rat_brain_bams — Rat brain BAMS connectome (2011-2013)
- Description
Directed networks of anatomical connections between regions of the rat brain, from three releases (2011, March 2012 and January 2013) of the connection matrix of the Brain Architecture Management System (BAMS) Rat Connectome Project of Bota and Swanson. BAMS is a curated database that collates connection reports from the primary experimental (tract-tracing) literature, using the regions of the Swanson rat brain atlas. Nodes are brain regions (about 500, spanning the cerebral cortex, cerebral nuclei, thalamus, hypothalamus, midbrain and hindbrain), and a directed edge points from the region of origin of a projection to its target.
2011: 503 regions, 27,667 edges.2012: 503 regions, 30,088 edges.2013: 496 regions, 33,020 edges.
The networks have the following properties:
- Nodes:
name, the abbreviation of the region in the Swanson atlas. - Edges:
strength, an ordinal connection-strength code from 1 to 9 (larger values for stronger connections). BAMS uses qualitative strength categories ("exists", "very weak", "weak", "moderate/weak", "moderate", "moderate/strong", "strong", "very strong"); the exact mapping of these to the codes in these files is not documented (the code 1 accounts for about 80% of the edges).
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
- Citation
-
- M. Bota, L. W. Swanson, "Online workbenches for neural network connections." Journal of Comparative Neurology 500(5), 807-814 (2007) 10.1002/cne.21209 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 2011 503 27,667 55.00 155.72 166.31 0.86 -0.59 0.35 3 1.00 Directed Unipartite name strength 12 KiB 82 KiB 80 KiB 73 KiB 2012 503 30,088 59.82 164.23 174.39 0.83 -0.60 0.36 3 1.00 Directed Unipartite name strength 12 KiB 88 KiB 86 KiB 79 KiB 2013 496 33,020 66.57 169.00 178.64 1.12 -0.57 0.40 3 0.99 Directed Unipartite name strength 14 KiB 97 KiB 94 KiB 87 KiB