Our memory is largely a product of perception, raising a fundamental question about the mind’s structure: How does perception influence memory and shape it?
A computational model and behavioral study developed by Yale scientists suggests a new clue to this age-old question.
Ilker Yildirim, an assistant professor of psychology in Yale’s Faculty of Arts and Sciences and senior author of the paper, said, “The mind prioritizes remembering things that it cannot explain very well. It might be ignored if a scene is predictable and not surprising.”
For instance, seeing a fire hydrant in a far-off natural setting could momentarily perplex someone, making the image more memorable because it is harder to understand. The study combined a behavioral investigation with a computational model of scene complexity to investigate which visual information is remembered.
The study employed a unique approach, constructing a computational model that focused on the compression and reconstruction of visual information, two crucial processes in memory development.
They used this model to guide the design of a set of tests in which participants were asked to recall individual images from a rapid stream of natural images. The Yale team discovered that participants were more likely to remember an image if it was more difficult for the computational model to rebuild.
John Lafferty, the John C. Malone Professor of Statistics and Data Science at Yale, said, “We used an AI model to try to shed light on people’s perception of scenes—this understanding could help in the development of more efficient memory systems for AI in the future.”
Journal Reference:
- Lin, Q., Li, Z., Lafferty, J. et al. Images with harder-to-reconstruct visual representations leave stronger memory traces. Nat Hum Behav (2024). DOI: 10.1038/s41562-024-01870-3
