Abstract
The main function of the principal clock located in the suprachiasmatic nucleus (SCN) of mammals is synchronizing the body rhythms to the 24 h light-dark cycle. Additionally, the SCN is able to adapt to the photoperiod of the cycle which varies among seasons. Under the long photoperiod (LP), the synchronization degree of the SCN neurons is lower than that under the photoperiod (SP). In the present study, a potential explanation is given for this phenomenon. We propose that the asymmetrical coupling between the light-signal-sensitive part (the ventralateral part, abbreviation: VL) and the light-signal-insensitive part (the dorsalmedial part, abbreviation: DM) of the SCN plays a role in the synchronization degree, which is reflected by the ratio of the number of the directed links from the VL neurons to the DM neurons to the total links of both directions between the VL and the DM. The ratio is assumed to characterize the directed network structure under different photoperiods, which is larger under the SP and smaller under the LP. We found that with the larger ratio in the situation of the SP, the synchronization degree is higher. Our finding may shed new light on the asymmetrical coupling between the VL and the DM, and the network structure of the SCN.
Highlights
The coupling between the VL and the DM is found to be asymmetrical
An alternative explanation was given for the distinct synchronization between the suprachiasmatic nucleus (SCN) neurons under different photoperiods by considering the asymmetrical coupling between the light-signal-sensitive VL part and the light-signal-insensitive DM part[4]
The ratio is assumed to reflect the directed network structure under different photoperiods, which is larger under the short photoperiod (SP) and smaller under the long photoperiod (LP)
Summary
Two kinds of models are used to describe the SCN neuronal oscillators, i.e. biochemical models such as Goodwin model[19,21,22] and Leloup-Goldbeter model[38], and phenomenological models such as Kuramoto model[21,39,40] and Poincaré model[41,42]. The Goodwin model takes both the neuronal phase and amplitude into account[19,21,22], which is based on the transcription-translation feedback loop in one single neuronal oscillator. The SCN network is assumed to be a directed Newman-Watts network which is established as follows[34]: at the first step, if the physical distance between two nodes i and j is smaller than a predefined value d, there are directed links Ai,j =Aj,i = 1 within the VL (DM); at the second step, j is directly linked to i (Aj,i = 1) with possibility p within the VL (i, j = 1, 2, ..., Nv) or DM (i, j = Nv + 1, Nv + 2, ..., N); Figure 1. The Goodwin model is taken into account where the results confirm our findings by the Kuramoto model
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
