Which working memory functions predict intelligence?

Oberauer, Klaus; Süβ, Heinz-Martin; Wilhelm, Oliver; Wittmann, Werner W.

doi:10.1016/j.intell.2008.01.007

Cited by 241 publications

(274 citation statements)

References 38 publications

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“…The idea that there are multiple sources of variance underlying general cognitive abilities such as working memory capacity and intelligence has a long history (e.g., Thurstone, 1931Thurstone, , 1938 and is consistent with multi-component models of working memory (Baddeley & Hitch, 1974), as well as prior investigations of individual differences in working memory capacity that have posited multiple pools of resources (Daneman & Tardiff, 1987;Shah & Miyake, 1996). Indeed, the current results are consistent with the notion that there are multiple sources of variation across both task domains and cognitive processes (Conway & Kovacks, 2013;Logie, 2011;Oberauer, Süss, Wilhelm, & Wittmann, 2008).…”

Section: Discussionsupporting

confidence: 88%

“…These findings support multiple source theories of capacity and intelligence and are inconsistent with general ability models (cf., Conway & Kovaks, 2013;Logie, 2011;Oberauer et al, 2008). The current study failed to replicate certain aspects of Fukuda et al (2010) with respect to the relationship between number and resolution measures derived from visual array tasks.…”

Section: Discussioncontrasting

confidence: 68%

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The scope and control of attention: Sources of variance in working memory capacity

Conway

2015

Mem Cogn

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Working memory capacity is a strong positive predictor of many cognitive abilities, across various domains. The pattern of positive correlations across domains has been interpreted as evidence for a unitary source of inter-individual differences in behavior. However, recent work suggests that there are multiple sources of variance contributing to working memory capacity. The current study (N = 71) investigates individual differences in the scope and control of attention, in addition to the number and resolution of items maintained in working memory. Latent variable analyses indicate that the scope and control of attention reflect independent sources of variance and each account for unique variance in general intelligence. Also, estimates of the number of items maintained in working memory are consistent across tasks and related to general intelligence whereas estimates of resolution are task-dependent and not predictive of intelligence. These results provide insight into the structure of working memory, as well as intelligence, and raise new questions about the distinction between number and resolution in visual short-term memory.Keywords Working memory · Working memory capacity · Individual differences · Visual arrays · Complex span · Intelligence Working memory is a limited capacity system responsible for the active maintenance of information, as well as its M. Chow · A. R. A. Conway ( )

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Section: Discussionsupporting

confidence: 88%

Section: Discussioncontrasting

confidence: 68%

The scope and control of attention: Sources of variance in working memory capacity

Conway

2015

Mem Cogn

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“…Second, trivia quiz questions could evoke reasoning strategies (e.g., rejection of implausible answers) that would require -and hence, practice -relational integration processes; that is, the coordination of information elements into structures. Recent theories consider relational integration as crucial part of WM (e.g., Oberauer, 2010;Oberauer, Süß, Wilhelm, & Wittmann, 2003), and research has shown that such processes are highly related to fluid intelligence (e.g., Oberauer, Süß, Wilhelm, & Wittmann, 2008). We can only speculate whether such processes took place during active control training, but it could serve as an explanation for the active control group also showing some improvement in the transfer tasks.…”

Section: Discussionmentioning

confidence: 86%

Does working memory training have to be adaptive?

Bastian

Eschen

2015

Psychological Research

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This study tested the common assumption that, to be most effective, working memory (WM) training should be adaptive (i.e., task difficulty is adjusted to individual performance). Indirect evidence for this assumption stems from studies comparing adaptive training to a condition in which tasks are practiced on the easiest level of difficulty only [cf. Klingberg (Trends Cogn Sci 14:317-324, 2010)], thereby, however, confounding adaptivity and exposure to varying task difficulty. For a more direct test of this hypothesis, we randomly assigned 130 young adults to one of the three WM training procedures (adaptive, randomized, or self-selected change in training task difficulty) or to an active control group. Despite large performance increases in the trained WM tasks, we observed neither transfer to untrained structurally dissimilar WM tasks nor far transfer to reasoning. Surprisingly, neither training nor transfer effects were modulated by training procedure, indicating that exposure to varying levels of task difficulty is sufficient for inducing training gains. Can fluid cognitive abilities such as working memory (WM) and reasoning be improved through computer-based WM training? This is a highly controversial question, with prior empirical studies (for reviews, see Morrison & Chein, 2011;von Bastian & Oberauer, 2014) and meta-analyses (Au et al., in press;Karbach & Verhaeghen, 2014;Lampit, Hallock, & Valenzuela, 2014;Melby-Lervåg & Hulme, 2013) providing contradictory findings. Although multiple previous studies revealed promising effects (e.g., Jaeggi, Buschkuehl, Jonides, & Perrig, 2008;Jaeggi, Buschkuehl, Shah, & Jonides, 2014;Jaeggi et al., 2010; Klingberg et al., 2005;Schweizer, Hampshire, & Dalgleish, 2011;Stepankova et al., 2014;, a growing number of other WM training interventions failed to induce such broad transfer (e.g., Chein & Morrison, 2010;Chooi & Thompson, 2012;Colom et al., 2013;Harrison et al., 2013;Redick et al., 2013;Salminen, Strobach, & Schubert, 2012; Sprenger et al., 2013;Thompson et al., 2013;von Bastian, Langer, Jäncke, & Oberauer, 2013). The factors contributing to the success of WM training interventions in terms of improving WM and reasoning are still unclear (see von Bastian & Oberauer, 2014), and large variations (and, in some occasions, serious flaws) in the methodologies and training regimens used complicate comparisons across studies (cf. Shipstead, Redick, & Engle, 2012), and thus the identification of such factors. Therefore, before we can conclude whether and under which circumstances WM training can induce transfer, carefully controlled, systematic investigations of factors potentially contributing to training effectiveness are needed.In theory, cognitive plasticity occurs if there is a "prolonged mismatch between functional organismic supplies and environmental demands" (Lövden, Bäckman, Lindenberger, Schaefer, & Schmiedek, 2010, p. 659). According to Lövden and colleagues (2010), this mismatch occurs if the environmental demands exceed the routine demands the cognitiv...

