The data-based inference method reveals the network structure of the SCN

The suprachiasmatic nucleus (SCN) is the central circadian pacemaker in mammals. Even though the SCN is composed of thousands of heterogeneous self-oscillating cells, the SCN can synchronize its component oscillators through the SCN neuronal network. To understand the SCN network structure, previous methods used the time series data to infer the network structure. However, because the SCN is synchronized, previous methods falsely inferred the network as if all the SCN cells were coupled with each other. To circumvent this, we develop a novel data-based method, which can successfully infer the SCN network from the time series data. In particular, our method accurately infers the SCN network with single-cell resolution bioluminescence data from 2,000 synchronized mice SCN cells. Furthermore, our method can infer the directionality of the coupling between SCN cells.