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Infant Auditory Processing and Event-related Brain Oscillations
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Temporal Structure in Sensorimotor Variability: A Stable Trait, But What For?

Marlou Nadine Perquin1,2,3, Marieke K van Vugt4, Craig Hedge5

  • 1Biopsychology & Cognitive Neuroscience, Faculty of Psychology and Sports Science, Bielefeld University, Bielefeld, Germany.

Computational Brain & Behavior
|January 9, 2023
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Summary
This summary is machine-generated.

Temporal dependencies in human performance can be stable individual traits. However, measures of these serial dependencies show limited usefulness for capturing individual differences in attention or related traits.

Keywords:
ADHDIntra-individual variabilityMind wanderingReaction time variabilityTapping

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Area of Science:

  • Cognitive psychology
  • Neuroscience
  • Behavioral science

Background:

  • Human performance exhibits inherent temporal variability, a key indicator of individual differences.
  • Temporal dependencies in performance, rather than being random, are of increasing interest in psychology.
  • Measuring and interpreting these temporal structures presents challenges and controversies, with unclear benefits for clinical and healthy populations.

Purpose of the Study:

  • To investigate individual differences in temporal structures of human performance across various tasks.
  • To assess the intra-individual repeatability of common temporal structure measures for capturing stable individual differences.
  • To examine inter-individual differences in temporal measures using task performance, meta-cognitive ratings, and self-assessed traits.

Main Methods:

  • Utilized new and archival datasets from 526 participants across 11 sensorimotor and cognitive tasks.
  • Analyzed intra-individual repeatability of temporal structure measures (autocorrelation, Power Spectra Density slope, Detrended Fluctuation Analysis slope, ARFIMA(1,d,1) model's long-term component).
  • Correlated temporal measures with task performance, on-taskness ratings from thought probes, and attention-deficit related traits.

Main Results:

  • Autocorrelation at lag 1 and Power Spectra Density slope demonstrated high intra-individual repeatability and correlated with task performance.
  • Detrended Fluctuation Analysis slope showed similar patterns but with less reliability.
  • The ARFIMA(1,d,1) model's long-term component exhibited poor repeatability and no correlation with performance.
  • Most temporal measures lacked external validity when correlated with subjective attentional states or self-assessed traits.

Conclusions:

  • Certain measures of serial dependencies in performance may represent stable individual traits.
  • The utility of these temporal measures for capturing individual differences in constructs like attention appears limited.
  • Provides recommendations for researchers on the measurement and interpretation of temporal structures in human performance.