scholarly journals Working Memory Delay Activity Predicts Individual Differences in Cognitive Abilities

2015 ◽  
Vol 27 (5) ◽  
pp. 853-865 ◽  
Author(s):  
Nash Unsworth ◽  
Keisuke Fukuda ◽  
Edward Awh ◽  
Edward K. Vogel
Keyword(s):  
Working Memory ◽  
Individual Differences ◽  
Cognitive Abilities ◽  
Latent Variable ◽  
Fluid Intelligence ◽  
Memory Span ◽  
Attention Control ◽  
Long Term Memory ◽  
Eeg Data ◽  
Contralateral Delay Activity

A great deal of prior research has examined the relation between estimates of working memory and cognitive abilities. Yet, the neural mechanisms that account for these relations are still not very well understood. The current study explored whether individual differences in working memory delay activity would be a significant predictor of cognitive abilities. A large number of participants performed multiple measures of capacity, attention control, long-term memory, working memory span, and fluid intelligence, and latent variable analyses were used to examine the data. During two working memory change detection tasks, we acquired EEG data and examined the contralateral delay activity. The results demonstrated that the contralateral delay activity was significantly related to cognitive abilities, and importantly these relations were because of individual differences in both capacity and attention control. These results suggest that individual differences in working memory delay activity predict individual differences in a broad range of cognitive abilities, and this is because of both differences in the number of items that can be maintained and the ability to control access to working memory.

scholarly journals Individual differences in working memory capacity, attention control, fluid intelligence, and pupillary measures of arousal

2021 ◽  
Author(s):  
Matthew Kyle Robison ◽  
Gene Arnold Brewer
Keyword(s):  
Working Memory ◽  
Individual Differences ◽  
Cognitive Abilities ◽  
Fluid Intelligence ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Attention Control ◽  
Future Research ◽  
Control Fluid ◽  
Thought Probes

The present study examined individual differences in three cognitive abilities: attention control (AC), working memory capacity (WMC), and fluid intelligence (gF) as they relate the tendency to experience task-unrelated thoughts (TUTs) and the regulation of arousal. Cognitive abilities were measured with a battery of nine laboratory tasks, TUTs were measured via thought probes inserted into two tasks, and arousal regulation was measured via pupillometry. Recent theorizing (Robison & Unsworth, 2017a) suggests that one reason why some people experience relatively frequent TUTs and relatively poor cognitive performance - especially AC and WMC - is that they exhibit dysregulated arousal. Here, we examined how arousal regulation might predict both AC and WMC, but also higher-order cognitive abilities like gF. Further, we examine direct and indirect associations with these abilities via a mediating influence of TUT. Participants who reported more TUTs also tended to exhibit poorer AC, lower WMC, and lower gF. Arousal dysregulation correlated with more TUTs and lower AC. However there was no direct correlation between arousal regulation and WMC, nor between arousal regulation and gF. Rather, the associations between arousal regulation, WMC, and gF were indirect via TUT. We discuss the implications of the results in light of the arousal regulation theory of individual differences and directions for future research.

scholarly journals Individual differences in vigilance: Implications for measuring sustained attention and its association with other cognitive abilities and psychological constructs

2019 ◽  
Author(s):  
Matthew Kyle Robison ◽  
Gene Arnold Brewer
Keyword(s):  
Individual Differences ◽  
Sustained Attention ◽  
Cognitive Abilities ◽  
Latent Variable ◽  
Fluid Intelligence ◽  
Attention Control ◽  
Psychological Constructs ◽  
Mixed Effects Modeling ◽  
Latent Variable Analysis ◽  
Control Fluid

Sustaining attention is notoriously difficult. Typically, when people have to sustain their attention to a single task, their performance deteriorates across time. This phenomenon isusually referred to as the vigilance decrement. However, as with most phenomena, there are substantial individual differences in the extent of this effect. That is, some people show more pronounced vigilance decrements than others. Such individual differences can potentially be leveraged to understand the cognitive mechanisms underlying sustained attention. In the present study, we combine linear mixed effects modeling and latent variable analysis to assess individual differences in vigilance and their association with other relevant psychological constructs. We analyzed six published and unpublished datasets and compared findings across studies. These studies used various combinations of working memory, attention control, fluid intelligence, and vigilance tasks. We conclude that vigilance is indeed a trait-level cognitive ability that is meaningfully related to other cognitive abilities, distinguishable yet related to attention control as it is typically measured, and correlates with other state and trait variables.

