macaque_markov — Macaque interareal cortical networks of Markov et al. (2013-2014)

Description

Directed networks of the macaque (Macaca mulatta and M. fascicularis) cerebral cortex, from the retrograde tract-tracing experiments of Markov, Kennedy and collaborators. In each experiment a retrograde tracer was injected into one cortical area (the target), and the labelled neurons projecting to it were counted in each of the 91 areas (the sources) of the authors' M132 atlas parcellation. Edges point from the source area to the injected target area, so only the injected areas have incoming edges.

flne: the connectivity of 29 injected areas from all 91 areas (Markov et al., Cerebral Cortex 2014). There is one edge for each injection and each source area with labelled neurons, so that areas injected in several animals are connected by parallel edges (1,989 edges, 1,615 distinct connections). Edge properties: flne, the extrinsic fraction of labelled neurons (the number of neurons labelled in the source area divided by the total number labelled outside the injected area); neurons, the number of labelled neurons; case, the injection case number; monkey, the identifier of the animal and hemisphere; status, whether the projection was previously reported in the literature ("Known") or newly found ("NFP"); references, the reference numbers (in the original publication) of previous reports of the projection, or "NA".
sln: the projections to 11 injected areas of the visual cortex (Markov et al., J. Comp. Neurol. 2014), annotated with the laminar origin of the projecting neurons, used to derive the hierarchy of visual areas. Edge properties: sln, the percentage of labelled neurons in the supragranular layers (SLN; high values indicate feedforward and low values feedback projections); distance, the white-matter distance between the two areas, in millimetres.
distances: the estimated white-matter distances, in millimetres (edge property distance), from every area to each of the 29 injected areas (Markov et al., PNAS 2013). This network contains all such pairs, whether or not the areas are connected, and is therefore a distance matrix rather than a connectivity network; in this file some areas are grouped differently (e.g. "INSULA", "TEMPORAL_POLE").

All networks have the vertex property name, the name of the cortical area. The networks were obtained from the authors' Core-Nets data site via OpenConnectome. The data were obtained from the graph collection of the Open Connectome Project (now NeuroData), whose servers are offline, via the Internet Archive.

Tags

Biological Connectome Weighted Multigraph Metadata

Citation

N. T. Markov et al., "A Weighted and Directed Interareal Connectivity Matrix for Macaque Cerebral Cortex." Cerebral Cortex 24(1), 17-36 (2014) 10.1093/cercor/bhs270 Sci-Hub
N. T. Markov et al., "Anatomy of hierarchy: Feedforward and feedback pathways in macaque visual cortex." Journal of Comparative Neurology 522(1), 225-259 (2014) 10.1002/cne.23458 Sci-Hub
N. T. Markov et al., "The role of long-range connections on the specificity of the macaque interareal cortical network." Proceedings of the National Academy of Sciences 110(13), 5187-5192 (2013) 10.1073/pnas.1218972110 Sci-Hub

Upstream URL OK

https://web.archive.org/web/20160420202242/http://openconnecto.me/graph-services/download/

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
flne	91	1,989	21.86	39.13	39.66	1.39	-0.34	0.56	3	1.00	Directed	Unipartite	name	flne neurons case monkey status references	21 KiB	28 KiB	27 KiB	21 KiB
sln	91	628	6.90	20.42	23.53	0.95	-0.71	0.37	3	1.00	Directed	Unipartite	name	sln distance	5 KiB	8 KiB	8 KiB	6 KiB
distances	93	2,667	28.68	42.12	58.11	0.03	-0.53	0.75	2	1.00	Directed	Unipartite	name	distance	6 KiB	17 KiB	16 KiB	12 KiB