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“…However, the present study can serve as a basis for future research putting shifting ability into the wider context of cognitive performance. More specifically, shifting has often been found to show different or even opposing patterns of correlations with other cognitive abilities (e.g., fluid intelligence) than other but supposedly related executive functions such as working memory (e.g., Oberauer, Süß, Wilhelm, & Wittmann, 2008; but see Draheim, Hicks, & Engle, 2016, for a possible methodological explanation), or inhibition and common executive function (cf. Miyake & Friedman, 2012).…”

Section: Limitations and Future Directionsmentioning

confidence: 99%

Shifting between mental sets: An individual differences approach to commonalities and differences of task switching components.

Bastian¹,

Druey²

2017

Journal of Experimental Psychology: General

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Switching between mental sets has been extensively investigated in both experimental and individual differences research using a wide range of task-switch paradigms. However, it is yet unclear whether these different tasks measure a unitary shifting ability or reflect different facets thereof. In this study, 20 task pairs were administered to 119 young adults to assess 5 proposed components of mental set shifting: switching between judgments, stimulus dimensions, stimulus-response mappings, response sets, and stimulus sets. Modeling latent factors for each of the components revealed that a model with 5 separate yet mostly correlated factors fit the data best. In this model, the components most strongly related to the other latent factors were stimulus-response mapping shifting and, to a lesser degree, response set shifting. In addition, both factors were statistically indistinguishable from a second-order general shifting factor. In contrast, shifting between judgments as well as stimulus dimensions consistently required separate factors and could, hence, not fully be accounted for by the general shifting factor. Finally, shifting between stimulus sets was unrelated to any other shifting component but mapping shifting. We conclude that tasks assessing shifting between mappings are most adequate to assess general shifting ability. In contrast, shifting between stimulus sets (e.g., as in the Trail Making Test) probably reflects shifts in visual attention rather than executive shifting ability.Keywords: task switching, individual differences, executive functions, unity and diversity Supplemental materials: http://dx.doi.org/10.1037/xge0000333.supp It is common experience that we rarely focus on only one activity at the time uninterruptedly. Rather, most of our daily life involves several things going on in quick succession or even concurrently. For example, while driving a car, we may simultaneously listen to music, quickly shift our attention from the street to the navigation system, and back on the road in an attempt to orient in an unfamiliar city. The mental processes behind such task switching and multitasking are obviously complex and have been one of the main topics in cognitive research of the last decades. Terms as, for instance, executive functions, cognitive control, or mental flexibility have been used to refer to the set of "shifting abilities" required in such situations, and many different paradigms have been developed to experimentally investigate these skills (e.g., Logan, 1985;Pashler, 2000).Set shifting abilities have also been of central interest in individual differences studies and studies on so-called frontal-lobe functions (e.g., Alvarez & Emory, 2006;Miyake et al., 2000). In these contexts, tasks have frequently been used that already have a long tradition in the assessment of frontal-executive functioning such as the Wisconsin Card Sorting Test (WCST) and its derivatives, or the Trail Making Test (TMT).In the present study, we try to bridge the two fields by using an individual differences...

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Which working memory functions predict intelligence?

Cited by 241 publications

References 38 publications

The scope and control of attention: Sources of variance in working memory capacity

The scope and control of attention: Sources of variance in working memory capacity

Does working memory training have to be adaptive?

Shifting between mental sets: An individual differences approach to commonalities and differences of task switching components.

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