Abstract
Biological neural networks operate at several levels of granularity, from the individual neuron to local neural circuits to networks of thousands of cells. The daily oscillation of the brain’s master clock in the suprachiasmatic nucleus (SCN) rests on a yet to be identified network of connectivity among its ∼20,000 neurons. The SCN provides an accessible model to explore neural organization at several levels of organization. To relate cellular to local and global network behaviors, we explore network topology by examining SCN slices in three orientations using immunochemistry, light and confocal microscopy, real-time imaging, and mathematical modeling. Importantly, the results reveal small local groupings of neurons that form intermediate structures, here termed “phaseoids” which can be identified through stable local phase differences of varying magnitude among neighboring cells. These local differences in phase are distinct from the global phase relationship – that between individual cells and the mean oscillation of the overall SCN. The magnitude of the phaseoids’ local phase differences are associated with a global phase gradient observed in the SCN’s rostral-caudal extent. Modeling results show that a gradient in connectivity strength can explain the observed gradient of phaseoid strength, an extremely parsimonious explanation for the heterogeneous oscillatory structure of the SCN.
Significance statement
Oscillation is a fundamental property of information sensing and encoding in the brain. Using real time imaging and modeling, we explore encoding of time by examining circadian oscillation in single neurons, small groups of neurons, and the entire nucleus, in the brain’s master: the suprachiasmatic nucleus. New insights into the network organization underlying circadian rhythmicity include the discovery of intermediate structures, termed ‘phaseoids’, characterized by groups of neurons which are stably out of phase with their neighbors. Modeling indicates that the pattern of phaseoids across the tissue encompasses a gradient in connectivity strength from the rostral to caudal aspects of the nucleus. Anisotropy in network organization emerges from comparisons of phaseoids and connectivity gradients in sagittal, horizontal and coronal slices.
Footnotes
The authors declare no competing financial interests.
The research was funded in part by grants from NSF | BIO | Division of Integrative Organismal Systems (IOS) 1256105; 1749500 (to RS and SP) and by JSPS KAKENHI (Grant 19K06774 to TY). TY thanks Dr. H. Gainer (National Institutes of Health) for the generous donation of AVP antibody for immunohistochemistry and Dr. Y. Shigeyoshi (Kindai University) for helpful discussions.
This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license, which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed.
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