How do we perform backward serial recall?

Norris, Dennis; Hall, Jane; Gathercole, Susan E.

doi:10.3758/s13421-018-0889-2

Cited by 20 publications

(32 citation statements)

References 31 publications

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“…Whereas backward recall leads to much lower memory span for verbal stimuli, its impact is minimal when the task involves recalling spatial sequences (Isaacs and Vargha-Khadem, 1989). This raises the possibility that the backward recall of spatial sequences may not involve the effortful and time-consuming peeling-off strategy that can be applied in backward digit span (Norris, Hall, & Gathercole, under review). If this is the case, the routines verbal and visuo-spatial will differ substantially and this will limit transfer.…”

Section: A Cognitive Taxonomy Of Wm Tasksmentioning

confidence: 99%

Working memory training involves learning new skills

Gathercole

Dunning

Holmes

et al. 2019

Journal of Memory and Language

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178

229

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We present a new framework characterizing training-induced changes in WM as the acquisition of novel cognitive routines akin to learning a new skill. Predictions were tested in three studies analyzing the transfer between WM tasks following WM training. Study 1 reports a meta-analysis establishing substantial transfer when trained and untrained tasks shared either a serial recall, complex span or backward span paradigm. Transfer was weaker for serial recall of verbal than visuo-spatial material, suggesting that this paradigm is served by an existing verbal STM system and does not require a new routine. Re-analysis of published WM training data in Study 2 showed that transfer was restricted to tasks sharing properties proposed to require new routines. In a re-analysis of data from four studies, Study 3 demonstrated that transfer was greatest for children with higher fluid cognitive abilities. These findings suggest that development of new routines depends on general cognitive resources and that they can only be applied to other similarly-structured tasks.

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Section: A Cognitive Taxonomy Of Wm Tasksmentioning

confidence: 99%

Working memory training involves learning new skills

Gathercole

Dunning

Holmes

et al. 2019

Journal of Memory and Language

Self Cite

178

229

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“…Both tasks may involve repeated cycles of forward verbal serial recall of diminishing lengths, peeling off the final item each time (Anders & Lillyquist, 1971;Gathercole et al, 2019;Thomas, Milner, & Hanerlandt, 2003). The encoding and retrieval processes required from verbal short-term memory for verbal serial recall are also the same for digits and letters (Norris, Hall, & Gathercole, 2019;Page & Norris, 1998): the system stores verbal material in phonological rather than semantic form (e.g. Salamé & Baddeley, 1982).…”

Section: Discussionmentioning

confidence: 99%

“…These converged on the same key path for the single-factor WM model (MI = 17.976, SRC = 3.894) and two-factor domain model (MI = 149.144, SRC = 3.804), namely a strong residual correlation between the BDR and BLR tasks. On reflection, this residual correlation is to be expected due to both tasks depending on encoding and retrieval processes from verbal short-term memory (Norris, Hall, & Gathercole, 2019). As this system stores verbal material in phonological rather than semantic form (e.g., Salamé & Baddeley, 1982), the processes involved in encoding, maintaining, and retrieving representations from verbal short-term memory should be the same for letters as digits.…”

Section: Primary Analysesmentioning

confidence: 97%

Evidence for separate backward recall and n-back working memory factors: A large-scale latent variable analysis

Byrne¹,

Gilbert²,

Kievit³

et al. 2019

Preprint

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There is growing interest in understanding what constrains transfer following working memory (WM) training with recent studies investigating what limits transfer within and across different WM paradigms. The primary aim of the current study was to conduct a large-scale latent variable analysis to identify distinct properties between WM tasks to provide further insight into task features that might constrain transfer following training. A secondary aim was to explore how the resulting WM factor(s) were linked to Gf. Participants (N = 703) completed multiple web-based versions of n-back and backward recall tasks and a test of non-verbal reasoning. The memory tasks contained different memoranda that varied across (spatial or verbal material) and within (verbal digits or letters) domain, allowing the variance specific to task content and paradigm to be assessed. The data were best-captured by two distinct but related backward recall and n-back constructs, each linked to a separate reasoning factor, in comparison to other plausible model constructions (including a single WM factor, two-factor domain, and three-factor materials model). This suggests these WM tasks measure distinct paradigm-specific processes, but share common variance with one another and with a reasoning task. The benefits of cognitive training targeting a single paradigm are therefore likely to be limited to the same paradigm. For broader transfer it will be necessary to target what is shared across paradigms.

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“…Even at the slowest rate of presentation, the keeping track strategy corresponding to continuous forward-going updating of the target set was reported as being almost always used by only 7 of the 30 participants. The same heterogeneity in reported strategies is found in other complex WM tasks including backward span (Norris et al, 2019) and complex span (Minear et al, 2016). The implication is that unfamiliar and cognitively demanding WM tasks are not necessarily served by invariant mechanisms reflected for example in a canonical model of running span, but instead reflect flexible and possibly idiosyncratic cognitive solutions (Gathercole et al, 2019).…”

Section: Discussionmentioning

confidence: 80%

The time course of updating in running span.

Kaur

Norris

Gathercole

2020

Journal of Experimental Psychology: Learning, Memory, and Cogni

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Running span can be performed by either passively listening to memory items or actively updating the target set. Previous research suggests that the active updating process is demanding and time-consuming and is favored at slow rates of presentation while the passive strategy is employed at fast rates. Two experiments examined the time course of recruitment of resources during task performance and its sensitivity to presentation rate. In Experiment 1, participants performed one of three serial recall tasks: running span, simple span, and modified span. The tasks were completed at the same time as a choice reaction time (RT) task and the RTs were used to index the resource demands of the memory task. Running span generated higher RT costs than simple span. The costs were present only for positions at and beyond the point in the sequence when the target memory set was changed, indicating a shift to a more cognitively demanding mode of updating. At these positions there was a generalized increase in RT costs that peaked 1000 ms following item presentation. In Experiment 2 the resource demands of running span varied with presentation rate and a peak demand at 1000 ms was again evident, but only with a slow presentation rate. In conjunction with strategy reports, these data establish that the process of active updating in running span is slow and cognitively demanding, making it difficult to use when presentation rates are fast.

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How do we perform backward serial recall?

Cited by 20 publications

References 31 publications

Working memory training involves learning new skills

Working memory training involves learning new skills

Evidence for separate backward recall and n-back working memory factors: A large-scale latent variable analysis

The time course of updating in running span.

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