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Updated: Jun 18, 2026

Recording and Analysis of Circadian Rhythms in Running-wheel Activity in Rodents
Published on: January 24, 2013
Correlation with behavioral activity and rest implies circadian regulation by SCN neuronal activity levels
Thijs Houben1, Tom Deboer, Floor van Oosterhout
1Department of Molecular Cell Biology, Leiden University Medical Centre, the Netherlands.
Abstract:
The SCN of the hypothalamus contains a major pacemaker, which exhibits 24-h rhythms in electrical impulse frequency. Although it is known that SCN electrical activity is high during the day and low during the night, the precise relationship between electrical activity and behavioral rhythms is almost entirely unknown. The authors performed long-term recordings of SCN multiple unit activity with the aid of implanted microelectrodes in parallel with the drinking activity in freely moving mice. The animals were kept in a 12h:12h light-dark cycle (LD 12:12) and in short-day (LD 8:16) and long-day photoperiods (LD 16:8). Onsets and offsets of behavioral activity occurred when SCN discharge was around half-maximum value. Of the onsets 80%, and of the offsets 62%, occurred when SCN electrical activity differed less than 15% from the half-maximum electrical activity levels. Transitions between rest and activity could be described by a sigmoid shaped probability curve with Hill coefficients of 7.0 for onsets and 5.7 for offsets. The similarity in the onset and offset levels shows an absence of hysteresis in the control of behavioral activity by the SCN. Exposure to short- or long-day photoperiods induced significant alterations in the waveform of electrical activity but did not affect SCN electrical activity levels at which behavioral transitions occurred. In all photoperiods, the SCN signal was skewed with more rapid discharge changes during onsets (19% per hour) than offsets (11% per hour). The precision of the circadian system appears optimized, as transitions between behavioral activity and rest occur when the change in SCN electrical activity is maximal, both during the declining and rising phase. The authors conclude that transitions in behavioral state can be described by a probability function around half-maximum electrical activity levels and that the parameters of the SCN, predicting onset and offset of behavior, are remarkably insensitive to environmental conditions.
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