Theoretical Correlations and Measured Correlations: Relating Recognition and Recall in Four Distributed Memory Models.

Kahana, Michael J.; Rizzuto, Daniel S.; Schneider, Anja

doi:10.1037/0278-7393.31.5.933

Cited by 46 publications

(45 citation statements)

References 84 publications

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“…The process dissociation procedure also relies on the strong assumption that the two processes are stochastically independent of one another; when the assumption is violated, estimates obtained from this procedure are uninterpretable (Curran & Hintzman, 1995;Hillstrom & Logan, 1997). Indeed, it has long been established that there is a correlation between the probability of correct recall and that of correct recognition (Tulving & Wiseman, 1975;Kahana, Rizzuto, & Schneider, 2005), strongly arguing against the process dissociation assumption of independence (item and source memory performance are also correlated; Starns, Rotello, & Hautus, 2014). Finally, even if the assumption of the process dissociation procedure are satisfied, it is insufficient for identifying the relevant processing components (Humphreys, Dennis, Chalmers, & Finnigan, 2000).…”

Section: Chapter 4 Secondary Processes In Recognitionmentioning

confidence: 99%

A dynamic approach to recognition memory.

Cox

Shiffrin

2017

Psychological Review

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ii Acknowledgements First, I extend my thanks to my committee members for their time, consideration, and guidance. I would especially like to thank my advisors, Rich Shiffrin and Mike Jones, for first convincing me to come to Indiana, making me feel welcome, and guiding me into the world I now inhabit. I must also thank Isaiah Harbison, Michael Dougherty, and Sharona Atkins for introducing me to the very idea of mathematical psychology and for teaching me and trusting me. show how the dynamic model can be extended to account for paradigms like associative recognition and list discrimination, leading to another novel test of the presence of recall-like processes. Associative recognition, list discrimination, recognition of similar foils, and source exclusion are all better explained by the formation of a compound cue rather than recall, although source memory is found to be better modeled by a recall process.

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Section: Chapter 4 Secondary Processes In Recognitionmentioning

confidence: 99%

A dynamic approach to recognition memory.

Cox

Shiffrin

2017

Psychological Review

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Section: The List Strength Paradigm: Data and Model Predictionsmentioning

confidence: 99%

“…A number of experiments tested and disconfirmed this prediction: increasing the strength of a set of studied items does not impair performance of the other items on the list for the case of item recognition with word stimuli (Kahana, Rizzuto, & Schneider, 2005;Ratcliff et al, 1990;Ratcliff, McKoon, & Tindall, 1994;Ratcliff, Sheu, & Gronlund, 1992;Shiffrin, Huber, & Marinelli, 1995;Yonelinas, Hockley, & Murdock, 1992) although small effects of list strength have been found with non-word stimuli such as faces and fractals (Norman, Tepe, Nyhus, & Curran, 2008;Osth, Dennis, & Kinnell, 2014). One should note that the free recall task contrasts with recognition memory in that increasing list strength has been shown to substantially impair performance (Malmberg & Shiffrin, 2005;Tulving & Hastie, 1972).…”

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confidence: 99%

The list strength effect in source memory: Data and a global matching model

Osth

Fox

McKague

et al. 2018

Journal of Memory and Language

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A critical constraint on models of item recognition comes from the list strength paradigm, in which a proportion of items are strengthened to observe the effect on the non-strengthened items. In item recognition, it has been widely established that increasing list strength does not impair performance, in that performance of a set of items is unaffected by the strength of the other items on the list. However, to date the effects of list strength manipulations have not been measured in the source memory task. We conducted three source memory experiments where items studied in two sources were presented in a pure weak list, where all items were presented once, and a mixed list, where half of the items in both sources were presented four times. Each experiment varied the nature of the testing format. In Experiment 1, in which each study list was only tested on one task (item recognition or source memory), a list strength effect was found in source memory while a null effect was found for item recognition. Experiments 2 and 3 showed robust null list strength effects when either the test phase (Experiment 2) or the analysis (Experiment 3) was restricted to recognized items. An extension of the Osth and Dennis (2015) model was able to account for the results in both tasks in all experiments by assuming that unrecognized items elicit guess responses in the source memory task and that there was low interference among the studied items. The results were also found to be consistent with a variant of the retrieving effectively from memory model (REM;Shiffrin & Steyvers, 1997) that uses ensemble representations.Keywords: recognition memory; source memory; global matching modelsThe list strength effect in source memory: Data and a global matching model A major distinction in episodic memory research concerns the difference between information about learned content and the context in which it occurred. A common memory failure illustrating this distinction is that people remember a fact or detail but have no memory for where they learned the information. The relationship between memory for content and context is studied in the laboratory using the item recognition and source memory paradigms. In the item recognition paradigm, participants study a list of items and at test are asked to discriminate between studied items (targets) and unstudied items (lures). The source memory paradigm presents participants with a set of items in different sources, such as different font colors, studied locations, or sensory modalities. At test, participants judge which source studied items were presented in.A number of computational models of decision making have been developed to explain the relations between item and source memory (e.g.; Banks, 2000;Batchelder & Riefer, 1990; DeCarlo, 2003;Yonelinas, 1999; Hautus, Macmillan, & Rotello, 2008; Glanzer, Hilford, & Kim, 2004;Klauer & Kellen, 2010;Slotnick & Dodson, 2005). These models fall into several frameworks including multivariate signal detection theory, in which participants make ...

