Stochastic simulation of the circadian rhythmicity in the SCN neuronal network

• We propose a stochastic multicellular model of the circadian activity in the SCN.
• The SCN neuronal network turned out to be a reliable setup that is robust to noise.
• The intercellular coupling was found crucial for precise circadian timing.
• The SCN neuronal activity patterns form locally synchronized clusters.

The suprachiasmatic nucleus (SCN) of the hypothalamus is the mammalian circadian pacemaker that plays a dominant role in the generation and control of daily physiological and behavioral rhythms. The coupling of the SCN neuronal activity with the solar day–night cycle and the intercellular communication between SCN neurons are the most important factors that ensure the precise 24 h timing of the circadian rhythmicity. In individual cells, however, the timekeeping is not precise because of the inherent randomness in the biochemical reactions. In order to investigate the impact of molecular noise and intercellular connectivity on the circadian network synchronization, we develop a stochastic multicellular model of the SCN. The circadian pacemaker is modeled as a realistic small-world network of neurons and was found to be robust to rather high levels of intrinsic fluctuations. We show that the SCN neuronal network synchronizes well with the photic entraining even at very large levels of stochasticity, whereby intercellular coupling is the required agent that ensures coherent oscillations. Furthermore, we show that the neuronal activity patterns form localized clusters, which are more pronounced in short photoperiods than in long days. The localized synchronization behavior was also found to be affected by the SCN network structure.