A Time Series Approach to Random Number Generation: Using Recurrence Quantification Analysis to Capture Executive Behavior

Oomens, Wouter; Maes, J.H.R.; Hasselman, Fred; Egger, J.I.M.

doi:10.3389/fnhum.2015.00319

Cited by 13 publications

(15 citation statements)

References 38 publications

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“…These types are subserved by distinct neuronal systems (Nigg, 2000;Stahl et al, 2014). Concerning the issue of process (im)pureness, tasks like the random letter generation task, used to assess behavioral inhibition (Gonneaud et al, 2011), and the card-sorting and fluency tests, used to measure shifting, likely involve other EF components (such as WM) and associated neural structures (e.g., Buchsbaum, Greer, Chang, & Berman, 2005;Huizinga et al, 2006;Miyake et al, 2000;Oomens, Maes, Hasselman, & Egger, 2015). An final feature of the previous PM studies is that they differ in the age ranges examined, with a somewhat underrepresentation of young teenagers (approximately 12−16 years of age).…”

Section: Age Differences In Pm and Association With Ef Developmentmentioning

confidence: 99%

Age Differences in Prospective Memory: A Further Evaluation of the Executive Framework

Zhao

et al. 2019

Journal of Cognition and Development

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According to the executive framework of prospective memory (PM), age-related differences in PM performance are mediated by agerelated differences in executive functioning (EF). The present study further explored this framework by examining which specific components of EF are associated with PM differences between and within three age groups. A group of children (7-9 years; N = 108), adolescents (12-14 years; N = 112), and adults (17-23 years; N = 106) performed focal-and non-focal event-based PM (EBPM) tasks, a time-based PM (TBPM) task, and tasks measuring EF components. Differences between age groups in focal EBPM, non-focal EBPM, and TBPM performance were mediated by, respectively, differences in interference control and response inhibition, performance on the ongoing task, and differences in working memory and response inhibition. However, within-age group analyses only revealed WM updating as significant predictor of TBPM performance in the adolescent group. These results support and further qualify the executive framework of PM. The differences in outcome dependent on the examined age range might be important for explaining mixed results of previous studies regarding the precise EF components underlying age-related PM task performance differences. Prospective memory (PM) refers to the ability to realize a delayed intention by "remembering to remember" to perform a future action (Ellis, 1996). PM is crucial for many daily-life tasks and involves different phases, specifically, the formation, retention, initiation, and execution of the intention (Kliegel, Martin, McDaniel, & Einstein, 2002). PM has a retrospective component, remembering what specific action to perform, next to a prospective component, remembering that a specific action must be performed (Einstein & McDaniel, 1996). In addition, a distinction can be made between event-based PM (EBPM) and time-based PM (TBPM), which refers to the type of cue that triggers execution of the intended action (Brandimonte, Einstein, & McDaniel, 1996). In EBPM, this concerns an external cue, such as when remembering to buy bread upon passing a bakery. In TBPM, the intention has to be realized at a specific time or period of time, such as to remember to take medicine in time. PM and executive functions According to an influential theory in the field, the multiprocess theory, PM tasks may require relatively automatic or strategic processes, depending, among other factors, on features of the

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Section: Age Differences In Pm and Association With Ef Developmentmentioning

confidence: 99%

Age Differences in Prospective Memory: A Further Evaluation of the Executive Framework

Zhao

et al. 2019

Journal of Cognition and Development

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“…As summarized by Towse and Neil (1998), experimental research on random generation indicates that response production relies on Executive Functions (Baddeley et al, 1986;Baddeley et al, 1998;Towse and Mclachlan, 1999;Miyake et al, 2000;Vandierendonck, 2000). Random generation has been extensively used in the past as a measure of the central executive component of working memory with behavioral methods (Baddeley et al, 1998;Schulz et al, 2012;Oomens et al, 2015) and in neuroimaging (Jahanshahi et al, 2000;Daniels et al, 2003), in healthy subjects and patients suffering from frontal lobe lesions (Spatt and Goldenberg, 1993), dementia (Brugger et al, 1996b), Parkinson's disease (Brown et al, 1998), schizophrenia (Rosenberg et al, 1990).…”

Section: Introductionmentioning

confidence: 99%

The Morra Game as a Naturalistic Test Bed for Investigating Automatic and Voluntary Processes in Random Sequence Generation

et al. 2020

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Morra is a 3,000-years-old hand game of prediction and numbers. The two players reveal their hand simultaneously, presenting a number of fingers between 1 and 5, while calling out a number between 2 and 10. Any player who successfully guesses the summation of fingers revealed by both players scores a point. While the game is extremely fast-paced, making it very difficult for players to achieve a conscious control of their game strategies, expert players regularly outperform non-experts, possibly with strategies residing out of conscious control. In this study, we used Morra as a naturalistic setting to investigate the necessity of attentive control in generation of sequence of items and the ability to proceduralize random number generation, which are both a crucial defensive strategy in Morra and a well-known empirical procedure to test the central executive capacity within the working memory model. We recorded the sequence of numbers generated by expert players in a Morra tournament in Sardinia (Italy) and by undergraduate students enrolled in a course-based research experience (CRE) course at Lawrence Technological University in the United States. Number sequences generated by non-expert and expert players both while playing Morra and in a random number generation task (RNGT) were compared in terms of randomness scores. Results indicate that expert players of Morra largely outperformed non-experts in the randomness scores only within Morra games, whereas in RNGT the two groups were very similar. Importantly, survey data acquired after the games indicate that expert players have very poor conscious recall of their number generation strategies used during the Morra game. Our results indicate that the ability of generating random sequences can be proceduralized and do not necessarily require attentive control. Results are discussed in the framework of the dual processing theory and its automatic-parallel-fast vs. controlled-sequential-slow polarities.

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“…In this study, we addressed two fundamental aspects in this matter: the implication of memory processes and the dependence upon external (environmental) factors. Regarding memory, one hypothesis holds that in human, the process of generating random patterns leverages memory 24 , to ensure the equality of response usage for example 25 . Such a procedure could indeed render choices uniformly distributed but is also very likely to produce structured sequences (i.e.…”

Section: U-turns (%)mentioning

confidence: 99%

Mice adaptively generate choice variability in a deterministic task

et al. 2020

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Can decisions be made solely by chance? Can variability be intrinsic to the decision-maker or is it inherited from environmental conditions? To investigate these questions, we designed a deterministic setting in which mice are rewarded for non-repetitive choice sequences, and modeled the experiment using reinforcement learning. We found that mice progressively increased their choice variability. Although an optimal strategy based on sequences learning was theoretically possible and would be more rewarding, animals used a pseudo-random selection which ensures high success rate. This was not the case if the animal is exposed to a uniform probabilistic reward delivery. We also show that mice were blind to changes in the temporal structure of reward delivery once they learned to choose at random. Overall, our results demonstrate that a decision-making process can self-generate variability and randomness, even when the rules governing reward delivery are neither stochastic nor volatile.

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A Time Series Approach to Random Number Generation: Using Recurrence Quantification Analysis to Capture Executive Behavior

Cited by 13 publications

References 38 publications

Age Differences in Prospective Memory: A Further Evaluation of the Executive Framework

Age Differences in Prospective Memory: A Further Evaluation of the Executive Framework

The Morra Game as a Naturalistic Test Bed for Investigating Automatic and Voluntary Processes in Random Sequence Generation

Mice adaptively generate choice variability in a deterministic task

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