Open AccessA multistage retrieval account of associative recognition ROC curves
Author(s) -
Olya Hakobyan,
Sen Cheng
Publication year - 2021
Publication title -
learning and memory
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.228
H-Index - 136
eISSN - 1549-5485
pISSN - 1072-0502
DOI - 10.1101/lm.053432.121
Subject(s) - associative property , recall , content addressable memory , recognition memory , computer science , pattern recognition (psychology) , artificial intelligence , associative learning , psychology , cognitive psychology , cognition , artificial neural network , mathematics , neuroscience , pure mathematics
Despite its name, associative recognition is a paradigm thought to rely on memory recall. However, it remains unclear how associative information may be represented and retrieved from memory and what its relationship to other information, such as item memory, is. Here, we propose a computational model of associative recognition, where relational information is accessed in a generic, multistage retrieval process. The model explains the relative difficulty of associative recognition compared with item recognition, the difference in experimental outcomes when different types of lures are used, as well as the conditions leading to the emergence of associative ROC curves with different shapes.