Light Regulates c-fos Gene Expression in the Hamster SCN: Implications for Circadian and Seasonal Control of Reproduction

  • Jon M. Kornhauser
  • Dwight E. Nelson
  • Kelly E. Mayo
  • Joseph S. Takahashi
Part of the Serono Symposia USA book series (SERONOSYMP)


The naturally occurring daily cycle of light and darkness in the environment exerts important control upon the function of the reproductive system in mammals, providing external timing cues that influence reproductive physiology in two distinct ways. First, the light-dark cycle serves to synchronize the circadian timekeeping system, and this circadian pacemaker regulates daily periodic events of the neuroendocrine axis. Second, many mammals breed on a seasonal basis, and the length of the day is the most important environmental factor regulating these dramatic seasonal changes in reproduction. The circadian pacemaking system mediates effects of this type by measuring changes in the photoperiod corresponding to seasonal alterations in day length (1). The suprachiasmatic nucleus (SCN) of the hypothalamus is the site of the predominant circadian pacemaker regulating behavioral and physiological processes in mammals, including the reproductive axis, (2–4). Timing signals from this pacemaker coordinate circadian components of reproductive rhythms; for example, the time of occurrence of the preovulatory surges in luteinizing hormone (LH) and follicle stimulating hormone (FSH) and of ovulation during proestrus (1, 5). The SCN also mediates the effects of alterations in photoperiod on seasonal changes in reproductive function. Thus, the circadian pacemaker in the SCN utilizes photic information for synchronization of endogenous rhythms to the environmental 24-h light cycle and for measurement of changes in day length for photoperiodic regulation of reproduction.


Nerve Growth Factor Circadian Rhythm Circadian Clock Golden Hamster Suprachiasmatic Nucleus 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag New York, Inc. 1992

Authors and Affiliations

  • Jon M. Kornhauser
  • Dwight E. Nelson
  • Kelly E. Mayo
  • Joseph S. Takahashi

There are no affiliations available

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