Reliability and correlates of intra-individual variability in the oculomotor system

Perquin, Marlou Nadine; Bompas, Aline

doi:10.16910/jemr.12.6.11

Cited by 7 publications

(11 citation statements)

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“…As ADHD is a multi-faceted condition, potential correlations between temporal structure and ADHD tendency would reveal little about the driving mechanism. For the first cohort, we therefore also included a questionnaire on impulsivity (one of the main two facets of ADHD) and a questionnaire on mind wandering tendencies, which has been associated with ADHD tendencies both in healthy and clinical participants (Perquin & Bompas, 2019 ; Seli et al, 2015 ; Shaw & Giambra, 1993 ; Unsworth et al, 2019 ) and may reflect an individual tendency towards getting off-task. However, anticipating on our results, we found clear statistical evidence against between-subject correlations across all three questionnaires and temporal dependency on the first cohort.…”

Section: Current Researchmentioning

confidence: 99%

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Temporal Structure in Sensorimotor Variability: A Stable Trait, But What For?

et al. 2023

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Human performance shows substantial endogenous variability over time, and this variability is a robust marker of individual differences. Of growing interest to psychologists is the realisation that variability is not fully random, but often exhibits temporal dependencies. However, their measurement and interpretation come with several controversies. Furthermore, their potential benefit for studying individual differences in healthy and clinical populations remains unclear. Here, we gather new and archival datasets featuring 11 sensorimotor and cognitive tasks across 526 participants, to examine individual differences in temporal structures. We first investigate intra-individual repeatability of the most common measures of temporal structures — to test their potential for capturing stable individual differences. Secondly, we examine inter-individual differences in these measures using: (1) task performance assessed from the same data, (2) meta-cognitive ratings of on-taskness from thought probes occasionally presented throughout the task, and (3) self-assessed attention-deficit related traits. Across all datasets, autocorrelation at lag 1 and Power Spectra Density slope showed high intra-individual repeatability across sessions and correlated with task performance. The Detrended Fluctuation Analysis slope showed the same pattern, but less reliably. The long-term component (d) of the ARFIMA(1,d,1) model showed poor repeatability and no correlation to performance. Overall, these measures failed to show external validity when correlated with either mean subjective attentional state or self-assessed traits between participants. Thus, some measures of serial dependencies may be stable individual traits, but their usefulness in capturing individual differences in other constructs typically associated with variability in performance seems limited. We conclude with comprehensive recommendations for researchers.

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Section: Current Researchmentioning

confidence: 99%

“…For transparency purposes, we do report all taken measures from the experiments. Questionnaire scores and eye movement data recorded before and after the task for cohort 1 are published in Perquin and Bompas ( 2019 ), alongside other datasets. This study was not preregistered.…”

Section: Appendixmentioning

confidence: 99%

Temporal Structure in Sensorimotor Variability: A Stable Trait, But What For?

et al. 2023

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“…As both data cohorts have been collected in collaborative projects, including student undergraduate projects, not all measures were analysed for the current research aims. For transparency purposes, we do report all taken measures from the experiments. Questionnaire scores and eye movement data recorded before and after the task for cohort 1 are published in Perquin & Bompas (2019), alongside other datasets. This study was not preregistered.…”

Section: Metronome Taskmentioning

confidence: 99%

“…Questionnaire scores and eye movement data recorded before and after the task for cohort 1 are published in Perquin & Bompas (2019), alongside other datasets. This study was not preregistered.…”

Section: Author Notementioning

confidence: 99%

“…As ADHD is a multi-faceted condition, potential correlations between temporal structure and ADHD tendency would reveal little about the driving mechanism. For the first cohort, we therefore also included a questionnaire on impulsivity (one of the main two facets of ADHD) and a questionnaire on mind wandering tendencies, which has been associated with ADHD tendencies both in healthy and clinical participants (Perquin & Bompas, 2019; Shaw & Giambra, 1993; Seli, Smallwood, Cheyne & Smilek, 2015; Unsworth, Robison & Miller, 2019) and may reflect an individual tendency towards getting off-task. However, anticipating on our results, we found clear statistical evidence against between-subject correlations across all three questionnaires and temporal dependency on the first cohort.…”

Section: Introductionmentioning

confidence: 99%

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Temporal structure in sensorimotor variability: a stable trait, but what for?

Perquin¹,

Bompas²

2019

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Human performance shows substantial endogenous variability over time. Such variability has been known to show temporal structures: Performance from action to action is not independent, but shows correlation with itself over time. While the existence of such dependencies has been frequently reported on, its measurement and interpretation come with a number of controversies, and its potential benefit for studying individual differences remains unclear. Two recent studies have linked temporal structures to individual differences in task performance, but with contrasting results. In the current study, we aim to investigate the intra-individual repeatability of these temporal structures in endogenous performance on the Metronome Task (25 participants, tested in two sessions ~45 minutes apart). Secondly, we examine the inter-individual correlates of the temporal structures (83 participants), specifically looking at: 1) task performance, 2) meta-cognitive ratings of attentional state, and 3) self-assessed personality traits (ADHD tendencies, mind wandering, and impulsivity).Rather than using one analysis method (as is common in the literature), we consistently compare all the frequently-used analysis methodsallowing us to investigate the structures without an a prior assumption on the underlying time scales.Results indicate that autocorrelation at lag 1 and Power Spectra Density slope showed the most intra-individual repeatability, ARFIMA(1,d,1) parameters showed the least, and evidence for Detrended Fluctuation Analysis was indeterminate with a moderate effect size at best. Overall, the autocorrelation at lag 1 seemed the best measure for studying individual differences, due to its high reliability and ease of use. Furthermore, with exception of the ARFIMA parameters, temporal structure was correlated with performance but not with subjective attentional state or self-assessed personality traits between participants.

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