Deciphering clock cell network morphology within the biological master clock, suprachiasmatic nucleus: From the perspective of circadian wave dynamics

Abstract

The biological master clock, suprachiasmatic nucleus (of rat and mouse), is composed of ~10,000 clock cells which are heterogeneous with respect to their circadian periods. Despite this inhomogeneity, an intact SCN maintains a very good degree of circadian phase (time) coherence which is vital for sustaining various circadian rhythmic activities, and it is supposedly achieved by not just one but a few different cell-to-cell coupling mechanisms, among which action potential (AP)-mediated connectivity is known to be essential. But, due to technical difficulties and limitations in experiments, so far very little information is available about the morphology of the connectivity at a cellular scale. Building upon this limited amount of information, here we exhaustively and systematically explore a large pool (~25,000) of various network morphologies to come up with some plausible network features of SCN networks. All candidates under consideration reflect an experimentally obtained ‘indegree distribution’ as well as a ‘physical range distribution of afferent clock cells.’ Then, importantly, with a set of multitude criteria based on the properties of SCN circadian phase waves in extrinsically perturbed as well as in their natural states, we select out appropriate model networks: Some important measures are, 1) level of phase dispersal and direction of wave propagation, 2) phase-resetting ability of the model networks subject to external circadian forcing, and 3) decay rate of perturbation induced “phase-singularities.” The successful, realistic networks have several common features: 1) “indegree” and “outdegree” should have a positive correlation; 2) the cells in the SCN ventrolateral region (core) have a much larger total degree than that of the dorsal medial region (shell); 3) The number of intra-core edges is about 7.5 times that of intra-shell edges; and 4) the distance probability density function for the afferent connections fits well to a beta function. We believe that these newly identified network features would be a useful guide for future explorations on the very much unknown AP-mediated clock cell connectome within the SCN.

Free running period affected by network structures of suprachiasmatic nucleus neurons exposed to constant light

“…Because the SCN neurons exhibit heterogeneity in light sensitivity, i.e., the VL neurons are much more sensitive to the light-information than the DM neurons, [36,37] and the links in VL neurons are denser than those in DM neurons. [34,35] Thus, there is positive correlation between the node degree and the sensitivity, we set l i = d i /D, i = 1, 2, . .…”

“…[31,32] The VL neurons are regarded as the hubs because the links of the VL neurons are much more than those of the DM neurons. [33][34][35] Additionally, the VL and the DM neurons have heterogenous characteristics in terms of the light sensitivity. [36][37][38] Early studies found that the VL neurons are directly sensitive to the light information originating from intrinsically photosensitive retinal ganglion cells through the retino-hypothalamic tract, and relay the information to the DM neurons.…”