Skip to main content

Table 1 Studied network parameters and their definitions

From: The effect of lesion filling on brain network analysis in multiple sclerosis using structural magnetic resonance imaging

Measure

Definition

Nodal level

Global level

Degree

Number of connections to a node

x

x*

Strength

Sum of the weight of all connections to a node

x

x*

Path length

Lowest number of connections between two nodes

x

x*

Clustering coefficient

The fraction of a node’s neighbours that are also neighbour between each other

x

x*

Global efficiency

Average inverse of shortest path length

x

x*

Local efficiency

Global efficiency of a node regarding its neighbourhood

x

x*

Within module degree z-score

Within module degree of centrality

x

 

Participation

The diversity of intermodular interconnections of individual nodes

x

 

Transitivity

The probability of interconnectivity of adjacent nodes

 

x

Modularity

Degree to which the graph can be subdivided into multiple small-world networks

 

x

Assortativity coefficient

Correlation coefficient between degrees/strengths of all nodes on two opposite ends of a connection

 

x

Small-worldness

The ratio of clustering coefficient on global level and the clustering coefficient of a random graph divided by the ratio of the average path length on global level and the average path length of a random graph

 

x

  1. *Network parameters at global level were calculated by averaging the outcome of nodal measures over all ROI’s