synchrony" protocol on the five healthy volunteers who participated in the study. For 10 days, the participants lived in dimly lit rooms cut off from any outside stimuli or time cues. The researchers adjusted scheduled behaviors (sleeping periods, eating, and the like), gradually shifting the behavior patterns until the participants had a 28-hour day, about 19 hours awake and 9 hours asleep. This 28-hour sleep/wake schedule was sustained for seven "days," while core body temperatures, used to mark participants' internal circadian phases, continued to oscillate with an approximate 24-hour period, indicating their sleep/wake cycles had been experimentally separated from their circadian cycles.
Using heartbeat data gathered from the participants throughout the 10-day desynchrony, Ivanov and BU team members Kun Hu and Zhi Chen, research assistants in physics, estimated correlations in the heartbeat fluctuations according to a power law function quantified using a method known as a detrended fluctuation analysis (DFA). The DFA mathematically describes the fluctuations at different time scales in the heartbeat signal and produces a scaling exponent that characterizes the degree of correlation between heartbeat intervals. If, for example, the scaling exponent, known as , equaled 0.5, the interval fluctuations showed no correlation; if equaled 1.5, the interval fluctuations were considered to be without control, exhibiting a so-called random walk property. If, however, fell between 0.5 and 1.5, the interval fluctuations were considered to be organized and physiologically controlled. Interestingly, research studies have associated values progressing toward 1.5 with pathological conditions, such as congestive heart failure.
When the team analyzed wake period data, they found a striking correlation: values changed according to the internal body clock time. At 2 a.m., the value was 0.8; at 5 p.m., it was 1.0. However, at 10 a.m., the time of day fPage: 1 2 3 4 Related biology news :1
Contact: Ann Marie Menting
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