Synchronization, clustering, and weak chimeras in a densely coupled transcription-based oscillator model for split...

Area of Science:

• * Chronobiology and computational neuroscience.
• * Investigating the suprachiasmatic nucleus (SCN) and circadian rhythms.

Background:

• * The suprachiasmatic nucleus (SCN) is the master circadian pacemaker in mammals.
• * Circadian gene expression within the SCN governs daily rhythms.
• * Light intensity is a critical environmental factor influencing SCN function.

Purpose of the Study:

• * To model and understand the synchronization dynamics of circadian gene expression in the SCN under different light conditions.
• * To investigate how these dynamics relate to activity patterns and potential clock splitting.
• * To explore the memory effects and emergent states like chimera states in SCN networks.

Main Methods:

• * Utilized a transcriptional circadian clock gene oscillator model.
• * Simulated network dynamics under constant dark (DD), dim light (dim LL), and bright light (bright LL) conditions.
• * Employed analytical methods by extracting phase models from ordinary differential equation models.

Main Results:

• * Observed distinct synchronization states: one-cluster in DD, bistability in dim LL, and two-cluster in bright LL.
• * The two-cluster state explains circadian clock splitting and bimodal activity patterns.
• * Demonstrated memory effects in circadian synchrony and the emergence of weak-chimera and chimera states with network heterogeneity.

Conclusions:

• * Light intensity critically modulates SCN oscillator synchronization, impacting daily rhythms.
• * Circadian synchrony exhibits memory, influenced by prior light exposure.
• * Computational models provide insights into SCN network complexity and guide experimental research on circadian desynchronization.