Supplemental Table 1. Abbreviations of cortical regions of interest

Cortical regions Abbr. Cortical regions Abbr.

Precental gyrus PreCG Cuneus CUN Superior frontal gyrus, dorsola- SFGdor Lingual gyrus LING teral Superior frontal gyrus, orbital part ORBsup Superior occipital gyrus SOG

Middle frontal gyrus MFG Middle occipital gyrus MOG

Middle frontal gyrus, orbital part ORBmid Inferior occipital gyrus IOG Inferior frontal gyrus, opercular IFGoperc Fusiform gyrus FFG part Inferior frontal gyrus, triangular IFGtriang Postcentral gyrus PoCG part Inferior frontal gyrus, orbital part ORBinf Superior parietal gyrus SPG Inferior parietal, but supramar- Rolandic operculum ROL IPL ginal and angular gyri Supplementary motor area SMA Supramarginal gyrus SMG

Olfactory cortex OLF Angular gyrus ANG

Superior frontal gyrus, medial SFGmed Precuneus PCUN Superior frontal gyrus, medial ORBsupmed Paracentral lobule PCL orbital Gyrus rectus REC Heschl gyrus HES

Insula INS Superior temporal gyrus STG Anterior cingulate and paracin- Temporal pole: superior temporal ACG TPOsup gulate gyri gyrus Median cingulate and paracin- DCG Middle temporal gyrus MTG gulate gyri Temporal pole: middle temporal Posterior cingulate gyrus PCG TPOmid gyrus Parahippocampal gyrus PHG Inferior temporal gyrus ITG Calcarine fissure and surround- CAL ing cortex

The brain regions were defined by Tzourio-Mazoyer et al. (2002) Tzourio-Mazoyer N, Landeau B, Papathanassiou D, Crivello F, Etard O, Delcroix N, Mazoyer B, Joliot M (2002) Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage 15:273-289.

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Supplemental Table 2. Regions with high nodal efficiency in weighted WM networks of normal controls

Regions Category Normalized Enodal

Left posterior cingulate gyrus Paralimbic 2.37 (0.54)

Right posterior cingulate gyrus Paralimbic 2.35 (0.52)

Left precuneus Association 2.34 (0.63)

Right precuneus Association 2.17 (0.58)

Left calcarine fissure and surrounding cortex Primary 1.84 (0.55)

Left median cingulate and paracingulate gyri Paralimbic 1.69 (0.56)

Left anterior cingulate and paracingulate gyri Paralimbic 1.66 (0.58)

Right anterior cingulate and paracingulate gyri Paralimbic 1.66 (0.59)

Left cuneus Association 1.65 (0.42)

Right median cingulate and paracingulate gyri Paralimbic 1.61 (0.58)

Right calcarine fissure and surrounding cortex Primary 1.52 (0.44)

Right superior frontal gyrus, dorsolateral Association 1.50 (0.61)

Left middle occipital gyrus Association 1.48 (0.37)

The values of normalized nodal efficiency were shown with mean (standard deviation). The hub re-

gions ( Enodal (i) > mean + SD) in the weighted WM network of the control group were listed in a

descending order of the normalized nodal efficiency (divided by mean, i.e., Enodal (i) / Enodal ). The cortical regions were classified as primary, association, and paralimbic (Mesulam, 1998).

Mesulam MM (1998) From sensation to cognition. Brain 121 ( Pt 6):1013-1052.

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Supplemental Table 3. Regions with high nodal efficiency in weighted WM networks of AD patients

Regions Category Normalized Enodal

Left posterior cingulate gyrus Paralimbic 2.67 (0.65)

Left precuneus Association 2.64 (0.84)

Right posterior cingulate gyrus Paralimbic 2.63 (0.63)

Right precuneus Association 2.50 (0.76)

Left calcarine fissure and surrounding cortex Primary 1.95 (0.70)

Left cuneus Association 1.82 (0.57)

Left middle occipital gyrus Association 1.63 (0.61)

Left median cingulate and paracingulate gyri Paralimbic 1.62 (0.79)

