August 2023
Volume 23, Issue 9
Open Access
Vision Sciences Society Annual Meeting Abstract  |   August 2023
Expectations Versus Reality: The Effect of Semantic Knowledge on Statistical Learning
Author Affiliations
  • Laura Sikun Li
    Queen's University
  • Hannah Lum Smith
    Queen's University
  • Karolina Krzyś
    Queen's University
  • Carrick C. Williams
    California State University San Marcos
  • Monica S. Castelhano
    Queen's University
Journal of Vision August 2023, Vol.23, 4758. doi:
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      Laura Sikun Li, Hannah Lum Smith, Karolina Krzyś, Carrick C. Williams, Monica S. Castelhano; Expectations Versus Reality: The Effect of Semantic Knowledge on Statistical Learning. Journal of Vision 2023;23(9):4758.

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

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Throughout our daily lives, we are constantly perceiving a flow of visual information. Previous research has shown that we extract frequencies and similarities (i.e., statistical learning) to help us understand and organise incoming information. Statistical learning can be used to increase efficiency in visual search tasks (Jiang & Sisk, 2019), but it is unclear how that learning is affected by prior knowledge about the world. In the present study, we investigated the effect of semantic knowledge on statistical learning. The experiment consisted of a learning and memory phase. In the learning phase, 129 participants were presented with four objects on a blank background (one per quadrant) and were asked to search for a target object, cued by its picture. Targets appeared in either high or low probability locations (80% or 20% of trials, respectively). Of theoretical interest, targets were placed in either semantically consistent (e.g., basketball net in upper quadrants) or inconsistent locations (e.g., chandelier in lower quadrants). In the memory phase, participants indicated where each target most often appeared (i.e., the high probability location). We found that participants had slower response times for low compared to high probability locations, which supports previous research. Critically, we found a significant interaction, where participants responded faster overall to targets in semantically consistent than inconsistent locations. These results indicated that where these objects typically appear in the world influenced learning, even when displayed without context. In the memory phase, we found that although accuracy was high for both, it was significantly higher for consistent (87%) than inconsistent (84%) high probability locations. Overall, these findings suggest that learning does not occur in a vacuum. Despite the short learning window, semantic knowledge had a significant influence on learning and performance.


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