A context noise model of episodic word recognition.
Abstract
Item noise models of recognition assert that interference at retrieval is generated by the words from the study list. Context noise models of recognition assert that interference at retrieval is generated by the contexts in which the test word has appeared. The authors introduce the bind cue decide model of episodic memory, a Bayesian context noise model, and demonstrate how it can account for data from the item noise and dual-processing approaches to recognition memory. From the item noise perspective, list strength and list length effects, the mirror effect for word frequency and concreteness, and the effects of the similarity of other words in a list are considered. From the dual-processing perspective, process dissociation data on the effects of length, temporal separation of lists, strength, and diagnosticity of context are examined. The authors conclude that the context noise approach to recognition is a viable alternative to existing approaches.
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Cited by (11)
- Untitled work2013
- Modeling hippocampal and neocortical contributions to recognition memory: a complementary-learning-systems approachNorman, Kenneth A., O'Reilly, Randall C. · 2003 · Psychological Review
- Topics in semantic representationGriffiths, Thomas L., Steyvers, Mark, Tenenbaum, Joshua B. · 2007 · Psychological Review
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- Bayesian hypothesis testing for psychologists: A tutorial on the Savage–Dickey methodWagenmakers, Eric-Jan, Lodewyckx, Tom, Kuriyal, Himanshu, Grasman, Raoul · 2010 · Cognitive Psychology
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A context noise model of episodic word recognition. https://app.cochat.ai/papers/10.1037//0033-295x.108.2.452
- The paper
- Dennis, S., & Humphreys, M. S. (2001). A context noise model of episodic word recognition. Psychological Review. https://doi.org/10.1037//0033-295x.108.2.452
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