TABLE 2.

Explanation of concepts and terminology based on Tewarie et al. (2015) and Van Dellen et al. (2015).

Measure	Explanation	Formula
Nodes (N)	Number of nodes
Links (M)	Number of links/maximum leaf number
Degree (k)	Number of links for a given node. Nodes with a high degree may be considered hubs. We used the maximum degree to characterize the strength of the most important node of the network.	$k_i=\sum _{j\in N}{a}_{ij}$
Leaf fraction (Lf)	Fraction of leaf nodes (L) in the MST where a leaf node is defined as a node with only one connection. It describes to what extent the network has a central organization. A high leaf fraction indicates, that communication is largely dependent on hub nodes.	Lf=L/M
Diameter	Longest distance between any two nodes in an MST, normalized by the total number of connections. In a network with a low diameter, information is efficiently processed between remote brain regions. The diameter is also related to the leaf number: the value of the diameter decreases when the leaf number increases.	D=d/M
Eccentricity	Longest shortest path from a reference node to any other node in the MST. Eccentricity is low if the node is located in the center of the tree. Eccentricity of the network describes how efficient information is communicated from the least central node.
Betweenness centrality (BC)	Fraction of all shortest paths that pass through a particular node. BC ranges between 0 (leaf node) and 1 (central node in a star-like network). Nodes with a high BC are considered hub nodes based on their importance for global communication in the network. The BC of the tree was characterized by the maximum BC value, which describes the importance of the most central node and it is a measure of central network organization.	$B{C}_i=\frac{1}{(n-1)(n-2)}\sum _{\begin{array}{c}\hfill h,j\in N\hfill \\ \hfill h\ne ȷ,h\ne i,\ne i\hfill \end{array}}\frac{{\mathrm{\rho }}_{hj}^{(i)}}{{\mathrm{\rho }}_{hj}}$ ρih is the number of shortest paths between h and j, and ρih(i) is the number of shortest paths between h and j that pass through i
Degree divergence (κ)	Measure of the broadness of the degree distribution. Related to resilience against attacks, epidemic spreading and the synchronizability of complex networks	$\mathrm{\kappa }=\frac{⟨k^2⟩}{⟨k⟩}$
Tree hierarchy (TH)	Quantifies the trade-off between large scale integration in the MST and the overload of central nodes It characterizes the hypothesized optimal topology of brain network organization, where information is transferred between brain regions in the fewest possible steps, while preventing information overload of central brain regions.	$T_H=\frac{L}{2MB{C}_{max}}$