Centrality and Community Detection in Macaque Rhesus Brain Networks with Gephi 0.9.2

Tools : Gephi you can download and install in https://gephi.org/
Gephi is the leading visualization and exploration software for all kinds of graphs and networks. Gephi is open-source and free.

Use data set from :
The Network Data Repository with Interactive Graph Analytics and Visualization

http://networkrepository.com/bn-macaque-rhesus-brain-1.php

Brain network
Description : Edges represent fiber tracts that connect one vertex to another.

Edge weights Unweighted
Nodes: 242
Edges: 4.1K
Density: 0.140256
Maximum degree:164
Minimum degree: 2
Average degree: 33

.edges convert to .csv

Edge link dataset is in .edges format, However we’ll convert to .csv format before import into Gephi.

Expect of network graph represented base on

1. Centrality — Betweenness centrality
For detecting the amount of influence a node has over the flow of information in a graph. It is often used to find nodes that serve as a bridge from one part of a graph to another.

2. Community Detection — Modularity
A subset of vertices in a graph that have more connections to each other than to the rest of the network.

Betweenness can have several meanings.
In this case: Cells of brain with high betweenness may be the important link that impact others.

Modularity in the brain:
Communities are groups of brain areas that are more highly connected to each other than the rest of the brain

Let’s start on Gephi 9.0.2

1. Data Laboratory → Import Spreadsheet

2. Overview → Statistics
(press run on Modularity, Network Diameter or others)

e.g. Modularity found 5 commnunities

3. Appearance → Node

Color of nodes by partition modularity class.

Size of nodes by ranking betweeness centrality.

4. Layout → Force Atlas

Shape the layout adjust by sizes

5. Filter → Queries

6. Graph → Lebel design

Lebel design

For customizing the visulization you can edit a graph with your style.
(learn more on Gephi)

Steps below are a sample that focus on the high betweenness centraliry (large sizes) and communities of groups of brain areas (colors).

Gephi help to find the High Betweenness e.g. node id are 31, 184, 73 etc. and 5 Modularity classes.

Future work :
You are able to use this tool for help identify the other problems e.g. the network brain of the other animals or the other industries. and there’re various features for analysing.

Useful References

https://gephi.org/features/
http://networkrepository.com/bn-macaque-rhesus-brain-1.php https://pixabay.com/photos/animals-monkeys-macaque-nature-1846731/https://www.humanbrainmapping.org/files/2017/ED%20Courses/Course%20Materials/Modularity_Muldoon_Sarah.pdf
https://neo4j.com/docs/graph-algorithms/current/algorithms/betweenness-centrality/
Eakasit Pacharawongsakda, Ph.D., BD517 Network Analysis Course, Big Data Engineering Program, CITE, DPU, 2018