Temporal organization of rest defined by actigraphy data in healthy and childhood chronic fatigue syndrome children
- Equal contributors
1 Department of Stem Cell Biology, Institute of Embryology and Genetics, Kumamoto University, Kumamoto, Japan
2 Kuwamizu Hospital, Kumamoto, Japan
3 Department of Child Development, Faculty of Life Sciences, Kumamoto University, Kumamoto, Japan
4 Research Center for Child Mental Development, Fukui University, Fukui, Japan
5 Department of Neuropharmacology, Graduate School of Pharmaceutical Sciences, Nagoya City University, Tanabe Street, Mizuho, Nagoya 467-8603, Japan
BMC Psychiatry 2013, 13:281 doi:10.1186/1471-244X-13-281Published: 4 November 2013
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.
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).
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.
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.