scholarly journals Is executive control related to working memory capacity and fluid intelligence?

2019 ◽  
Vol 148 (8) ◽  
pp. 1335-1372 ◽  
Author(s):  
Alodie Rey-Mermet ◽  
Miriam Gade ◽  
Alessandra S. Souza ◽  
Claudia C. von Bastian ◽  
Klaus Oberauer
Keyword(s):  
Working Memory ◽  
Executive Control ◽  
Fluid Intelligence ◽  
Working Memory Capacity ◽  
Memory Capacity

Strategy use moderates the relation between working memory capacity and fluid intelligence: A combined approach

Intelligence ◽  
2022 ◽  
Vol 91 ◽  
pp. 101627
Author(s):  
Chenyu Li ◽  
Xuezhu Ren ◽  
Karl Schweizer ◽  
Tengfei Wang
Keyword(s):  
Working Memory ◽  
Fluid Intelligence ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Strategy Use ◽  
Combined Approach

scholarly journals For Whom the Mind Wanders, and When, Varies Across Laboratory and Daily-Life Settings

2017 ◽  
Vol 28 (9) ◽  
pp. 1271-1289 ◽  
Author(s):  
Michael J. Kane ◽  
Georgina M. Gross ◽  
Charlotte A. Chun ◽  
Bridget A. Smeekens ◽  
Matt E. Meier ◽  
...  
Keyword(s):  
Working Memory ◽  
Executive Control ◽  
Life Experience ◽  
Daily Life ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Mind Wandering ◽  
Personality Factors ◽  
Laboratory Findings ◽  
The Mind

Undergraduates ( N = 274) participated in a weeklong daily-life experience-sampling study of mind wandering after being assessed in the lab for executive-control abilities (working memory capacity; attention-restraint ability; attention-constraint ability; and propensity for task-unrelated thoughts, or TUTs) and personality traits. Eight times a day, electronic devices prompted subjects to report on their current thoughts and context. Working memory capacity and attention abilities predicted subjects’ TUT rates in the lab, but predicted the frequency of daily-life mind wandering only as a function of subjects’ momentary attempts to concentrate. This pattern replicates prior daily-life findings but conflicts with laboratory findings. Results for personality factors also revealed different associations in the lab and daily life: Only neuroticism predicted TUT rate in the lab, but only openness predicted mind-wandering rate in daily life (both predicted the content of daily-life mind wandering). Cognitive and personality factors also predicted dimensions of everyday thought other than mind wandering, such as subjective judgments of controllability of thought. Mind wandering in people’s daily environments and TUTs during controlled and artificial laboratory tasks have different correlates (and perhaps causes). Thus, mind-wandering theories based solely on lab phenomena may be incomplete.

Understanding the Relationship Between Rationality and Intelligence: A Latent-Variable Approach

2021 ◽  
Author(s):  
Alexander P. Burgoyne ◽  
Cody Mashburn ◽  
Jason S. Tsukahara ◽  
Zach Hambrick ◽  
Randall W Engle
Keyword(s):  
Working Memory ◽  
Latent Variable ◽  
Fluid Intelligence ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Attention Control ◽  
Equation Modeling ◽  
General Intelligence ◽  
Variable Approach ◽  
The Relationship

A hallmark of intelligent behavior is rationality—the disposition and ability to think analytically to make decisions that maximize expected utility or follow the laws of probability, and therefore align with normative principles of decision making. However, the question remains as to whether rationality and intelligence are empirically distinct, as does the question of what cognitive mechanisms underlie individual differences in rationality. In a large sample of participants (N = 331), we used latent variable analyses to assess the relationship between rationality and intelligence. The results indicated that there was a common ability underpinning performance on some, but not all, rationality tests. Latent factors representing rationality and general intelligence were strongly correlated (r = .54), but their correlation fell well short of unity. Indeed, after accounting for variance in performance attributable to general intelligence, rationality measures still cohered on a latent factor. Confirmatory factor analysis indicated that rationality correlated significantly with fluid intelligence (r = .56), working memory capacity (r = .44), and attention control (r = .49). Structural equation modeling revealed that attention control fully accounted for the relationship between working memory capacity and rationality, and partially accounted for the relationship between fluid intelligence and rationality. Results are interpreted in light of the executive attention framework, which holds that attention control supports information maintenance and disengagement in service of complex cognition. We conclude by speculating about factors rationality tests may tap that other cognitive ability tests miss, and outline directions for further research.

scholarly journals Is working memory capacity a causal factor in fluid intelligence?

2019 ◽  
Vol 26 (4) ◽  
pp. 1333-1339 ◽  
Author(s):  
Alexander P. Burgoyne ◽  
David Z. Hambrick ◽  
Erik M. Altmann
Keyword(s):  
Working Memory ◽  
Fluid Intelligence ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Causal Factor

scholarly journals Working memory capacity mediates the relationship between removal and fluid intelligence

2018 ◽  
Vol 101 ◽  
pp. 18-36 ◽  
Author(s):  
Krishneil A. Singh ◽  
Gilles E. Gignac ◽  
Christopher R. Brydges ◽  
Ullrich K.H. Ecker
Keyword(s):  
Working Memory ◽  
Fluid Intelligence ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
The Relationship

scholarly journals Capacity, Control, or Both – Which Aspects of Working Memory Contribute to Children’s General Fluid Intelligence?

2016 ◽  
Vol 47 (1) ◽  
pp. 21-28 ◽  
Author(s):  
Edward Nęcka ◽  
Agata Lulewicz
Keyword(s):  
Working Memory ◽  
Inhibitory Control ◽  
Executive Control ◽  
Creative Thinking ◽  
Fluid Intelligence ◽  
Storage Capacity ◽  
Working Memory Capacity ◽  
Capacity Control ◽  
Prepotent Response ◽  
Raven's Progressive Matrices

Abstract Starting from the assumption that working memory capacity is an important predictor of general fluid intelligence, we asked which aspects of working memory account for this relationship. Two theoretical stances are discussed. The first one posits that the important explanatory factor is storage capacity, roughly defined as the number of chunks possible to hold in the focus of attention. The second one claims that intelligence is explained by the efficiency of executive control, for instance, by prepotent response inhibition. We investigated 96 children at the age between 10 and 13. They completed a version of the n-back task that allows assessment of both storage capacity and inhibitory control. They also completed Raven’s Progressive Matrices as the fluid intelligence test and the Test for Creative Thinking - Drawing Production, for control purposes. We found that Raven’s scores correlated negatively with the number of unnecessary responses to irrelevant stimuli but they did not correlate with the number of signal detections. We conclude that children’s fluid intelligence depends on inhibitory control, with no relationship with storage capacity.

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