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 We analyzed six published and unpublished datasets and compared findings across studies.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.

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 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 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.

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 Making Cognitive Latent Variables Manifest: Distinct Neural Networks for Fluid Reasoning and Processing Speed

2015 ◽  
Vol 27 (6) ◽  
pp. 1249-1258 ◽  
Author(s):  
Christian Habeck ◽  
Jason Steffener ◽  
Daniel Barulli ◽  
Yunglin Gazes ◽  
Qolamreza Razlighi ◽  
...  
Keyword(s):  
Individual Differences ◽  
Cognitive Ability ◽  
Cognitive Abilities ◽  
Latent Variables ◽  
Latent Variable ◽  
Cognitive Tasks ◽  
Neural Activation ◽  
Strongly Correlated ◽  
Activation Patterns ◽  
Fluid Reasoning

Cognitive psychologists posit several specific cognitive abilities that are measured with sets of cognitive tasks. Tasks that purportedly tap a specific underlying cognitive ability are strongly correlated with one another, whereas performances on tasks that tap different cognitive abilities are less strongly correlated. For these reasons, latent variables are often considered optimal for describing individual differences in cognitive abilities. Although latent variables cannot be directly observed, all cognitive tasks representing a specific latent ability should have a common neural underpinning. Here, we show that cognitive tasks representing one ability (i.e., either perceptual speed or fluid reasoning) had a neural activation pattern distinct from that of tasks in the other ability. One hundred six participants between the ages of 20 and 77 years were imaged in an fMRI scanner while performing six cognitive tasks, three representing each cognitive ability. Consistent with prior research, behavioral performance on these six tasks clustered into the two abilities based on their patterns of individual differences and tasks postulated to represent one ability showed higher similarity across individuals than tasks postulated to represent a different ability. This finding was extended in the current report to the spatial resemblance of the task-related activation patterns: The topographic similarity of the mean activation maps for tasks postulated to reflect the same reference ability was higher than for tasks postulated to reflect a different reference ability. Furthermore, for any task pairing, behavioral and topographic similarities of underlying activation patterns are strongly linked. These findings suggest that differences in the strengths of correlations between various cognitive tasks may be because of the degree of overlap in the neural structures that are active when the tasks are being performed. Thus, the latent variable postulated to account for correlations at a behavioral level may reflect topographic similarities in the neural activation across different brain regions.

scholarly journals Theory of Mind Measurements and Mechanisms: An Investigation of Construct Validity and Cognitive Processes in Theory of Mind Tasks

2021 ◽  
Author(s):  
◽  
Ester Navarro Garcia
Keyword(s):  
Individual Differences ◽  
Theory Of Mind ◽  
Construct Validity ◽  
Cognitive Abilities ◽  
Fluid Intelligence ◽  
Metalinguistic Awareness ◽  
Latent Factors ◽  
Confirmatory Factor Analyses ◽  
Crystallized Intelligence ◽  
Important Challenge

Understanding the perspectives of others is a critical skill. Theory of mind (ToM) is an essential ability for social competence and communication, and it is necessary for understanding behaviors that differ from our own (Premack and Woodruff, 1978). Although all individuals possess a ToM to varying degrees, bilinguals are especially adept to perspective-taking. Research has reported that bilinguals outperform monolinguals in ToM tasks (e.g., Goetz, 2003; Rubio-Fernandez & Glucksberg, 2012). However, the mechanisms underlying this effect are unclear. Studying individual differences in ToM performance between bilinguals and monolinguals can help explain these mechanisms. Yet this promising area of research faces an important challenge: the lack of psychometric research on ToM measurement. Recent research suggests that tests that measure the ToM construct might not be as reliable as previously thought (Warnell & Redcay, 2019). This hinders the interpretation of experimental and correlational findings and puts into question the validity of the ToM construct. This dissertation addresses these two questions empirically to improve our understanding of what constitutes ToM. Study 1 examines the structure of ToM, crystallized intelligence (Gc), and fluid intelligence (Gf) to understand (a) whether ToM constitutes a construct separate from other cognitive abilities and (b) to explore whether tasks of ToM present adequate construct validity. For this, three confirmatory factor analyses (CFAs) were conducted. The results demonstrated that a model with three latent factors (ToM, Gf and Gc) did not adequately fit the data and was not significantly different from a model with only two latent factors (ToM-Gf and Gc). In addition, an exploratory factor analysis (EFA) showed that two of the ToM tasks loaded onto a Gf factor whereas one of the tasks loaded onto a third factor by itself. Finally, an exploratory network analysis (NMA) was conducted to observe relationships among the tasks. The results showed that the ToM tasks were no more related to each other than to some tasks of Gf and Gc, and that ToM tasks did not form a consistent cluster. Overall, the results of Study 1 suggest that ToM tasks are likely not measuring a monolithic ToM construct. Study 2 examines individual differences in metalinguistic awareness, executive function, and bilingualism as predictors of ToM. The results showed that all variables significantly predicted ToM, but bilingualism was not a significant moderator of ToM. Overall, the findings suggest that in this sample there was no difference in the processes used to predict ToM based on being bilingual or monolingual. Implications for measurement and individual differences in ToM are discussed.

scholarly journals Psychometric Models of Individual Differences in Reading Comprehension: A Reanalysis of Freed, Hamilton, and Long (2017)

2019 ◽  
Author(s):  
Sara Anne Goring ◽  
Christopher J. Schmank ◽  
Michael J. Kane ◽  
Andrew R. A. Conway
Keyword(s):  
Reading Comprehension ◽  
Individual Differences ◽  
Cognitive Abilities ◽  
Latent Variable ◽  
Convergent Validity ◽  
Cognitive Task ◽  
Network Modeling ◽  
Network Models ◽  
Measurement Model ◽  
Common Cause

Individual differences in reading comprehension have often been explored using latent variable modeling (LVM), to assess the relative contribution of domain-general and domain-specific cognitive abilities. However, LVM is based on the assumption that the observed covariance among indicators of a construct is due to a common cause (i.e., a latent variable; Pearl, 2000). This is a questionable assumption when the indicator variables are measures of performance on complex cognitive tasks. According to Process Overlap Theory (POT; Kovacs & Conway, 2016), multiple processes are involved in cognitive task performance and the covariance among tasks is due to the overlap of processes across tasks. Instead of a single latent common cause, there are thought to be multiple dynamic manifest causes, consistent with an emerging view in psychometrics called network theory (Barabási, 2012; Borsboom & Cramer, 2013). In the current study, we reanalyzed data from Freed et al. (2017) and compared two modeling approaches: LVM (Study 1) and psychometric network modeling (Study 2). In Study 1, two exploratory LVMs demonstrated problems with the original measurement model proposed by Freed et al. Specifically, the model failed to achieve discriminant and convergent validity with respect to reading comprehension, language experience, and reasoning. In Study 2, two network models confirmed the problems found in Study 1, and also served as an example of how network modeling techniques can be used to study individual differences. In conclusion, more research, and a more informed approach to psychometric modeling, is needed to better understand individual differences in reading comprehension.

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