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

Abstract

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 ...

Accounting for the build-up of proactive interference across lists in a list length paradigm reveals a dominance of item-noise in recognition memory

“…In its standard form, the Osth and Dennis (2015) model does not account for prior lists that are part of the same experiment. Regardless, the conclusions of Osth and Dennis (2015) were reinforced when the model was expanded to account for source memory data (Osth, Fox, McKague, Heathcote & Dennis, 2018), and when the model was integrated with the diffusion decision model (DDM; Ratcliff, 1978) to account for response times (RTs) and various effects (e.g., LLE, test position effect) simultaneously (Osth, Jansson et al, 2018).…”

Global matching models of recognition memory

“…The null list-strength effect has been replicated numerous times across different memory labs (Kahana, Rizzuto, & Schneider, 2005;Murnane & Shiffrin, 1991a, 1991bRatcliff, McKoon, & Tindall, 1994;Ratcliff et al, 1992;Yonelinas, Hockley, & Murdock, 1992). It has even been found in other memory tasks, such as associative recognition , cued recall (Wilson & Criss, 2017), and source memory (Osth, Fox, McKague, Heathcote, & Dennis, 2018). A mathematical analysis by Shiffrin, Ratcliff, and of the existing memory models found that none of the models at the time yielded the correct predictions about the list-strength paradigm.…”

“…Item noise exerted only a negligible influence on words and natural scenes, while there were larger influences for visually confusable stimuli such as faces and fractal images. Moreover, in recent years the model was extended to complete RT distributions (Osth, Jansson, et al, 2018) and to source memory (Osth, Fox, et al, 2018) -the introductions of each of these constraints did not change the original conclusions, reinforcing the idea that forgetting in recognition memory is caused by memories acquired prior to the list episode.…”

Global semantic similarity effects in recognition memory: Insights from BEAGLE representations and the diffusion decision model

“…Fox et al (2019) replicated the findings of Brandt et al (2019) with word stimuli and modeled the increase in interference in lists across a session using the Osth and Dennis model, which is a global matching model that is able to decompose performance into the contributions of item-noise and noise from pre-experimental sources, namely context-noise and background-noise. Previous investigations using the model have found a dominance of pre-experimental interference in recognition memory (Osth & Dennis, 2015;Osth, Fox, McKague, Heathcote, & Dennis, 2018;Osth, Jansson, et al, 2018). However, none of these investigations considered the buildup of interference within a session, meaning there was no distinction made between short lists that were tested first (which are advantaged over long lists) or short lists that were tested after long lists (which perform comparably to longer lists).…”