Table 2.

Graph properties for the full network under each weighting scheme, as well as the subnetworks composed of those cortical nodes whose strengths are significantly different between patients and control subjects

Whole-brain network (streamline-weighted)Whole-brain network (FA-weighted)Selected subnetwork (streamline-weighted)Selected subnetwork (FA-weighted)
Cortical ROIs (nodes), N 68 68 10 16 
Mean (SD) edge density, % 
Control Subjects 75.0 (4.5) 75.0 (4.5) 98.3 (1.7) 79.9 (8.6) 
Patients 71.5 (5.1) 71.5 (5.1) 96.3 (3.1) 70.9 (8.0) 
Effect size (Cohen’s d−0.72 −0.72 −0.76 −1.09 
Mean (SD) global efficiency 
Control Subjects 0.314 (0.034) 0.423 (0.016) 0.384 (0.085) 0.421 (0.024) 
Patients 0.314 (0.053) 0.414 (0.017) 0.315 (0.066) 0.399 (0.023) 
Effect size (Cohen’s d0.01 −0.53 −0.94 −0.97 
Whole-brain network (streamline-weighted)Whole-brain network (FA-weighted)Selected subnetwork (streamline-weighted)Selected subnetwork (FA-weighted)
Cortical ROIs (nodes), N 68 68 10 16 
Mean (SD) edge density, % 
Control Subjects 75.0 (4.5) 75.0 (4.5) 98.3 (1.7) 79.9 (8.6) 
Patients 71.5 (5.1) 71.5 (5.1) 96.3 (3.1) 70.9 (8.0) 
Effect size (Cohen’s d−0.72 −0.72 −0.76 −1.09 
Mean (SD) global efficiency 
Control Subjects 0.314 (0.034) 0.423 (0.016) 0.384 (0.085) 0.421 (0.024) 
Patients 0.314 (0.053) 0.414 (0.017) 0.315 (0.066) 0.399 (0.023) 
Effect size (Cohen’s d0.01 −0.53 −0.94 −0.97 

FA, fractional anisotropy; ROI, region of interest; SD, standard deviation.

An absolute Cohen’s d value of 0.5 is conventionally considered to be a medium effect, and 0.8 a large effect.