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“…Note that this theory-based prediction does not lead to zROC slopes less than 1.0, as was reported by several investigators with lists of verbal items. In order to produce zROC slopes less than 1.0, an additional factor-such as variability in attention or goodness of encoding (see, e.g., Kahana, Rizzuto, & Schneider, 2005)-must be considered. Arguably, with verbal items, variability in goodness of encoding-particularly in long lists-would be greater than the variability associated with stimuli like those used in the present experiments.…”

Section: Learning From the Form Of Rocsmentioning

confidence: 99%

Recognition and position information in working memory for visual textures

et al. 2008

Self Cite

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282Working within a framework of exemplar-similarity models of memory (see, e.g., Estes, 1994;Kahana & Sekuler, 2002;Kahana, Zhou, Geller, & Sekuler, 2007;Medin & Schaffer, 1978;Nosofsky, 1986;Nosofsky & Kantner, 2006), we used sinusoidal luminance gratings as stimuli in a modified Sternberg (1966) recognition task. The metric properties of the grating stimuli were exploited to test a novel prediction generated by combining the exemplar-similarity approach with an explicit, signal detection account of decision making (Wickens, 2002).In exemplar-similarity models of recognition memory, it is assumed that a summed-similarity computation is a basic component of subjects' recognition judgment. This computation sums-over all study items-the p's similarity to each of the study items. According to the model, when this sum reaches or exceeds some critical value, the subject will say "yes," judging that the p had been among the n study items that had just been seen. Following convention, we will use the term target (T ) to designate trials on which p replicated a study item and the term lure (L) to designate trials on which p did not replicate any of the study items. On average, the value of summed similarity on T trials will exceed that on L trials, which means that P(yes) responses on T trials will be higher than those on L trials. The nature of the elements entering into the computation will also tend to produce a systematic difference in the variances of summed-similarity values on T and on L trials, which leads to an unexpected prediction for the slope of z-transformed receiver operating characteristics(zROCs).On T trials, values of summed similarity arise from two quantitatively different sources that differ in their respective variability. The first, far larger source of variability reflects the contribution of the n 1 study items that are not replicated by p. Random selection of study items from a stimulus pool means that some of n 1 study items will be similar to p, and that others will be very different from p. As a result of this random divergence, these n 1 nonmatching study items will contribute a highly variable amount of similarity to the summed-similarity signal for any trial. The second, smaller source of variability in summed similarity on T trials reflects the contribution of the one study item that the p does replicate. Over trials, this study item's representation will tend to be perceptually similar to p-even with the memorial noise postulated by the model. Because that study item and p are physically identical, they are likely to be perceptually similar, despite the random noise associated with the study item's memorial representation. As a result, similarity between this study item and p will vary over a narrow range clustered near 1.0 (Zhou, Kahana, & Sekuler, 2004). In three experiments, we examined connections between item-recognition memory and memory for itemposition information. With sequences of compound gratings as study and probe items, subjects made either itemposition judgments (Experim...

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Theoretical Correlations and Measured Correlations: Relating Recognition and Recall in Four Distributed Memory Models.

Cited by 46 publications

References 84 publications

A dynamic approach to recognition memory.

A dynamic approach to recognition memory.

The list strength effect in source memory: Data and a global matching model

Recognition and position information in working memory for visual textures

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