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Temporal organization of rest defined by actigraphy data in healthy and childhood CFS

Discussion in 'Latest ME/CFS Research' started by Bob, Nov 5, 2013.

  1. Bob

    Bob

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    Temporal organization of rest defined by actigraphy data in healthy and childhood chronic fatigue syndrome children
    Minako Kawabata, Taro Ueno, Jun Tomita, Junko Kawatani, Akemi Tomoda, Shoen Kume and Kazuhiko Kume
    BMC Psychiatry 2013, 13:281
    doi:10.1186/1471-244X-13-281

    Published: 4 November 2013

    Provisional abstract:
    http://www.biomedcentral.com/1471-244X/13/281/abstract
    Provisional PDF:
    http://www.biomedcentral.com/content/pdf/1471-244X-13-281.pdf


    Abstract (provisional)

    Background
    Accumulating evidence has shown a universality in the temporal organization of activity and rest among animals ranging from mammals to insects. Previous reports in both humans and mice showed that rest bout durations followed long-tailed (i.e., power-law) distributions, whereas activity bouts followed exponential distributions. We confirmed similar results in the fruit fly, Drosophila melanogaster. Conversely, another report showed that the awakening bout durations, which were defined by polysomnography in bed, followed power-law distributions, while sleeping periods, which may correspond to rest, followed exponential distributions. This apparent discrepancy has been left to be resolved.

    Methods
    Actigraphy data from healthy and disordered children were analyzed separately for two periods: time out of bed (UP period) and time in bed (DOWN period).

    Results
    When data over a period of 24 h were analyzed as a whole, rest bouts showed a power law distribution as previously reported. However, when UP and DOWN period data were analyzed separately, neither showed power law properties. Using a newly developed strict method, only 30% of individuals satisfied the power law criteria, even when the 24 h data were analyzed. The human results were in contrast to the Drosophila results, which revealed clear power-law distributions for both day time and night time rest through the use of a strict method. In addition, we analyzed the actigraphy data from patients with childhood type chronic fatigue syndrome (CCFS), and found that they showed differences from healthy controls when their UP and DOWN data were analyzed separately.

    Conclusions
    These results suggested that the DOWN sleep, the bout distribution of which showed exponential properties, contributes to the production of long-tail distributions in human rest periods. We propose that separate analysis of UP and DOWN period data is important for understanding the temporal organization of activity.

     
  2. Bob

    Bob

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    I don't understand a word of it! :eek:
     
  3. Esther12

    Esther12 Senior Member

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    I don't get it either Bob.

    I had read something else that was using actigraphy to measure movement during sleep. Not sure if I'm willing to do the work needed on this one!
     
    Bob likes this.
  4. Snow Leopard

    Snow Leopard Senior Member

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    Lost in translation maybe?
     
    Bob likes this.
  5. Bob

    Bob

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    Perhaps it's a Google translation! :)
     
  6. MeSci

    MeSci ME/CFS since 1995; activity level 6

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    You mean we're different from flies? Who knew? :rolleyes:
     
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