Noise in Competing Representations Determines the Direction of Memory Biases

Abstract

Memories are reconstructions, prone to errors. Historically considered a nuisance, memory errors have recently gained attention when found to be systematically shifted away from or toward non-reported items, promising insights into memory mechanisms. We propose that these biases are optimal and inevitable when the brain disentangles overlapping memory signals, predicting that bias direction depends on the noise distribution between memorized items, not just absolute noise levels. We tested this prediction in four color-memory experiments using novel stimuli with independently varied noise levels. The results support our hypothesis: targets with the same absolute noise level can be repelled from or attracted to non-target items, depending on their relative noise levels. We further show that the model can fit nonlinear bias patterns observed in human data with noise levels as the only free parameters. These findings challenge currently dominant models and support signal disentanglement as a unifying explanation of memory biases.