We developed the Context-Maintenance and Retrieval model for Items and Associations (CMR-IA), a retrieved-context theory of memory for items, associations, and their interaction. Our theory assumes an evolving representation of temporal context that binds to items and associations, allowing the rememberer to make judgments based on the occurrence of a mnemonic target within a particular context. In addition to the assumptions inherited from prior retrieved-context theories, CMR-IA assumes a conjunctive (Gestalt) representation for paired associates, increased attention to rare items, and variable thresholds for recognition decisions.

We applied CMR-IA to key findings concerning recognition of items and associations, including effects of recency, similarity, receiver-operating characteristic curves, word frequency, differential forgettings of items and associations, and contiguity effects for successive probes. We also applied CMR-IA to cued recall phenomena, including serial position effects, distribution of correct responses and errors, contiguity effects, associative symmetry, and similarity effects. Finally, we asked whether CMR-IA can account for the dependencies between successive tests of item and associative memory. We showed that combining a Gestalt associative mechanism with retrieved-context theory provides a unified account for many empirical phenomena concerning item and associative memory.

Paper (submitted)

Poster (presented at CNS2024 & CEMS2024):