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.

Individual Differences in Attention Control

2020 ◽  
pp. 175-211
Author(s):  
Cody A. Mashburn ◽  
Jason S. Tsukahara ◽  
Randall W. Engle
Keyword(s):  
Working Memory ◽  
Individual Differences ◽  
Fluid Intelligence ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Attention Control ◽  
Executive Attention ◽  
Attention Theory ◽  
Attentional Resources ◽  
The Relationship

This chapter outlines the executive attention theory of higher-order cognition, which argues that individual differences in the ability to maintain information in working memory and disengage from irrelevant information is inextricably linked to variation in the ability to deploy domain-free attentional resources in a goal-directed fashion. It also summarizes recent addendums to the theory, particularly regarding the relationship between attention control, working memory capacity, and fluid intelligence. Specifically, the chapter argues that working memory capacity and fluid intelligence measures require different allocations of the same attentional resources, a fact which accounts for their strong correlation. At various points, it addresses theoretical alternatives to the executive attention theory of working memory capacity and empirical complications of the study of attention control, including difficulties deriving coherent attention control latent factors.

scholarly journals Differential and Experimental Approaches to Studying Intelligence in Humans and Non-Human Animals

2020 ◽  
Author(s):  
Alexander P. Burgoyne ◽  
Jason S. Tsukahara ◽  
Christopher Draheim ◽  
Randall W Engle
Keyword(s):  
Individual Differences ◽  
Cognitive Performance ◽  
Cognitive Abilities ◽  
Fluid Intelligence ◽  
Relevant Information ◽  
Attention Control ◽  
Cognitive Tasks ◽  
General Factor ◽  
Albino Rat ◽  
General Ability

Why do some individuals learn more quickly than others, or perform better in complex cognitive tasks? In this article, we describe how differential and experimental research methods can be used to study intelligence in humans and non-human animals. More than one hundred years ago, Spearman (1904) discovered a general factor underpinning performance across cognitive domains in humans. Shortly thereafter, Thorndike (1935) discovered positive correlations between cognitive performance measures in the albino rat. Today, research continues to shed light on the underpinnings of the positive manifold observed among ability measures. In this review, we focus on the relationship between cognitive performance and attention control: the domain-general ability to maintain focus on task-relevant information while preventing attentional capture by task-irrelevant thoughts and events. Recent work from our lab has revealed that individual differences in attention control can largely explain the positive associations between broad cognitive abilities such as working memory capacity and fluid intelligence. In research on mice, attention control has been closely linked to a general ability factor reflecting route learning and problem solving. Taken together, both lines of research suggest that individual differences in attention control underpin performance in a variety of complex cognitive tasks, helping to explain why measures of cognitive ability correlate positively. Efforts to find confirmatory and disconfirmatory evidence across species stands to improve not only our understanding of attention control, but cognition in general.

What Influences Successful Communication? An Examination of Cognitive Load and Individual Differences

2019 ◽  
Author(s):  
Ester Navarro ◽  
Brooke N Macnamara ◽  
Sam Glucksberg ◽  
Andrew R. A. Conway
Keyword(s):  
Working Memory ◽  
Individual Differences ◽  
Cognitive Load ◽  
Cognitive Abilities ◽  
Fluid Intelligence ◽  
Working Memory Capacity ◽  
Cognitive Resources ◽  
Audience Design ◽  
Low Load ◽  
Communication Errors

