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macaque_neural — Macaque cortical connectivity (Young 1993; CoCoMac 2007)

Description

Two networks of anatomical connections among areas of the cerebral cortex of the macaque monkey, compiled from published axonal tract-tracing studies, and distributed with the Brain Connectivity Toolbox (BCT). In both, nodes are cortical areas and edges are axonal pathways (projections) between them.

  • young71: the 71-area network of M. P. Young (Proc. R. Soc. B 252, 13-18, 1993), who collated the tract-tracing literature into a connection matrix covering visual, somatosensory, auditory, motor, prefrontal and limbic (cingulate, insular, parahippocampal) areas. The BCT matrix contains 746 connections, with 308 reciprocally connected pairs of areas. Area names follow the source file, with numbered (Brodmann-type) areas prefixed by "A" (e.g. "A46" is area 46, "A7a" is area 7a), together with visual areas such as "V1", "MT" or "PITd" and auditory and temporal areas such as "KA", "PAAR" or "TS1".
  • cocomac47: 47 areas of the visual, somatosensory and motor cortex, defined according to the parcellation of Felleman and Van Essen (as in "V1", "MT", "FEF" or "46"). This matrix was contributed by R. Kötter and used by C. J. Honey, R. Kötter, M. Breakspear and O. Sporns (PNAS 104, 10240-10245, 2007). There, the results of published tracing studies were manually collated in the CoCoMac database, mapped onto the Felleman–Van Essen parcellation, and redundant and inconsistent reports were resolved to obtain a binary connection matrix with 505 connections; 192 pairs of areas are reciprocally connected.

The two networks are independent compilations of the tracing literature using different parcellations, so the 47-area network is not a subnetwork of the 71-area one (several areas, such as "MDP", "MIP" or "36", appear only in the former, while the auditory, prefrontal and limbic areas appear only in the latter); nodes with the same name in both refer to the same anatomical area only approximately.

Both networks are directed and unweighted: an edge $i\to j$ indicates a projection from area $i$ to area $j$ (an entry $a_{ij}=1$ of the binary source matrix, following the BCT convention); absent entries mean that no connection was reported. There are no self-loops.

The networks have the following properties:

  • (Node) name: the name of the cortical area (with the padding spaces of the source files removed).
Tags
Biological Connectome Unweighted
Added
2020-08-11
Citation
  • M. P. Young, "The organization of neural systems in the primate cerebral cortex", Proc. R. Soc. Lond. B 252, 13-18 (1993) 10.1098/rspb.1993.0040 Sci-Hub
  • C. J. Honey, R. Kötter, M. Breakspear, O. Sporns, "Network structure of cerebral cortex shapes functional connectivity on multiple time scales", Proc. Natl. Acad. Sci. USA 104, 10240-10245 (2007) 10.1073/pnas.0701519104 Sci-Hub
  • R. Kötter, "Online retrieval, processing, and visualization of primate connectivity data from the CoCoMac database", Neuroinformatics 2, 127-144 (2004) 10.1385/NI:2:2:127 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
cocomac47 47 505 10.74 11.05 15.69 3.35 0.01 0.56 4 1.00 Directed Unipartite name 3 KiB 4 KiB 3 KiB 3 KiB
young71 71 746 10.51 11.69 15.17 5.50 0.02 0.44 5 1.00 Directed Unipartite name 3 KiB 5 KiB 5 KiB 4 KiB
Ridiculograms*
* These are automatically generated force-directed visualizations, and can be quite meaningless for networks both big and small. They should not be taken seriously as sources of scientific insight. See here for a discussion.