brain_coactivation — Human brain functional coactivation and resting-state networks (2013)

Description

Weighted networks of 638 regions of the human brain (the grey matter excluding the cerebellum, parcellated into regions of similar size that respect anatomical landmarks), from Crossley et al., as distributed with the Brain Connectivity Toolbox. Nodes are brain regions, and an undirected edge connects two regions with strong functional coactivation or connectivity, as defined below.

• coactivation: the functional coactivation network, from a meta-analysis of the BrainMap database comprising 6,884 task-related contrasts from 1,641 functional MRI and PET studies of healthy adults published between 1985 and 2010. Each reported activation was modelled as a 1 cm³ sphere around its coordinates, and a region was considered activated by a contrast if at least 20% of a sphere overlapped it. Two regions are connected if their coactivation, measured by the Jaccard index (the number of contrasts activating both regions divided by the number of contrasts activating either), is significantly larger than expected by chance (P < 0.01, false-discovery-rate corrected).
• rsfmri: the resting-state functional connectivity network of the same regions, from 3T functional MRI scans of 27 healthy volunteers (5 min, eyes closed). The Pearson correlations between the band-pass filtered (0.01-0.1 Hz) regional time series were Fisher-transformed and averaged over the volunteers, and two regions are connected if their correlation is among the strongest, keeping as many edges as in the coactivation network. Two regions have no connections in this network.

The networks have the following properties:

• Nodes: coord, the (x, y, z) coordinates of the region in standard stereotactic space, in millimetres (the regions have no names in the source data).
• Edges: weight, the Jaccard index of coactivation (coactivation), or the group-average Fisher-transformed correlation (rsfmri).

Tags

Biological Connectome Weighted Metadata

Citation

• N. A. Crossley, A. Mechelli, P. E. Vértes, T. T. Winton-Brown, A. X. Patel, C. E. Ginestet, P. McGuire, E. T. Bullmore, "Cognitive relevance of the community structure of the human brain functional coactivation network." Proceedings of the National Academy of Sciences 110(28), 11583-11588 (2013) 10.1073/pnas.1220826110 Sci-Hub
• M. Rubinov, O. Sporns, "Complex network measures of brain connectivity: Uses and interpretations." NeuroImage 52(3), 1059-1069 (2010) 10.1016/j.neuroimage.2009.10.003 Sci-Hub

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https://sites.google.com/site/bctnet/datasets-and-demos

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

Show all columns

Name	Nodes	Edges	$\left<k\right>$	$\sigma_k$	$\lambda_h$	$\tau$	$r$	$c$	$\oslash$	$S$	Kind	Mode	NPs	EPs	gt	GraphML	GML	csv
coactivation	638	18,625	58.39	33.71	88.70	4.91	0.38	0.41	4	1.00	Undirected	Unipartite	coord	weight	92 KiB	160 KiB	152 KiB	169 KiB
rsfmri	638	18,625	58.39	43.15	104.73	12.80	0.39	0.56	8	0.99	Undirected	Unipartite	coord	weight	156 KiB	218 KiB	214 KiB	221 KiB