The impact of cognitive load on delayed recall

Camos, Valérie; Portrat, Sophie

doi:10.3758/s13423-014-0772-5

Cited by 81 publications

(106 citation statements)

References 20 publications

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“…These restoration processes can be argued to not only protect representations in WM from decay but to also help establishing long-term memory traces. Whereas articulatory maintenance rehearsal has only a limited effect on long-term memory (Greene, 1987), refreshing has been shown to improve long-term retention (Raye et al, 2007), and providing more time for refreshing during a WM task results in better recall of the memoranda in a delayed test (Camos & Portrat, 2015;Loaiza & McCabe, 2012b) Therefore, the efficiency of refreshing could be a source of common variance of WM and long-term memory. In line with this hypothesis, Loaiza and McCabe (2012a) have argued that age differences in episodic long-term memory can in part be explained by age differences in the efficiency of refreshing.…”

Section: Correlations With Long-term Memory (C3)mentioning

confidence: 99%

What limits working memory capacity?

Oberauer

Farrell

Jarrold

et al. 2016

Psychological Bulletin

253

213

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We review the evidence for the three principal theoretical contenders that vie to explain why and how working memory capacity is limited. We examine the possibility that capacity limitations arise from temporal decay; we examine whether they might reflect a limitation in cognitive resources; and we ask whether capacity might be limited because of mutual interference of representations in working memory. We evaluate each hypothesis against a common set of findings reflecting the capacity limit: The set-size effect and its modulation by domain-specificity and heterogeneity of the memory set; the effects of unfilled retention intervals and of distractor processing in the retention interval; and the pattern of correlates of working-memory tests. We conclude that---at least for verbal memoranda---a decay explanation is untenable. A resource-based view remains tenable but has difficulty accommodating several findings. The interference approach has its own set of difficulties but accounts best for the set of findings, and therefore appears to present the most promising approach for future development.Keywords: working memory, decay, resources, interference, individual differences WM Capacity 3 What Limits Working Memory Capacity?Working memory (WM) is the system that holds mental representations available for processing. Its limited capacity is a limiting factor for the complexity of our thoughts (Halford, Cowan, & Andrews, 2007;Oberauer, 2009). Measures of WM capacity have been identified as major determinants of cognitive development in childhood (Bayliss, Jarrold, Gunn, & Baddeley, 2003) and in old age (Park et al., 2002;Salthouse, 1994), as well as of individual differences in intellectual abilities (Conway, Kane, & Engle, 2003;Jarrold & Towse, 2006). Understanding why WM capacity is limited is therefore an essential step toward understanding why human cognitive abilities are limited, why individuals differ in these abilities, and how abilities develop over the lifespan.In this article we use the term WM capacity in a descriptive sense, referring to the fact that people can hold only a limited amount of mental content available for processing. The capacity limit is usually operationalized as a limit on how much new information people can remember over short periods of time (in the order of seconds), but there are reasons to believe (discussed below) that the capacity limit also applies to people's ability to make information in the current environment simultaneously available for processing.Hypotheses about what limits WM capacity can be organized into three groups: (1) Some theories assume that representations in WM decay over time, unless decay is prevented by some form of restoration process such as rehearsal. According to this view, WM has limited capacity because only a limited amount of information can be rehearsed before it fades away into an irrecoverable state (Baddeley, Thomson, & Buchanan, 1975;Schweickert & Boruff, 1986). (2) Alternatively, WM capacity has been characterized as a limited resourc...

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Section: Correlations With Long-term Memory (C3)mentioning

confidence: 99%

What limits working memory capacity?

Oberauer

Farrell

Jarrold

et al. 2016

Psychological Bulletin

253

213

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“…Focusing briefly on an item enhances its level of activation and thus counteracts memory loss. It has been suggested that these two classic maintenance mechanisms, operating independently on the maintenance of verbal information, affect different features of the memoranda , Camos & Portrat, 2015.…”

Section: Wm Maintenance Mechanisms Contributing To Recall Performancementioning

confidence: 99%

“…New associations are formed between elements concurrently held in the focus of attention resulting in new LTM information that is formed during short-term memory tasks: a chunk. The information that benefits from attentional refreshing may be in a more deeply analyzed form (Cowan & Chen, 2009) and more persistent (Camos & Portrat, 2015) than information that is activated without the involvement of the focus of attention, that is, by articulatory rehearsal. Hence, associations or links between elements, that is, chunks, are stored as a specific function of the focus of attention (Cowan, 1999(Cowan, , 2001(Cowan, , 2005a(Cowan, , 2005b and the focus of attention would be limited to a few chunks at a time (usually three to five chunks in adults; see Cowan, 2001).…”

Section: Wm Maintenance Mechanisms Contributing To Recall Performancementioning

confidence: 99%

Promoting the experimental dialogue between working memory and chunking: Behavioral data and simulation

et al. 2015

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Working memory (WM) is a cognitive system allowing short-term maintenance and processing of information. Maintaining information in WM consists, classically, in rehearsing or refreshing it. Chunking could also be considered as a maintenance mechanism. However, in the literature, it is more often used to explain performance than explicitly investigated within WM paradigms. Hence, the aim of the present paper was (1) to strengthen the experimental dialogue between WM and chunking, by studying the effect of acronyms in a computer-paced complex span task paradigm and (2) to formalize explicitly this dialogue within a computational model. Young adults performed a WM complex span task in which they had to maintain series of 7 letters for further recall while performing a concurrent location judgment task. The series to be remembered were either random strings of letters or strings containing a 3-letter acronym that appeared in position 1, 3, or 5 in the series. Together, the data and simulations provide a better understanding of the maintenance mechanisms taking place in WM and its interplay with long-term memory. Indeed, the behavioral WM performance lends evidence to the functional characteristics of chunking that seems to be, especially in a WM complex span task, an attentional time-based mechanism that certainly enhances WM performance but also competes with other processes at hand in WM. Computational simulations support and delineate such a conception by showing that searching for a chunk in long-term memory involves attentionally demanding subprocesses that essentially take place during the encoding phases of the task.

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“…Bernardin, & Camos, 2004;Barrouillet, Bernardin, Portrat, Vergauwe, & Camos, 2007;Barrouillet, Portrat, & Camos, 2011;Camos & Portrat, 2015;Hudjetz & Oberauer, 2007;Ricker & Cowan, 2010;Vergauwe, Barrouillet, & Camos, 2009; but see Oberauer, Lewandowsky, Farrell, Jarrold, & Greaves, 2012;Oberauer & Lewandowsky, 2013), and (2) increasing the number of times a memory item has been refreshed, by presenting cues prompting participants to think of specific WM items during a retention interval, results in better memory performance for that item (Souza, Rerko, & Oberauer, 2015). In these studies, researchers have focused on the effects of refreshing on memory performance at the end of the trial or at the end of the experimental session.…”

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confidence: 99%