ArticleFrontiers in human neuroscience2015
A Time Series Approach to Random Number Generation: Using Recurrence Quantification Analysis to Capture Executive Behavior.
Article in Frontiers in human neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Random Number Generation in Adults With Dyslexia: Further Evidence of Dyslexia-Related Executive Function Difficulties.Dyslexia (Chichester, England) · 2026Article
- An improved modeling approach to investigate biases in human random number generation.PloS one · 2025Article
- A time-series perspective on executive functioning: The benefits of a dynamic approach to random number generation.International journal of methods in psychiatric research · 2023Article
- Instruction effects on randomness in sequence generation.Frontiers in psychology · 2023Article
- Early Warning Signals in Phase Space: Geometric Resilience Loss Indicators From Multiplex Cumulative Recurrence Networks.Frontiers in physiology · 2022Article
- Random walk: Random number generation during backward and forward walking- the role of aging.Frontiers in aging neuroscience · 2022Article
- RandseqR: An R Package for Describing Performance on the Random Number Generation Task.Frontiers in psychology · 2021Article
- Mice adaptively generate choice variability in a deterministic task.Communications biology · 2020Article
- The Morra Game as a Naturalistic Test Bed for Investigating Automatic and Voluntary Processes in Random Sequence Generation.Frontiers in psychology · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The concept of executive functions plays a prominent role in contemporary experimental and clinical studies on cognition. One paradigm used in this framework is the random number generation (RNG) task, the execution of which demands aspects of executive functioning, specifically inhibition and working memory. Data from the RNG task are best seen as a series of successive events. However, traditional RNG measures that are used to quantify executive functioning are mostly summary statistics referring to deviations from mathematical randomness. In the current study, we explore the utility of recurrence quantification analysis (RQA), a non-linear method that keeps the entire sequence intact, as a better way to describe executive functioning compared to traditional measures. To this aim, 242 first- and second-year students completed a non-paced RNG task. Principal component analysis of their data showed that traditional and RQA measures convey more or less the same information. However, RQA measures do so more parsimoniously and have a better interpretation.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.