On producing random binary sequences

Nickerson, Raymond S.; Butler, Susan F.

doi:10.2307/27784387

Cited by 18 publications

(8 citation statements)

References 22 publications

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“…In some experimental versions participants were simply asked to make random choices ( Oomens et al, 2015 ; Sisti et al, 2018 ), others used analogies and mental models to illustrate the concept of randomness, such as the hat analogy, where one imagines to blindly draw pieces of paper with numbers written on them out of a hat, reads them out loud and puts them back in the hat ( Joppich et al, 2004 ). Also often used were die or coin analogies, where the instructions were to report the results of an imagined die ( Knoch et al, 2004 ) or coin toss ( Nickerson and Butler, 2009 ). A different way of instructing has been to encourage unpredictability by avoiding “schemes” or patterns ( Daniels et al, 2003 ).…”

Section: The Role Of Instructions In Randomization Tasksmentioning

confidence: 99%

“…Traditionally, randomization performance has been assessed by random sequence generation (RSG) tasks where participants are required to make a series of random choices from a predetermined set of options (see Nickerson, 2002 ). Commonly used choice sets are the digits from 0–9 ( Joppich et al, 2004 ), binary sets, e.g., 0/1 or heads/tails ( Nickerson and Butler, 2009 ), letters A-I ( Jahanshahi and Dirnberger, 1999 ), nouns ( Heuer et al, 2010 ) or symbols on Zener cards ( Sisti et al, 2018 ). However, experimental parameters have varied considerably throughout different RSG versions, including especially the way participants were instructed to be random ( Wagenaar, 1972 ).…”

Section: Introductionmentioning

confidence: 99%

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Instruction effects on randomness in sequence generation

et al. 2023

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Randomness is a fundamental property of human behavior. It occurs both in the form of intrinsic random variability, say when repetitions of a task yield slightly different behavioral outcomes, or in the form of explicit randomness, say when a person tries to avoid being predicted in a game of rock, paper and scissors. Randomness has frequently been studied using random sequence generation tasks (RSG). A key finding has been that humans are poor at deliberately producing random behavior. At the same time, it has been shown that people might be better randomizers if randomness is only an implicit (rather than an explicit) requirement of the task. We therefore hypothesized that randomization performance might vary with the exact instructions with which randomness is elicited. To test this, we acquired data from a large online sample (n = 388), where every participant made 1,000 binary choices based on one of the following instructions: choose either randomly, freely, irregularly, according to an imaginary coin toss or perform a perceptual guessing task. Our results show significant differences in randomness between the conditions as quantified by conditional entropy and estimated Markov order. The randomization scores were highest in the conditions where people were asked to be irregular or mentally simulate a random event (coin toss) thus yielding recommendations for future studies on randomization behavior.

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Section: The Role Of Instructions In Randomization Tasksmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Instruction effects on randomness in sequence generation

et al. 2023

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“…Their sequences sometimes avoid long runs of a single outcome, and other regularities (Nickerson, 2002). Occasionally, however, researchers do report an abundance of button repetitions in the sequences (e.g., Neuringer, 1986; Nickerson & Butler, 2009).…”

Section: Renormalization Group Theorymentioning

confidence: 99%

Embodied nonlinear dynamics of cognitive performance.

Annand¹,

Holden²

2023

Journal of Experimental Psychology: General

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Study participants are typically unable to generate binary button-press sequences that pass as classically random sequences, such as from successive "fair coin" flips. Instead, their sequences repeat or alternate between responses too often. These deviations from randomness are commonly explained in terms of limitations or idiosyncrasies in cognitive processing. This article tests a novel hypothesis that randomness departures in participant-generated binary sequences are driven by coordination dynamics; alternating and repeating sequences are related to bimanual coordination attractors. Participants (N = 128) were asked to generate sequences that were representative of a random sequence, by successively pressing either of two buttons across 1,600 trials. Statistical analyses identify the binary button-press dynamics with a discrete sine-circle version of the Haken, Kelso, Bunz bimanual coordination model. Permutation analyses revealed the most common one-to five-trial subsequences were identified with the most dynamically stable coordinative relationships, consistent with bimanual coordination predictions. The sequences were consistent with scaling noises. Thus, participants' sequences departed from classical randomness by virtue of membership in a more inclusive category of variability that subsumes classical randomness. Recurrence quantification analysis revealed the mixture of stochasticity and determinism in the sequences was better approximated by the sine-circle model than by phase-randomized surrogate data sets that preserved both the power spectral densities and distributions of each participant's sequence. A relationship between randomness production and two-alternative forced-choice performance is established that constrains response time distribution models. The article's organization illustrates a nonreductive approach to inference for cognitive systems, inspired by statistical physics concepts such as renormalization group theory and universality.

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“…There is no standardized experimental procedure in RSG studies. Instead RSG has employed a variety of tasks and parameters, such as different numbers of choice options, such as the digits from 0-9 (Joppich et al, 2004), binary sets e.g., 0/1 or heads/tails (Nickerson & Butler, 2009), the letters A-I (Jahanshahi & Dirnberger, 1999), or nouns (Heuer et al, 2010). Another variable task parameter across RSG experiments is the method of instructing participants to be random, which ranges from analogies like drawing numbers from a hat (Jahanshahi et al, 2000), tossing a coin (Nickerson & Butler, 2009) or roll a die (Knoch et al, 2004), via instructing to avoid specific patterns (Azouvi et al, 1996; Daniels et al, 2003) all the way to emphasizing unpredictability (Finke, 1984).…”

Section: Introductionmentioning

confidence: 99%

Neural Correlates of Different Randomization Tasks

Guseva,

Bogler,

Allefeld

et al. 2024

Preprint

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In some cases, when we are making decisions, the available choices can appear to be equivalent. When this happens, our choices appear not to be constrained by external factors and instead we can believe to be selecting "randomly". Furthermore, randomness is sometimes even explicitly required by task conditions such as in random sequence generation (RSG) tasks. This is a challenging task that involves the coordination of multiple cognitive processes, which can include the inhibition of habitual choice patterns and monitoring of the running choice sequence. It has been shown that random choices are strongly influenced by the way they are instructed. This raises the question whether the brain mechanisms underlying random selection also differ between different task instructions. To assess this, we measured brain activity while participants were engaging in three different variations of a sequence generation task: Based on previous work, participants were instructed to either (1) "generate a random sequence of choices", (2) "simulate a fair coin toss", or (3) "choose freely". Our results reveal a consistent frontoparietal activation pattern that is shared across all tasks. Specifically, increased activity was observed in bilateral inferior and right middle frontal gyrus, left pre-supplementary motor area, bilateral inferior parietal lobules and portions of anterior insular cortex in both hemispheres. Activity in the mental coin toss condition was higher in right dorsolateral prefrontal cortex, left (pre-) supplementary motor area, a portion of right inferior frontal gyrus, bilateral superior parietal lobules and bilateral anterior insula. Additionally, our multivariate analysis revealed a distinct region in the right frontal pole to be predictive of the outcome of choices, but only when randomness was explicitly instructed. These results emphasize that different randomization tasks involve both shared and unique neural mechanisms. Thus, even seemingly similar randomization behavior can be produced by different neural pathways.

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On producing random binary sequences

Cited by 18 publications

References 22 publications

Instruction effects on randomness in sequence generation

Instruction effects on randomness in sequence generation

Embodied nonlinear dynamics of cognitive performance.

Neural Correlates of Different Randomization Tasks

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