Discrete photoentrainment of mammalian central clock is regulated by bi-stable dynamic network in the suprachiasmatic nucleus

Abstract

The circadian clock, an evolutionarily conserved mechanism regulating the majority of physiological functions in many organisms, is synchronized with the environmental light-dark cycle through circadian photoentrainment. This process is mediated by light exposure at specific times, leading to a discrete phase shift including phase delays during early subjective night, phase advances during late subjective night, and no shift at midday, known as the dead zone. In mammals, such as mice, the intrinsically photosensitive retinal ganglion cells (ipRGCs) are crucial for conveying light information to the suprachiasmatic nucleus (SCN), the central clock consisting of approximately 20,000 neurons. While the intracellular signaling pathways that modulate clock gene expression post-light exposure are well-studied, the functional neuronal circuits responsible for the three discrete light responses are not well understood. Utilizing in vivo two-photon microscopy with gradient-index (GRIN) endoscopes, we have identified seven distinct light responses from SCN neurons. Our findings indicate that light responses from individual SCN neurons are mostly stochastic from trial to trial. However, at the population level, light response composition remains similar across trials, with only minor variations between circadian times, suggesting a dynamic populational coding for light input. Additionally, only a small subset of SCN neurons shows consistent light responses. Furthermore, by utilizing the targeted recombination in active populations (TRAP) system to label neurons that respond to light during early subjective night, we demonstrate that their activation can induce phase delays at any circadian time, effectively breaking the gate that produce photoentrainment dead zone typically observed at midday. Our results suggest the existence of at least two separate time-dependent functional circuits within the SCN. We propose a dynamic bi-stable network model for circadian photoentrainment in the mammalian central clock, where a shifting clock is driven by a dynamic functional circuit utilizing population coding to integrate information flow similar to proposed cortical computational network, rather than a simplistic, consistent linear circuit.