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Diurnal variation of motor activity in adult ADHD patients analyzed with methods from graph theory

Author

Listed:
  • Ole Bernt Fasmer
  • Erlend Eindride Fasmer
  • Kristin Mjeldheim
  • Wenche Førland
  • Vigdis Elin Giæver Syrstad
  • Petter Jakobsen
  • Jan Øystein Berle
  • Tone E G Henriksen
  • Zahra Sepasdar
  • Erik R Hauge
  • Ketil J Oedegaard

Abstract

Attention-deficit /hyperactivity disorder (ADHD) is a common neurodevelopmental syndrome characterized by age-inappropriate levels of motor activity, impulsivity and attention. The aim of the present study was to study diurnal variation of motor activity in adult ADHD patients, compared to healthy controls and clinical controls with mood and anxiety disorders. Wrist-worn actigraphs were used to record motor activity in a sample of 81 patients and 30 healthy controls. Time series from registrations in the morning and evening were analyzed using measures of variability, complexity and a newly developed method, the similarity algorithm, based on transforming time series into graphs. In healthy controls the evening registrations showed higher variability and lower complexity compared to morning registrations, however this was evident only in the female controls. In the two patient groups the same measures were not significantly different, with one exception, the graph measure bridges. This was the measure that most clearly separated morning and evening registrations and was significantly different both in healthy controls and in patients with a diagnosis of ADHD. These findings suggest that actigraph registrations, combined with mathematical methods based on graph theory, may be used to elucidate the mechanisms responsible for the diurnal regulation of motor activity.

Suggested Citation

  • Ole Bernt Fasmer & Erlend Eindride Fasmer & Kristin Mjeldheim & Wenche Førland & Vigdis Elin Giæver Syrstad & Petter Jakobsen & Jan Øystein Berle & Tone E G Henriksen & Zahra Sepasdar & Erik R Hauge &, 2020. "Diurnal variation of motor activity in adult ADHD patients analyzed with methods from graph theory," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-18, November.
    • Handle: RePEc:plo:pone00:0241991
    DOI: 10.1371/journal.pone.0241991
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    References listed on IDEAS

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    1. Erik R Hauge & Jan Øystein Berle & Ketil J Oedegaard & Fred Holsten & Ole Bernt Fasmer, 2011. "Nonlinear Analysis of Motor Activity Shows Differences between Schizophrenia and Depression: A Study Using Fourier Analysis and Sample Entropy," PLOS ONE, Public Library of Science, vol. 6(1), pages 1-10, January.
    2. Karoline Krane-Gartiser & Tone Elise Gjotterud Henriksen & Gunnar Morken & Arne Vaaler & Ole Bernt Fasmer, 2014. "Actigraphic Assessment of Motor Activity in Acutely Admitted Inpatients with Bipolar Disorder," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-9, February.
    3. Erlend Eindride Fasmer & Ole Bernt Fasmer & Jan Øystein Berle & Ketil J Oedegaard & Erik R Hauge, 2018. "Graph theory applied to the analysis of motor activity in patients with schizophrenia and depression," PLOS ONE, Public Library of Science, vol. 13(4), pages 1-19, April.
    4. B. Aguilar-San Juan & L. Guzmán-Vargas, 2013. "Earthquake magnitude time series: scaling behavior of visibility networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 86(11), pages 1-10, November.
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