cat_corticothalamic — Cat cortico-thalamic connectivity (Scannell, 1999)

Description

Directed and weighted networks of the extrinsic anatomical connections among the cortical areas and thalamic nuclei of the cat cerebral hemisphere, from the collation of Scannell et al., as distributed with the Brain Connectivity Toolbox (contributed by O. Sporns). Scannell et al. compiled the connections reported in the published tract-tracing literature into a database of the cortico-cortical, cortico-thalamic, thalamo-cortical and thalamo-thalamic connections of the cat. Nodes are brain regions (cortical areas or thalamic nuclei), and a directed edge $i\to j$ indicates a reported axonal projection from region $i$ to region $j$ (an entry $a_{ij}>0$ of the source matrix, following the Brain Connectivity Toolbox convention), weighted by its reported strength (1 to 3).

all: all 95 regions, cortical areas and thalamic nuclei (2126 connections).
cortex: only the 52 cortical areas (818 connections; the toolbox documentation states 820). This is the same as the subnetwork of all induced by the cortical areas.

Note that this differs from the 65-area cortico-cortical version of the cat connectome in the cat_cortex entry.

The networks have the following properties:

name: the name of the cortical area (e.g. "17", "AES", "PFCL"). The source data contain names only for the cortical areas; the thalamic nuclei in all are unnamed (empty string).
cortical (all only): whether the region is a cortical area (the first 52 regions), otherwise it is a thalamic nucleus.
weight: the strength of the connection as classified in the collation, from 1 (weak or sparse) to 3 (strong or dense).

Tags

Biological Connectome Weighted Metadata

Citation

J. W. Scannell, G. A. P. C. Burns, C. C. Hilgetag, M. A. O'Neil, M. P. Young, "The connectional organization of the cortico-thalamic system of the cat." Cerebral Cortex 9(3), 277-299 (1999) 10.1093/cercor/9.3.277 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

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
all	95	2,126	22.38	23.67	30.79	2.39	-0.06	0.48	4	1.00	Directed	Unipartite	name cortical	weight	3 KiB	7 KiB	7 KiB	6 KiB
cortex	52	818	15.73	12.98	21.81	2.34	0.02	0.61	3	1.00	Directed	Unipartite	name	weight	2 KiB	4 KiB	3 KiB	3 KiB