Literature DB >> 33916172

Binding Costs in Processing Efficiency as Determinants of Cognitive Ability.

Benjamin Goecke1, Florian Schmitz1, Oliver Wilhelm1.   

Abstract

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.

Entities:  

Keywords:  binding; mental speed; working memory capacity

Year:  2021        PMID: 33916172     DOI: 10.3390/jintelligence9020018

Source DB:  PubMed          Journal:  J Intell        ISSN: 2079-3200


  28 in total

1.  INFERRED COMPONENTS OF REACTION TIMES AS FUNCTIONS OF FOREPERIOD DURATION.

Authors:  R H HOHLE
Journal:  J Exp Psychol       Date:  1965-04

2.  Working memory capacity and fluid intelligence are strongly related constructs: comment on Ackerman, Beier, and Boyle (2005).

Authors:  Michael J Kane; David Z Hambrick; Andrew R A Conway
Journal:  Psychol Bull       Date:  2005-01       Impact factor: 17.737

3.  Working memory and intelligence--their correlation and their relation: comment on Ackerman, Beier, and Boyle (2005).

Authors:  Klaus Oberauer; Ralf Schulze; Oliver Wilhelm; Heinz-Martin Süss
Journal:  Psychol Bull       Date:  2005-01       Impact factor: 17.737

4.  The nature of individual differences in working memory capacity: active maintenance in primary memory and controlled search from secondary memory.

Authors:  Nash Unsworth; Randall W Engle
Journal:  Psychol Rev       Date:  2007-01       Impact factor: 8.934

5.  The Magical Mystery Four: How is Working Memory Capacity Limited, and Why?

Authors:  Nelson Cowan
Journal:  Curr Dir Psychol Sci       Date:  2010-02-01

6.  Effects of aging and IQ on item and associative memory.

Authors:  Roger Ratcliff; Anjali Thapar; Gail McKoon
Journal:  J Exp Psychol Gen       Date:  2011-08

Review 7.  Processing speed as a mental capacity.

Authors:  R Kail; T A Salthouse
Journal:  Acta Psychol (Amst)       Date:  1994-08

Review 8.  Working memory: theories, models, and controversies.

Authors:  Alan Baddeley
Journal:  Annu Rev Psychol       Date:  2011-09-27       Impact factor: 24.137

9.  How to measure working memory capacity in the change detection paradigm.

Authors:  Jeffrey N Rouder; Richard D Morey; Candice C Morey; Nelson Cowan
Journal:  Psychon Bull Rev       Date:  2011-04

10.  Individual Differences and Fitting Methods for the Two-Choice Diffusion Model of Decision Making.

Authors:  Roger Ratcliff; Russ Childers
Journal:  Decision (Wash D C )       Date:  2015
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  3 in total

1.  Intelligence IS Cognitive Flexibility: Why Multilevel Models of Within-Individual Processes Are Needed to Realise This.

Authors:  Damian P Birney; Jens F Beckmann
Journal:  J Intell       Date:  2022-08-01

2.  Age-Related Changes and Reorganization of Creativity and Intelligence Indices in Schoolchildren and University Students.

Authors:  Olga Razumnikova; Maxim Bakaev
Journal:  J Intell       Date:  2022-08-02

3.  Taking a Closer Look: The Relationship between Pre-School Domain General Cognition and School Mathematics Achievement When Controlling for Intelligence.

Authors:  Antje Ehlert; Nadine Poltz; Sabine Quandte; Juliane Kohn; Karin Kucian; Michael Von Aster; Günter Esser
Journal:  J Intell       Date:  2022-09-19
  3 in total

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