saccade rates decrease before stimulus onset relative to a control condition. Strikingly, these anticipatory micro-saccades are more often directed toward high-probability distractor locations than away from them, consistent with a reactive suppression mechanism. In parallel, alpha-band activity (8-14 Hz) carries decodable representations of high-probability distractor locations, indicating preparatory neural tuning. Overall, these findings provide evidence that the oculomotor system is closely involved in encoding and responding to learned spatial regularities.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 1.9MB, Terms of use)
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- Publisher copy:
- 10.1038/s41467-026-73916-1
Authors
- Publisher:
- Nature Research
- Journal:
- Nature Communications More from this journal
- Publication date:
- 2026-06-02
- DOI:
- EISSN:
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2041-1723
- ISSN:
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2041-1723
- Language:
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English
- Keywords:
- Pubs id:
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2429350
- Local pid:
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pubs:2429350
- Source identifiers:
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W7163176395
- Deposit date:
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2026-06-04
- ARK identifier:
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- Copyright date:
- 2026
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