Ultradian components in the locomotor activity rhythms of the genetically normal mouse, Mus musculus.
Ultradian periodicities in physiological processes have been reported for a wide variety of organisms and may appear as bouts in locomotor activity. In some instances, this temporal organization can be related to some ethological strategy. In mice, however, ultradian rhythms have been reported largely in animals with circadian pacemakers disrupted either by genetic or surgical manipulation. Using analysis techniques capable of resolving periodicities in the ultradian range in the presence of strong diel periodicity, we found unequivocal evidence of ultradian rhythms in mice entrained to an light:dark cycle. We collected locomotor activity data of individuals from 11 genetically disparate strains of mice whose activity was recorded in 12 h:12 h L:D photoperiods for 3 days. Data were subjected to maximum entropy spectral analysis and autocorrelation, both before and after filtering to remove the 24-h periodicity. We found that every strain had a majority of individuals with strong ultradian rhythms ranging from ~3 to ~5 h. These periodicities were commonly visible in individual animals both in high-pass-filtered and in unfiltered data. Furthermore, when all raw data from a given strain were pooled to get a 24-h ensemble average across all animals and days, the rhythms continued to be discernable. We fitted Fourier series to these form estimates to model the frequency structure of each strain and found significant effects of strain and an interaction between period and strain indicating significant genetic variation for rhythmicity in the ultradian range. The techniques employed in this study should have wider use in a range of organisms and fields.
Dowse
Harold
H
School of Biology and Ecology, University of Maine, Orono, ME 04469, USA. dowse@maine.edu
Umemori
Juzoh
J
Koide
Tsuyoshi
T
D000204:Activity Cycles / Q000502:physiology*; D000818:Animals; D051379:Mice; D009043:Motor Activity / Q000502:physiology*; D013057:Spectrum Analysis