Computational models suggest that human memory judgments exhibit interference due to the use of overlapping representations.

Abstract

Episodic memory is a core function that allows us to remember the events of our lives. Given that many events in our life contain overlapping elements (e.g., similar people and places), it is critical to understand how well we can remember the specific events of our lives versus how susceptible we are to interference between similar memories. Several prominent theories converged on the notion that pattern separation in the hippocampus causes it to play a greater role in processes such as recollection, associative memory, and memory for specific details, while overlapping distributed representations in the neocortex cause it to play a stronger role in domain-specific memory. We propose that studying memory performance on tasks with targets and similar lures provides a critical test bed for comparing the extent to which human memory is driven by pattern separation (e.g., hippocampus) versus more overlapping representations (e.g., neocortex). We generated predictions from several computational models and tested these predictions in a large sample of human participants. We found a linear relationship between memory performance and target-lure pattern similarity within a neural network simulation of inferior temporal cortex, an object-processing region. We also observed strong effects of test format on performance and consistent relationships between test formats. Altogether, our results were better accounted for by distributed memory models at the more linear end of a representational continuum than pattern-separated representations; therefore, our results provide important insight into prominent memory theories by suggesting that recognition memory performance is primarily driven by overlapping representations (e.g., neocortex). (PsycInfo Database Record (c) 2025 APA, all rights reserved).