Right median cingulate and paracingulate gyri Paralimbic 1.60 (0.77)

Right calcarine fissure and surrounding cortex Primary 1.59 (0.46)

Left anterior cingulate and paracingulate gyri Paralimbic 1.50 (0.75)

Left inferior temporal gyrus Association 1.49 (0.38)

The values of normalized nodal efficiency were shown with mean (standard deviation). The hub re-

gions ( Enodal (i) > mean + SD) in the weighted WM network of the AD group were listed in a des-

cending order of the normalized nodal efficiency ( Enodal (i) / Enodal ). The cortical regions were clas- sified as primary, association, and paralimbic (Mesulam, 1998).

Mesulam MM (1998) From sensation to cognition. Brain 121 ( Pt 6):1013-1052.

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Supplemental Table 4. Comparisons of topological properties in the FA-weighted net- work of AD patients and normal controls

T statistic Network Metrics Patients Controls P value (AD vs NC)

Cp 0.518 (0.025) 0.531 (0.030) -1.582 0.120

Lp 2.320 (0.243) 2.207 (0.143) 2.064 0.044* γ 3.512 (0.460) 3.395 (0.375) 0.938 0.353 λ 1.160 (0.034) 1.148 (0.020) 1.567 0.123 σ 3.024 (0.347) 2.957 (0.310) 0.642 0.524

Eloc 0.698 (0.039) 0.724 (0.038) -2.368 0.022*

Eglob 0.435 (0.037) 0.455 (0.029) -2.206 0.032*

The values of network metrics were shown with mean (standard deviation). Lp, Eloc, and Eglob were found significantly altered in FA weighted networks of AD patients. Note: Cp = clustering coefficient,

Lp = characteristic shortest path length, γ = normalized clustering coefficient, λ = normalized cha- racteristic shortest path length, σ = small-worldness, Eloc = local efficiency, Eglob = global efficiency, *P

< 0.05

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Supplemental Table 5. Comparisons of topological properties in the FN-weighted net- work of AD patients and normal controls

T statistic Network Metrics Patients Controls P value (AD vs NC)

Cp 0.451 (0.023) 0.460 (0.028) -1.013 0.316

Lp 2.439 (0.493) 2.166 (0.270) 2.551 0.014* γ 4.168 (0.558) 4.026 (0.411) 1.025 0.310 λ 1.417 (0.080) 1.373 (0.064) 2.368 0.022* σ 2.940 (0.341) 2.939 (0.331) -0.145 0.885

Eloc 0.908 (0.094) 0.943 (0.095) -1.399 0.168

Eglob 0.423 (0.068) 0.469 (0.058) -2.661 0.010*

The values of network metrics were shown with mean (standard deviation). Lp, λ, and Eglob were found significantly altered in FN weighted networks of AD patients. Note: Cp = clustering coefficient,

Lp = characteristic shortest path length, γ = normalized clustering coefficient, λ = normalized cha- racteristic shortest path length, σ = small-worldness, Eloc = local efficiency, Eglob = global efficiency, *P

< 0.05

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Supplemental Text 1. Short discussion of FA- and FN-weighted networks

In the FA-weighted WM networks, we found that AD patients showed longer shortest path length, decreased local efficiency and global efficiency (Supplemental Table 4). In the FN-weighted WM networks, we found that AD patients showed longer shortest path length, increased normalized shortest path length, and decreased global efficiency (Supplemental Table 5). These results indicate that the AD networks had abnormal topological organization (longer shortest path length and re- duced global efficiency) regardless of the selection of FA or FN as the weights. These results are also consistent with those obtained by FA-by-FN weighted network analysis (see Main text). Of note, however, we also found that AD patients had decreased local efficiency in the FA-weighted networks rather than the FN- and FA-by-FN-weighted networks. This suggests that the FA- and FN-weighted networks are sensitive to different network metrics for AD patients. Considering that the connectivity weights of the brain networks were defined using the characteristics of WM tracts (i.e., FA and FN), we speculate these results could be attributable to the reduction of fiber number and the disruption of

WM integrity between different brain regions in the Alzheimer’s brain.

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