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On the temporal characteristics of performance variability in attention deficit hyperactivity disorder (ADHD).

  • B. Feige
  • , Monica Biscaldi
  • , Christopher Saville
  • , C. Kluckert
  • , Stephan Bender
  • , Ulrich Ebner-Priemer
  • , K. Henighausen
  • , R. Rauh
  • , C. Fleischhaker
  • , Christoph Klein
    • University of Freiburg
    • Technische Universität Dresden
    • Karlsruhe Institute of Technology

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Increased intra-subject variability of reaction times (ISV-RT) is one of the most consistent findings in attention-deficit/hyperactivity disorder (ADHD). Although the nature of this phenomenon is still unclear, it has been hypothesised to reflect interference from the Default Mode Network (DMN). So far, ISV-RT has been operationally defined either as a frequency spectrum of the underlying RT time series, or as a measure of dispersion of the RT scores distribution. Here, we use a novel RT analysis framework to link these hitherto unconnected facets of ISV-RT by determining the sensitivity of different measures of RT dispersion to the frequency content of the underlying RT time series. N=27 patients with ADHD and N=26 healthy controls performed several visual N-back tasks. Different measures of RT dispersion were repeatedly modelled after individual frequency bands of the underlying RT time series had been either extracted or suppressed using frequency-domain filtering. We found that the intra-subject standard deviation of RT preserves the "1/f noise" characteristic typical of human RT data. Furthermore and most importantly, we found that the ex-Gaussian parameter τ is rather exclusively sensitive to frequencies below 0.025 Hz in the underlying RT time series and that the particularly slow RTs, which nourish τ, occur regularly as part of an quasi-periodic, ultra-slow RT fluctuation. Overall, our results are compatible with the idea that ISV-RT is modulated by an endogenous, slowly fluctuating process that may reflect DMN interference.
    Original languageEnglish
    Pages (from-to)e69674
    JournalPLoS ONE
    DOIs
    Publication statusPublished - 2 Oct 2013

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

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