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Associative inference and self-derivation of knowledge involve the same underlying process of relational generalization

Poster Session B - Sunday, March 8, 2026, 8:00 – 10:00 am PDT, Fairview/Kitsilano Ballroom

Lainey Costa¹ (), Cheyna Warner², Dagmar Zeithamova³; ¹University of Oregon

Relational generalization is the ability to infer new information by connecting related information acquired at different times (A relates to B, B relates to C, thus A relates to C). This memory-based inference has been studied using several paradigms, most commonly examining the integration of arbitrary associations of objects. One more naturalistic paradigm is the self-derivation of knowledge task, where participants can integrate two real-world facts that have related information to infer new information. However, because of the rooting in the real world and language understanding, it is not clear to what degree the self-derivation of knowledge task measures the same ability as standard memory inference tasks rather than general semantic memory abilities. Utilizing an individual differences approach, here we tested the degree to which an individual's self-derivation performance can be predicted from their general verbal retrieval abilities and a standard associative inference task with visual objects. Results showed that associative inference and verbal fluency both separately positively predict self-derivation of knowledge. Furthermore, associative inference and verbal fluency predicted self-derivation of knowledge after controlling for individual’s associative memory. Notably, this study is the first to empirically demonstrate that self-derivation and associative inference are underpinned by the same cognitive processes, thus reinforcing the validity of both laboratory measures to assess relational generalization.

Topic Area: LONG-TERM MEMORY: Other