scn_functional_networks — Mouse suprachiasmatic nucleus functional networks (2016)

Description

Functional networks between the neurons of the suprachiasmatic nucleus (SCN) of mice, the master circadian clock located in the hypothalamus, inferred by Abel et al. from single-cell bioluminescence recordings. Slices of the SCN of five mice expressing a bioluminescent reporter of the clock protein PERIOD2 (PER2::LUC) were imaged at a rate of one sample per hour, and the cells were tracked over time. The neurons were desynchronized by blocking their communication with the neurotoxin tetrodotoxin (TTX), which was then washed out, and the network was inferred from the bioluminescence traces of the individual cells while they resynchronized after the washout.

Two cells are connected if the maximal information coefficient (MIC) between their bioluminescence traces after the washout exceeds a threshold, which was chosen separately for each SCN (0.949, 0.935, 0.9895, 0.968 and 0.969 for SCNs 1 to 5, respectively), as given by the authors. Cells without any connection above the threshold are kept as isolated nodes.

scn1, ..., scn5: the functional networks of the five SCN slices.

The networks have the following properties:

Nodes: pos, the (x, y) location of the cell in the image; bioluminescence, the time series of the bioluminescence of the cell during the TTX washout, with one sample per hour.
Edges: mic, the maximal information coefficient between the two cells.

Tags

Biological Connectome Weighted Metadata

Citation

J. H. Abel, K. Meeker, D. Granados-Fuentes, P. C. St. John, T. J. Wang, B. B. Bales, F. J. Doyle, E. D. Herzog, L. R. Petzold, "Functional network inference of the suprachiasmatic nucleus." Proceedings of the National Academy of Sciences 113(16), 4512-4517 (2016) 10.1073/pnas.1521178113 Sci-Hub

Upstream URL OK

https://github.com/JohnAbel/scn-resynchronization-data-2016

Networks

Tip: click on a column header to sort the list, or hover over it for a description.

Column legend

$\left<k\right>$: Mean degree
$\sigma_k$: Standard deviation of the degrees
$\lambda_h$: Largest eigenvalue of the Hashimoto (non-backtracking) matrix
$\tau$: Random walk mixing time
$r$: Degree assortativity
$c$: Global clustering coefficient
$\oslash$: (Pseudo-) diameter
$S$: Relative size of the largest component
NPs: Node properties
EPs: Edge properties

Name	Nodes	Edges	$\left<k\right>$	$\sigma_k$	$\lambda_h$	$\tau$	$r$	$c$	$\oslash$	$S$	Kind	Mode	NPs	EPs	gt	GraphML	GML	csv
scn1	541	1,686	6.23	7.46	17.87	54.09	0.37	0.36	14	0.70	Undirected	Unipartite	pos bioluminescence	mic	766 KiB	795 KiB	794 KiB	484 KiB
scn2	404	1,033	5.11	7.26	17.99	26.27	0.28	0.37	10	0.56	Undirected	Unipartite	pos bioluminescence	mic	716 KiB	725 KiB	723 KiB	428 KiB
scn3	430	724	3.37	5.97	15.23	22.36	0.33	0.37	14	0.42	Undirected	Unipartite	pos bioluminescence	mic	772 KiB	790 KiB	789 KiB	493 KiB
scn4	350	747	4.27	7.47	17.56	19.50	0.14	0.35	9	0.44	Undirected	Unipartite	pos bioluminescence	mic	669 KiB	668 KiB	665 KiB	322 KiB
scn5	358	805	4.50	7.13	17.65	20.59	0.28	0.39	8	0.49	Undirected	Unipartite	pos bioluminescence	mic	548 KiB	558 KiB	557 KiB	362 KiB