From seeing to remembering: Images with harder-to-reconstruct representations leave stronger memory traces

These authors jointly supervised this work. Correspondence should be addressed to these authors. Abstract Much of what we remember is not due to intentional selection, but simply a by-product of perceiving. This raises a foundational question about the architecture of the mind: How does perception interface with and influence memory? Here, inspired by a classic proposal relating perceptual processing to memory durability, the level-of-processing theory, we present a sparse coding model for compressing feature embeddings of images, and show that the reconstruction residuals from this model predict how well images are encoded into memory. In an open memorability dataset of scene images, we show that reconstruction error not only explains memory accuracy but also response latencies during retrieval, subsuming, in the latter case, all of the variance explained by powerful vision-only models. We also confirm a prediction of this account with'model-driven psychophysics'. This work establishes reconstruction error as a novel signal interfacing perception and memory, possibly through adaptive modulation of perceptual processing. Introduction So much of what we remember is not the result of intentional selection, but rather the result of simply perceiving. How are perceptual experiences cast into memory? And how does perceiving exert control over remembering?