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Memory for artwork is predictable

delete2023-07-03
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OA
AI
T
Trent Davis
W
Wilma Bainbridge *
DOI:10.1073/pnas.2302389120delete
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Abstract

Abstract

En 中文
Viewing art is often seen as a highly personal and subjective experience. However, are there universal factors that make a work of art memorable? We conducted three experiments, where we recorded online memory performance for 4,021 paintings from the Art Institute of Chicago, tested in-person memory after an unconstrained visit to the Art Institute, and obtained abstract attribute measures such as beauty and emotional valence for these pieces. Participants showed significant agreement in their memories both online and in-person, suggesting that pieces have an intrinsic memorability based solely on their visual properties that is predictive of memory in a naturalistic museum setting. Importantly, ResMem, a deep learning neural network designed to estimate image memorability, could significantly predict memory both online and in-person based on the images alone, and these predictions could not be explained by other low-or high -level attributes like color, content type, aesthetics, and emotion. A regression comprising ResMem and other stimulus factors could predict as much as half of the variance of in-person memory performance. Further, ResMem could predict the fame of a piece, despite having no cultural or historical knowledge. These results suggest that perceptual features of a painting play a major role in influencing its success, both in memory for a museum visit and in cultural memory over generations.
Keywords:
memorability
naturalistic memory
art
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Journal

P
Proceedings of the National Academy of Sciences of the United States of America
IF:
9.1
Papers:
10.8W
Citations:
73.5W

Organization

U
university of chicago
Scholars:
4.4W
Papers: 3.7W
Citations: 80