Published July 3, 2023 | Version v1
Journal article Open

Memory for artwork is predictable

  • 1. University of Chicago

Description

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.

Data availability

Data (csv files) have been deposited in Memorability of Art, on the Open Science Framework (https://osf.io/vhp5d/).

Files

Memory-for-artwork-is-predictable.pdf

Files (1.1 MB)

Name Size Download all
Artlicle
md5:e2eef184843277d2282157c416862e7e
932.5 kB Preview Download
Supporting information
md5:46fcbee547816f6d60b7b834275b6f1b
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Additional details

Identifiers

DOI
10.1073/pnas.2302389120
Other
oai:uchicago.tind.io:6631

UChicago Information

Division(s)
Social Sciences Division
Department(s)
Psychology