Oomens Wouter, Maes Joseph H R, Hasselman Fred, Egger Jos I M
Centre of Excellence for Neuropsychiatry, Vincent van Gogh Institute for Psychiatry , Venray , Netherlands.
Donders Institute for Brain, Cognition and Behavior, Radboud University , Nijmegen , Netherlands.
Front Hum Neurosci. 2015 Jun 5;9:319. doi: 10.3389/fnhum.2015.00319. eCollection 2015.
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.
执行功能的概念在当代认知实验和临床研究中起着重要作用。该框架中使用的一个范式是随机数生成（RNG）任务，执行该任务需要执行功能的各个方面，特别是抑制和工作记忆。RNG任务的数据最好被视为一系列连续事件。然而，用于量化执行功能的传统RNG测量大多是指与数学随机性偏差的汇总统计量。在当前研究中，我们探索了递归量化分析（RQA）的效用，这是一种保持整个序列完整的非线性方法，与传统测量相比，它是描述执行功能的更好方法。为此，242名一年级和二年级学生完成了一项无时间限制的RNG任务。对他们数据的主成分分析表明，传统测量和RQA测量传达的信息大致相同。然而，RQA测量以更简洁的方式做到了这一点，并且具有更好的解释性。
