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. 2017 Mar 28;7:45347. doi: 10.1038/srep45347

Figure 2. Edges used as features in the classification procedure.

Figure 2

Panel (A) shows the distribution of the 89 edges selected as relevant features in all randomized logistic regression (RLR) feature selection repeats. Twenty-one edges were selected in ≥80% of the leave-one-out cross-validation (LOOCV) iterations (red segment). Panel (B) depicts the location of the 21 edges most consistently selected as relevant features to discriminate Parkinson’s disease patients without mild cognitive impairment (PD-nonMCI) from patients with mild cognitive impairment (PD-MCI). Brain nodes are scaled according to the number of edges connected to them. Panel (C) shows the mean strength values and standard deviation of the 21 most consistent features according to group. Significant pairwise intergroup differences in edge strength (increases or decreases; p < 0.05 with false-discovery rate control) are marked with an asterisk. Labels of pairs of nodes connected by each edge are shown (see Supplementary Table 3). r: connectivity strength (Pearson’s correlation coefficient). HC: healthy controls. Amyg: Amygdala; BG: basal ganglia; CG: Cingulate gyrus; IFG: Inferior frontal gyrus; IPL: Inferior parietal lobule; ITG: Inferior temporal gyrus; LOcC: lateral occipital cortex; MFG: Middle frontal gyrus; MVOcC: medioventral occipital cortex; PCL: Paracentral lobule; Pcun: precuneus; PhG: Parahippocampal gyrus; PoG: Postcentral gyrus; PrG: Precentral gyrus; SFG: Superior frontal gyrus; SPL: Superior parietal lobule; STG: Superior temporal gyrus; Tha: Thalamus. Brain plots were created with Surf Ice (https://www.nitrc.org/projects/surfice/).