Plasticity in the period of the circadian pacemaker induced by phase dispersion of its constituent cellular clocks

Domien G. M. Beersma*, Kim A. Gargar, Serge Daan

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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The mammalian circadian pacemaker is commonly thought to be a rigid oscillator that generates output under a variety of circumstances that differ only in phase, period, and/or amplitude. Yet the pacemaker is composed of many cells that each can respond to varying circumstances in different ways. Computer simulations demonstrate that networks of such pacemaker cells behave differently under a light-dark cycle compared with constant darkness. The differences demonstrate that the circadian pacemaker is plastic: The pacemaker shapes its properties in response to the circumstances. A consequence is that properties of a pacemaker under a light-dark cycle cannot be derived from studies of the same system in constant darkness. In this paper we show that the dispersion of phase in a network of coupled oscillators can influence ensemble period: For the considered type of coupling, it is demonstrated that the more synchronous the cells are, the longer is the ensemble period. This is consistent with various data sets obtained in mammals, and even with a data set from fruit flies, in which circadian variation in behavior is regulated in a distinctly differently way from that in mammals. We conclude that environmental circumstances such as photoperiod and exposure to light pulses in otherwise darkness modify the phase distribution of the network and, thereby, the period of the ensemble. Our study supports the view that such properties as circadian period are not solely determined by clock genes but are also determined by the genes that regulate the communication in cellular networks.

Original languageEnglish
Pages (from-to)237-245
Number of pages9
JournalJournal of Biological Rhythms
Issue number3
Publication statusPublished - Jun-2017


  • circadian period
  • SCN
  • neuronal network
  • computer model
  • transient phase shifts
  • seasonal change
  • GABA

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