The underlying cognitive mechanisms explaining why speakers sometimes make communication errors are not well understood. Some scholars have theorized that audience design engages automatic processes when a listener is present; others argue that it relies on effortful resources, regardless of listener presence. We hypothesized that (a) working memory is engaged during communicative audience design and (b) the extent to which working memory is engaged relies on individual differences in cognitive abilities and concurrent amount of resources available. In Experiment 1, participants completed a referential task under high, low, or no cognitive load with a present listener, whose perspective differed from the speaker’s. Speakers made few referential errors under no and low load, but errors increased when cognitive load was highest. In Experiment 2, the listener was absent. Speakers made few referential errors under no and low load, but errors increased when cognitive load was highest, suggesting that audience design is still effortful under high cognitive load, regardless of the presence of a listener. Experiment 3 tested whether cognitive abilities predicted communication performance. Participants with higher fluid intelligence and working memory capacity made fewer communication errors. Our findings suggest that communication relies on available cognitive resources, and therefore errors occur as a function of factors like cognitive load, and individual differences.

scholarly journals Apshvalka_ind_diffs_preprint

2018 ◽  
Author(s):  
Richard Ramsey ◽  
Dace Apšvalka ◽  
Emily S. Cross
Keyword(s):  
Working Memory ◽  
Individual Differences ◽  
Observational Learning ◽  
Cognitive Abilities ◽  
Fluid Intelligence ◽  
Common Mechanism ◽  
Cognitive Resources ◽  
Key Press ◽  
Post Test ◽  
Observational Practice

Humans have a remarkable ability to learn by watching others, whether learning to tie an elaborate knot or play the piano. However, the mechanisms that translate visual input into motor skill execution remain unclear. It has been proposed that common cognitive and neural mechanisms underpin learning motor skills by physical and observational practice. Here we provide a novel test of the common mechanism hypothesis by testing the extent to which certain individual differences predict observational as well as physical learning. Participants (N=92 per group) either physically practiced a five-element key-press sequence or watched videos of similar sequences before physically performing trained and untrained sequences in a test phase. We also measured cognitive abilities across participants that have previously been associated with rates of learning, including working memory and fluid intelligence. Our findings show that individual differences in working memory and fluid intelligence predict improvements in dissociable aspects of motor learning following physical practice, but not observational practice. Working memory predicts general learning gains from pre- to post-test that generalise to untrained sequences, whereas fluid intelligence predicts sequence-specific trains gains that are tied to trained sequences. However, neither working memory nor fluid intelligence predict training gains following observational learning. Therefore, these results suggest limits to the shared mechanism hypothesis of physical and observational learning. Indeed, models of observational learning need updating to reflect the extent to which such learning is based on shared as well as distinct processes compared to physical learning. We suggest that such differences could reflect the more intentional nature of learning during physical compared to observational practice, which relies to a greater extent on higher-order cognitive resources such as working memory and fluid intelligence.

scholarly journals A toolbox approach to improving the measurement of attention control

2019 ◽  
Author(s):  
Chris Draheim ◽  
Jason S. Tsukahara ◽  
Jessie Martin ◽  
Cody Mashburn ◽  
Randall W Engle
Keyword(s):  
Working Memory ◽  
Individual Differences ◽  
Reaction Time ◽  
Fluid Intelligence ◽  
Empirical Test ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Attention Control ◽  
The Individual ◽  
Unitary Concept

Cognitive tasks that produce reliable and robust effects at the group level often fail to yield reliable and valid individual differences. An ongoing debate among attention researchers is whether conflict resolution mechanisms are task-specific or domain-general, and the lack of correlation between most attention measures seems to favor the view that attention control is not a unitary concept. We have argued that the use of difference scores, particularly in reaction time, is the primary cause of null and conflicting results at the individual differences level, and that methodological issues with existing tasks preclude making strong theoretical conclusions. The present article is an empirical test of this view in which we used a toolbox approach to develop and validate new tasks hypothesized to reflect attention processes. Here, we administered existing, modified, and new attention tasks to over 400 subjects (final N = 396). Compared to the traditional Stroop and flanker tasks, performance on the accuracy-based measures was more reliable, had stronger intercorrelations, formed a more coherent latent factor, and had stronger associations to measures of working memory capacity and fluid intelligence. Further, attention control fully accounted for the relationship between working memory capacity and fluid intelligence. These results show that accuracy-based tasks can be better suited to individual differences investigations than traditional reaction time tasks, particularly when the goal is to maximize prediction. We conclude that attention control is a unitary concept.

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