ArticleJournal of cognitive neuroscience2025
Electroencephalographic Responses to the Number of Objects in Partially Occluded and Uncovered Scenes.
Article in Journal of cognitive neuroscience, 2025. 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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1 citing paper in PubMed.
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2 authors.
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Abstract
Perceptual completion is ubiquitous when estimating properties such as the shape, size, or number of objects in partially occluded scenes. Behavioral experiments showed that the number of hidden objects is underestimated in partially occluded scenes compared with an estimation based on the density of visible objects and the amount of occlusion. It is still unknown at which processing level this (under)estimation of the number of hidden objects occurs. We studied this question using a passive viewing task in which observers viewed a game board that was initially partially occluded and later was uncovered to reveal its hidden parts. We simultaneously measured the electroencephalographic responses to the partially occluded board presentation and its uncovering. We hypothesized that if the underestimation is a result of early sensory processing, it would be observed in the activities of P1 and N1, whereas if it is because of higher level processes such as expectancy, it would be reflected in P3 activities. Our data showed that P1 amplitude increased with numerosity in both occluded and uncovered states, indicating a link between P1 and simple stimulus features. The N1 amplitude was highest when both the initially visible and uncovered areas of the board were completely filled with game pieces, suggesting that the N1 component is sensitive to the overall Gestalt. Finally, we observed that P3 activity was reduced when the density of game pieces in the uncovered parts matched the initially visible parts, implying a relationship between the P3 component and expectation mismatch. Overall, our results suggest that inferences about the number of hidden items are reflected in high-level processing.
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