An Approximate Binomial Likelihood Theory of Mirror Effects in Episodic Item Recognition Memory

2004 ◽  
Author(s):  
Andrew J. Heathcote
Keyword(s):  
Recognition Memory ◽  
Item Recognition ◽  
Mirror Effects

Tests of a model for source and item recognition memory

2009 ◽  
Author(s):  
Michael J. Hautus ◽  
Caren M. Rotello ◽  
Neil A. MacMillan
Keyword(s):  
Recognition Memory ◽  
Item Recognition

Hippocampal, parahippocampal and occipital-temporal contributions to associative and item recognition memory: an fMRI study

Neuroreport ◽  
2001 ◽  
Vol 12 (2) ◽  
pp. 359-363 ◽  
Author(s):  
A. P. Yonelinas ◽  
J. B. Hopfinger ◽  
M. H. Buonocore ◽  
N. E. A. Kroll ◽  
K. Baynes
Keyword(s):  
Recognition Memory ◽  
Item Recognition ◽  
Fmri Study

scholarly journals ERP correlates of item recognition memory: Effects of age and performance

2009 ◽  
Vol 1250 ◽  
pp. 218-231 ◽  
Author(s):  
David A. Wolk ◽  
N. Mandu Sen ◽  
Hyemi Chong ◽  
Jenna L. Riis ◽  
Scott M. McGinnis ◽  
...  
Keyword(s):  
Recognition Memory ◽  
Item Recognition ◽  
Memory Effects ◽  
And Performance

Relative sparing of item recognition memory in a patient with adult-onset damage limited to the hippocampus

Hippocampus ◽  
2002 ◽  
Vol 12 (3) ◽  
pp. 325-340 ◽  
Author(s):  
A.R. Mayes ◽  
J.S. Holdstock ◽  
C.L. Isaac ◽  
N.M. Hunkin ◽  
N. Roberts
Keyword(s):  
Recognition Memory ◽  
Item Recognition ◽  
Adult Onset

Spatial and stimulus-type tuning in the LEC, MEC, POR, PrC, CA1, and CA3 during spontaneous item recognition memory

Hippocampus ◽  
2013 ◽  
Vol 23 (12) ◽  
pp. 1425-1438 ◽  
Author(s):  
Zachery Beer ◽  
Caroline Chwiesko ◽  
Takashi Kitsukawa ◽  
Magdalena M. Sauvage
Keyword(s):  
Recognition Memory ◽  
Stimulus Type ◽  
Item Recognition

scholarly journals Word frequency and word likeness mirror effects in episodic recognition memory

2006 ◽  
Vol 34 (4) ◽  
pp. 826-838 ◽  
Author(s):  
Andrew Heathcote ◽  
Elizabeth Ditton ◽  
Kristie Mitchell
Keyword(s):  
Recognition Memory ◽  
Word Frequency ◽  
Mirror Effects

scholarly journals The simultaneous recognition of multiple words: A process analysis

2021 ◽  
Author(s):  
Anne Voormann ◽  
Mikhail S. Spektor ◽  
Karl Christoph Klauer
Keyword(s):  
Word Recognition ◽  
Recognition Memory ◽  
Item Recognition ◽  
State Model ◽  
Single Word ◽  
Discrete State ◽  
Single Item ◽  
Word Test ◽  
Paired Word ◽  
Multiple Item

AbstractIn everyday life, recognition decisions often have to be made for multiple objects simultaneously. In contrast, research on recognition memory has predominantly relied on single-item recognition paradigms. We present a first systematic investigation into the cognitive processes that differ between single-word and paired-word tests of recognition memory. In a single-word test, participants categorize previously presented words and new words as having been studied before (old) or not (new). In a paired-word test, however, the test words are randomly paired, and participants provide joint old–new categorizations of both words for each pair. Across two experiments (N = 170), we found better memory performance for words tested singly rather than in pairs and, more importantly, dependencies between the two single-word decisions implied by the paired-word test. We extended two popular model classes of single-item recognition to paired-word recognition, a discrete-state model and a continuous model. Both models attribute performance differences between single-word and paired-word recognition to differences in memory-evidence strength. Discrete-state models account for the dependencies in paired-word decisions in terms of dependencies in guessing. In contrast, continuous models map the dependencies on mnemonic (Experiment 1 & 2) as well as on decisional processes (Experiment 2). However, in both experiments, model comparison favored the discrete-state model, indicating that memory decisions for word pairs seem to be mediated by discrete states. Our work suggests that individuals tackle multiple-item recognition fundamentally differently from single-item recognition, and it provides both a behavioral and model-based paradigm for studying multiple-item recognition.

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