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. Author manuscript; available in PMC: 2019 Aug 1.
Published in final edited form as: Neuroimage. 2018 Apr 12;176:83–91. doi: 10.1016/j.neuroimage.2018.04.010

Table 1:

The minimum number of nodes (and fraction with respect the size of the network) that are needed to control the system spending a minimum energy not greater than ϵmin = 1010. We here show results for the APOE-4 data and the corresponding Barabasi-Albert network (BA), Small-World network (SW) and Erdős–Rényi network (ER) (of same size, connectivity and edge weight distribution) following the procedure described in the main text. For a given sequence, “High” is the rank from the largest to the smallest, while “Low” is the rank from the smallest to the largest.

Data BA SW ER
Centrality measure Low High Low High Low High Low High
Degree centrality 51/0.46 49/0.45 44.64/0.41 42/0.38 45/0.41 43.5/0.40 44.64/0.41 42/0.38
Betweenness centrality 52/0.47 46/0.42 45/0.41 42.52/0.38 46/0.42 42.5/0.39 45/0.41 42.52/0.39
Eigenvector centrality 50/0.45 51/0.46 45.76/0.42 42.16/0.38 46/0.42 44/0.4 45.76/0.42 42.16/0.38
Page-rank centrality 51/0.46 47/0.42 44.84/0.41 42.36/0.39 47.5/0.43 43/0.39 44.84/0.41 42.36/0.39
Random sequence 46/0.41 47/0.42 44.08/0.40 43.48/0.40 45.5/0.41 43.81/0.40 44.08/0.40 43.48/0.40