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Quantitative Study of Dual Circadian Oscillator Models under Different Skeleton Photoperiods.

Danilo E F L FlôresGisele Akemi Oda
Published in: Journal of biological rhythms (2020)
The daily proportion of light and dark hours (photoperiod) changes annually and plays an important role in the synchronization of seasonal biological phenomena, such as reproduction, hibernation, and migration. In mammals, the first step of photoperiod transduction occurs in the suprachiasmatic nuclei (SCN), the circadian pacemaker that also coordinates 24-h activity rhythms. Thus, in parallel with its role in annual synchronization, photoperiod variation acutely shapes day/night activity patterns, which vary throughout the year. Systematic studies of this behavioral modulation help understand the mechanisms behind its transduction at the SCN level. To explain how entrainment mechanisms could account for daily activity patterns under different photoperiods, Colin Pittendrigh and Serge Daan proposed a conceptual model in which the pacemaker would be composed of 2 coupled, evening (E) and morning (M), oscillators. Although the E-M model has existed for more than 40 years now, its physiological bases are still not fully resolved, and it has not been tested quantitatively under different photoperiods. To better explore the implications of the E-M model, we performed computer simulations of 2 coupled limit-cycle oscillators. Four model configurations were exposed to systematic variation of skeleton photoperiods, and the resulting daily activity patterns were assessed. The criterion for evaluating different model configurations was the successful reproduction of 2 key behavioral phenomena observed experimentally: activity psi-jumps and photoperiod-induced changes in activity phase duration. We compared configurations with either separate light inputs to E and M or the same light inputs to both oscillators. The former replicated experimental results closely, indicating that the configuration with separate E and M light inputs is the mechanism that best reproduces the effects of different skeleton photoperiods on day/night activity patterns. We hope this model can contribute to the search for E and M and their light input organization in the SCN.
Keyphrases
  • physical activity
  • machine learning