scholarly journals Modeling Mental Speed: Decomposing Response Time Distributions in Elementary Cognitive Tasks and Correlations with Working Memory Capacity and Fluid Intelligence

2016 ◽  
Vol 4 (4) ◽  
pp. 13 ◽  
Author(s):  
Florian Schmitz ◽  
Oliver Wilhelm
Keyword(s):  
Working Memory ◽  
Response Time ◽  
Fluid Intelligence ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Cognitive Tasks ◽  
Response Time Distributions ◽  
Elementary Cognitive Tasks

scholarly journals Binding Costs in Processing Efficiency as Determinants of Cognitive Ability

2021 ◽  
Vol 9 (2) ◽  
pp. 18
Author(s):  
Benjamin Goecke ◽  
Florian Schmitz ◽  
Oliver Wilhelm
Keyword(s):  
Working Memory ◽  
Individual Differences ◽  
Reaction Time ◽  
Fluid Intelligence ◽  
Task Complexity ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Cognitive Tasks ◽  
General Factor ◽  
Elementary Cognitive Tasks

Performance in elementary cognitive tasks is moderately correlated with fluid intelligence and working memory capacity. These correlations are higher for more complex tasks, presumably due to increased demands on working memory capacity. In accordance with the binding hypothesis, which states that working memory capacity reflects the limit of a person’s ability to establish and maintain temporary bindings (e.g., relations between items or relations between items and their context), we manipulated binding requirements (i.e., 2, 4, and 6 relations) in three choice reaction time paradigms (i.e., two comparison tasks, two change detection tasks, and two substitution tasks) measuring mental speed. Response time distributions of 115 participants were analyzed with the diffusion model. Higher binding requirements resulted in generally reduced efficiency of information processing, as indicated by lower drift rates. Additionally, we fitted bi-factor confirmatory factor analysis to the elementary cognitive tasks to separate basal speed and binding requirements of the employed tasks to quantify their specific contributions to working memory capacity, as measured by Recall−1-Back tasks. A latent factor capturing individual differences in binding was incrementally predictive of working memory capacity, over and above a general factor capturing speed. These results indicate that the relation between reaction time tasks and working memory capacity hinges on the complexity of the reaction time tasks. We conclude that binding requirements and, therefore, demands on working memory capacity offer a satisfactory account of task complexity that accounts for a large portion of individual differences in ability.

scholarly journals Binding Costs in Processing Efficiency as Determinants of Cognitive Ability

2020 ◽  
Author(s):  
Benjamin Goecke ◽  
Florian Schmitz ◽  
Oliver Wilhelm
Keyword(s):  
Working Memory ◽  
Individual Differences ◽  
Cognitive Ability ◽  
Fluid Intelligence ◽  
Task Complexity ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Cognitive Tasks ◽  
General Factor ◽  
Elementary Cognitive Tasks

Performance in elementary cognitive tasks is moderately correlated with fluid intelligence and working memory capacity. These correlations are higher for more complex tasks, presumably due to increased demands on working memory capacity. In accordance with the binding hypothesis, which states that working memory capacity reflects the limit of a person’s ability to establish and maintain temporary bindings (e.g., relations between items or relations between items and their context), we manipulated binding requirements (i.e., 2, 4, and 6 relations) in three choice reaction time paradigms (i.e., two comparison tasks, two change-detection tasks, and two substitution tasks) measuring mental speed. Response time distributions of N = 115 participants were analyzed with the diffusion model. Higher binding requirements resulted in generally reduced efficiency of information processing, as indicated by lower drift rates. Additionally, we fitted bi-factor confirmatory factor analysis to the elementary cognitive tasks to separate basal speed and binding requirements of the employed tasks to quantify their specific contributions to working memory capacity, as measured by Recall-1-Back tasks. A latent factor capturing individual differences in binding was incrementally predictive of working memory capacity, over and above a general factor capturing speed. These results indicate that the theory-driven task complexity manipulation in terms of binding requirements moderated the relation of mental speed tasks with cognitive ability in the predicted way. We conclude that binding requirements and, therefore, demands on working memory capacity offer a satisfactory account of task complexity that accounts for a large portion of individual differences in ability.

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

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 The Development of Latin Square Tasks. More Science Than Art?

2021 ◽  
Author(s):  
Johanna Hartung ◽  
Benjamin Goecke ◽  
Ulrich Schroeders ◽  
Florian Schmitz ◽  
Oliver Wilhelm
Keyword(s):  
Working Memory ◽  
Fluid Intelligence ◽  
Working Memory Capacity ◽  
Theoretical Perspective ◽  
Latin Square ◽  
Memory Capacity ◽  
The Novel ◽  
Improve Measurement ◽  
Item Characteristics ◽  
Underlying Processes

In contrast to measures of working memory capacity, tests for fluid intelligence are elusive in their psychometric properties. Somewhat surprisingly, fluid intelligence is not as tractable as often conceived. We studied Latin Square Tasks (LSTs) as a group of indicators that supposedly can improve measurement of fluid intelligence. In four studies (N > 3,300), we compared competing theoretical accounts that differ in the cognitive processes proposed for successfully completing items. To this end, the cognitive demand was operationalized by two key requirements that decisively influence the task difficulty: a) processing of information with differing complexity and b) memorizing steps to the final solution. Confirming predictions, the underlying processes of LSTs are independent of stimulus type and rotation of the matrices. Relations with reasoning confirmed the validity of the novel Latin Square Tasks. Working memory capacity was a limiting resource that determined performance, however more precise predictions of item difficulties might be possible when further item characteristics will be considered. From a theoretical perspective, we discuss the superiority of a perspective on LSTs inspired by the binding hypothesis compared to relational complexity theory.

scholarly journals Intelligence test items varying in capacity demands cannot be used to test the causality of working memory capacity for fluid intelligence

2021 ◽  
Author(s):  
Gidon T. Frischkorn ◽  
Klaus Oberauer
Keyword(s):  
Working Memory ◽  
Test Performance ◽  
Latent Variable ◽  
Fluid Intelligence ◽  
Working Memory Capacity ◽  
Strong Relationship ◽  
Theoretical Models ◽  
Memory Capacity ◽  
Intelligence Test ◽  
Test Items

AbstractThere is a strong relationship between fluid intelligence and working memory capacity (WMC). Yet, the cognitive mechanisms underlying this relationship remain elusive. The capacity hypothesis states that this relationship is due to limitations in the amount of information that can be stored and held active in working memory. Previous research aimed at testing the capacity hypothesis assumed that it implies stronger relationships of intelligence test performance with WMC for test items with higher capacity demands. The present article addresses this assumption through simulations of three theoretical models implementing the capacity hypothesis while systematically varying different psychometric variables. The results show that almost any relation between the capacity demands of items and their correlation with WMC can be obtained. Therefore, the assumption made by previous studies does not hold: The capacity hypothesis does not imply stronger correlations of WMC and intelligence test items with higher capacity demands. Items varying in capacity demands cannot be used to test the causality of WMC (or any other latent variable) for fluid intelligence.

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