ArticleJournal of vision2026
Characterizing surround suppression with dynamic natural scenes.
Article in Journal of vision, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Distinct mechanisms of contextual modulation for dynamic natural scenes in motion- and scene-selective cortex.Journal of neurophysiology · 2026Article
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2 authors.
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Abstract
Surround suppression refers to the reduction in perceptual sensitivity to a central stimulus caused by its surrounding context. Previous studies have examined this phenomenon mainly with simple stimuli varying only in low-level visual features, leaving it unclear whether the same principles apply to natural scenes. To address this, we investigated surround suppression in complex and dynamic scenes by systematically manipulating categorical similarity and motion congruence between the center and surrounding scenes. Categorical similarity was examined across four levels: identical exemplars, different exemplars of the same basic-level category, different basic-level categories, and different superordinate categories. Motion direction was manipulated by center and surround drifting either in the same or opposite directions. In two experiments, we measured contrast sensitivity for the center scene during a categorization task. We found that the suppression increased as the categorical similarity between the center and the surround decreased, with the strongest suppression observed for different superordinate categories. This finding contrasts with results for simple stimuli, where increasing center-surround similarity increases suppression. Yet, consistent with the findings from simple stimuli, suppression was stronger when the center and surround moved in the same direction. These findings show that contextual modulation in natural vision is governed not only by low-level feature similarity but also by high-level categorical structure. Context-dependent suppression may therefore help the visual system to prioritize coherent, task-relevant information while filtering incongruent input.
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