ArticleInternational journal of methods in psychiatric research2023
A time-series perspective on executive functioning: The benefits of a dynamic approach to random number generation.
Article in International journal of methods in psychiatric research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Dynamic Testing in a Heterogeneous Clinical Sample: A Feasibility Study.Behavioral sciences (Basel, Switzerland) · 2025Article
- An improved modeling approach to investigate biases in human random number generation.PloS one · 2025Article
- A comparative evaluation of measures to assess randomness in human-generated sequences.Behavior research methods · 2024Article
- No relations between executive functions and dimensional models of psychopathology or is time the missing link?PloS one · 2024Article
- 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
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Authors and funding
4 authors.
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Abstract
objectivesExecutive functioning (EF) is a key topic in neuropsychology. A multitude of underlying processes and constructs have been suggested to explain EF, which are measured by at least as many different neuropsychological tests. However, these tests often refer to summary statistics to quantify the construct under study, failing to capture the dynamic nature of EF. An alternative to these summary statistics is a time-series approach that quantifies all the available temporal information.
methodsWe used recurrence quantification analysis (RQA) to quantify the characteristics of any temporal pattern in random number generation data and we compared RQA to the traditional and static analysis of random number sequences.
resultsThe traditional measures yield inconsistent results with increasing sequences length, both for computer-generated and human-generated sequences, whereas the RQA measures do not.
conclusionThe results suggest that a time-series approach does a better job at modelling what is happening on different time-scales, and, therefore, is better at explaining how EF is changing in the course of the random number generation task. We argue that it is likely that these findings also apply to other neuropsychological EF tests, and that a time-series approach is an important addition to the study of EF.
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