Next Article in Journal / Special Issue
Use of Response Time for Measuring Cognitive Ability
Previous Article in Journal / Special Issue
Cognitive Aging in the Seattle Longitudinal Study: Within-Person Associations of Primary Mental Abilities with Psychomotor Speed and Cognitive Flexibility
Article Menu

Export Article

Open AccessArticle
J. Intell. 2016, 4(4), 13; doi:10.3390/jintelligence4040013

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

Institute of Psychology, University Ulm, Albert-Einstein Allee 47, 89081 Ulm, Germany
*
Author to whom correspondence should be addressed.
Academic Editor: Paul De Boeck
Received: 18 April 2016 / Revised: 24 August 2016 / Accepted: 15 September 2016 / Published: 14 October 2016
(This article belongs to the Special Issue Mental Speed and Response Times in Cognitive Tests)
View Full-Text   |   Download PDF [1784 KB, uploaded 14 October 2016]   |  

Abstract

Previous research has shown an inverse relation between response times in elementary cognitive tasks and intelligence, but findings are inconsistent as to which is the most informative score. We conducted a study (N = 200) using a battery of elementary cognitive tasks, working memory capacity (WMC) paradigms, and a test of fluid intelligence (gf). Frequently used candidate scores and model parameters derived from the response time (RT) distribution were tested. Results confirmed a clear correlation of mean RT with WMC and to a lesser degree with gf. Highly comparable correlations were obtained for alternative location measures with or without extreme value treatment. Moderate correlations were found as well for scores of RT variability, but they were not as strong as for mean RT. Additionally, there was a trend towards higher correlations for slow RT bands, as compared to faster RT bands. Clearer evidence was obtained in an ex-Gaussian decomposition of the response times: the exponential component was selectively related to WMC and gf in easy tasks, while mean response time was additionally predictive in the most complex tasks. The diffusion model parsimoniously accounted for these effects in terms of individual differences in drift rate. Finally, correlations of model parameters as trait-like dispositions were investigated across different tasks, by correlating parameters of the diffusion and the ex-Gaussian model with conventional RT and accuracy scores. View Full-Text
Keywords: mental speed; working memory capacity; intelligence; response time modeling; ex-Gaussian model; diffusion model mental speed; working memory capacity; intelligence; response time modeling; ex-Gaussian model; diffusion model
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Schmitz, F.; Wilhelm, O. Modeling Mental Speed: Decomposing Response Time Distributions in Elementary Cognitive Tasks and Correlations with Working Memory Capacity and Fluid Intelligence. J. Intell. 2016, 4, 13.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
J. Intell. EISSN 2079-3200 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top