Disassortative Network Structure Improves the Synchronization between Neurons in the Suprachiasmatic Nucleus. Issue 5 (October 2019)

• Record Type: Journal Article
• Authors: Gu, Changgui; Gu, Xiangwei; Wang, Ping; Ren, Henggang; Weng, Tongfeng; Yang, Huijie; Rohling, Jos H. T.
• Is Part Of: Journal of biological rhythms. Volume 34:Issue 5(2019)
• Page Start: 515
• Page End: 524
• Publication Date: 2019-10
• Subjects: transfer entropy -- short time series -- causality -- robust circadian rhythms -- weak circadian rhythms; Biological rhythms -- Periodicals; Circadian rhythms -- Periodicals; 571.77
• DOI: 10.1177/0748730419861765
• Languages: English
• ISSNs: 0748-7304

Abstract

In mammals, an endogenous clock located in the suprachiasmatic nucleus (SCN) of the brain regulates the circadian rhythms of physiological and behavioral activities. The SCN is composed of about 20, 000 neurons that are autonomous oscillators with nonidentical intrinsic periods ranging from 22 h to 28 h. These neurons are coupled through neurotransmitters and synchronized to form a network, which produces a robust circadian rhythm of a uniform period. The neurons, which are the nodes in the network, are known to be heterogeneous in their characteristics, which is reflected in different phenotypes and different functionality. This heterogeneous nature of the nodes of the network leads to the question as to whether the structure of the SCN network is assortative or disassortative. Thus far, the disassortativity of the SCN network has not been assessed and neither have its effects on the collective behaviors of the SCN neurons. In the present study, we build a directed SCN network composed of hundreds of neurons for a single slice using the method of transfer entropy, based on the experimental data. Then, we measured the synchronization degree as well as the disassortativity coefficient of the network structure (calculated by either the out-degrees or the in-degrees of the nodes) and found that the network of the SCN is a disassortative network. Furthermore, a positive relationship is observed between the synchronization degree and disassortativity of the network, which is confirmed by simulations of our modeling. Our finding suggests that the disassortativity of the network structure plays a role in the synchronization between SCN neurons; that is, the synchronization degree increases with the increase of the disassortativity, which implies that a more heterogeneous coupling in the network of the SCN is important for proper function of the SCN.