Generalization and false memory in acquired equivalence

Abstract

Memory allows us to remember specific events but also combine information across events to infer new information. New inferences are thought to stem from integrating memories of related events during encoding but can be also generated on-demand, based on separate memories of individual events. Integrative encoding has been argued as dominant in the acquired equivalence paradigm, where people have a tendency to assume that when two faces share one preference, they also share another. A downside may be a loss of source memory, where inferred preferences are mistaken for observed ones. Here, we tested these predictions of the integrative encoding hypothesis across five datasets collected using variations of the acquired equivalence paradigm. Results showed a statistically reliable but numerically small tendency to generalize preferences across faces, with stronger evidence for on-demand inferences at retrieval rather than spontaneous integration during encoding. A newly included explicit source memory test showed that participants differentiated learned from inferred preferences to a high degree, irrespective of whether they generalized preferences across faces. False memory was however increased in participants who made generalization decisions faster, which could be consistent with integrative encoding and/or source monitoring frameworks. The results suggest that generalization in acquired equivalence may result from integrated representations that facilitate new inferences at the expense of source memory, but also demonstrate that on-demand retrieval-based processes may play a larger role in this paradigm than previously thought. Finally, the results indicate that reaction times may be more sensitive than performance as a means to assess representations underlying behavior. More broadly, the study informs current theories of generalization and knowledge representation and provides new insights into how memory biases decisions.