MNI (x,y,z) T value. Dorsal Attention Network (DAN) Pre vs. NC

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1 Supplementary Table 1. Increased/decreased functional connectivity of resting state networks in patients and controls. Anatomical Locations Hemisphere BA Cluster voxels MNI (x,y,z) T value Default Mode Network (DMN) Pre vs. NC Anterior cingulate cortex L 10,11,24,25, ,39, R 10,24, ,36, Superior frontal gyrus L 8,9,10, ,48, Posterior cingulate cortex L/R 23,26,29, ,-42,33/3,-39, /-4.04 Inferior frontal gyrus, R 44,45, , 36, triangular 1m vs. NC Medial Frontal gyrus L 30-15,51, m vs. NC Posterior cingulated gyrus L 23,26,29, ,-42, Inferior Frontal gyrus, R 45,46,47, ,27, triangular 1m vs. Pre Medial frontal gyrus L/R 8,9,10,11, ,57,9/12,60, /+3.14 Superior Frontal R 8,9,10,11, ,54, Gyrus,medial Posterior cingulate cortex L/R 23,26,29, ,-48,33/3,-42, / m vs. Pre Superior frontal gyrus R 9,10,11, ,30, Posterior cingulate L/R 23,26,29, ,-42,24/6,-48, / m vs. 1m Medial superior frontal L 9,10, ,39, gyrus Dorsal Attention Network (DAN) Pre vs. NC 1

2 Precentral gyrus L 4,6, ,-12, Inferior frontal gyrus, L 44,45, ,39, triangular Middle frontal gyrus R 44, ,0, Inferior parietal gyrus L ,39, R ,-42, Middle temporal gyrus L 20,21, ,-60, Postcentral gyrus R 43, ,-33, Inferior frontal gyrus, R 44, ,12, opercular Inferior temporal gyrus R 20,21, ,-51, Inferior temporal gyrus L 20,21, ,-63, Middle occipital gyrus L 7, ,-75, R 7, ,-75, m vs. NC Middle frontal gyrus L 9,44, ,3, Inferior temporal gyrus R 20,21, ,-63, m vs. NC None 1m vs. Pre Middle frontal gyrus L 9,44, ,36, Inferior frontal gyrus, L 44,45, ,39, triangular Superior parietal gyrus L 7, ,-54, Inferior parietal gyrus L ,-39, Inferior frontal gyrus, R 44, ,9, opercular L 44, ,6, Middle temporal gyrus L 20,21, ,-60, Inferior temporal gyrus L 20,21, ,-63, Middle frontal gyrus R 10,44,45,46, ,-6, m vs. Pre 2

3 Middle frontal gyrus R 44, ,-3, Inferior parietal gyrus L ,-42, R ,-39, Superior parietal lobule L 7, ,-60, Postcentral gyrus L 43, ,-39, R 43, ,-33, Middle occipital gyrus L 7, ,-81, Inferior frontal gyrus, R 44, ,6, opercular 6m vs. 1m None Central-Executive Network (CEN) Pre vs. NC Inferior frontal gyrus, R 38,44,45,47, ,9, opercular Inferior parietal gyrus L 40, ,-42, Middle temporal gyrus R 22, ,-48, L 22, ,-66, Superior temporal gyrus R 21,22, ,-51, Supramarginalgryus R 22,40, ,-45, Inferior parietal lobule R 39, ,-42, m vs. NC Middle temporal gyrus L 22, ,-57, Inferior parietal gyrus L 40, ,-42, Inferior frontal gyrus R 44,45, ,24, Superior temporal gyrus R 21,22, ,-48, Middle temporal gyrus R 22, ,-45, m vs. NC None 1m vs. Pre 3

4 Supramarginalgryus R 22,40, ,-48, Inferior Parietal Lobule R 39, ,-21, Superior temporal gyrus R 21,22, ,-39, Middle temporal gyrus R 22, ,-57, m vs. Pre Supramarginalgyrus L 22,40, ,-45, R 22,40, ,-57, Inferior parietal lobule L 40, ,-33, R 39, ,-42, Middle temporal gyrus R 22, ,-69, Superior temporal gyrus R 21,22, ,-57, m vs. 1m Supramarginalgyrus L 22,40, ,-24, Postcentral gyrus L 2,3,22, ,-27, Sensory-Motor Network (SMN) Pre vs. NC Postcentral gyrus L 1,2,3,4, ,-9, R 1,2,3,4, ,-9, Precentral gyrus L 3,4,6, ,-12, R 3,4,6,43, ,-3, m vs. NC Precentral gyrus L 3,4,6, ,-6, R 3,4,6,43, ,0, Postcentral gyrus L 1,2,3,4, ,-12, m vs. NC Supramarginal gyrus R 1,2,3,42, ,-30, Precentral gyrus L 3,4,6, ,-6, m vs. Pre Postcentral gyrus R 3,4,6,43, ,-9, Precentral gyrus R 3,4,6, ,-6,

5 6m vs. Pre Supplementary motor area L ,12, Postcentral gyrus R 3,4,6,43, ,-9, L 3,4,6,43, ,-9, Precentral gyrus R 3,4,6,43, ,-9, L 3,4,6, ,-9, m vs. 1m None Self-Referential Network (SRN) Pre vs. NC None 1m vs. NC None 6m vs. NC None 1m vs. Pre None 6m vs. Pre None 6m vs. 1m None Auditory Network (AN) Pre vs. NC Superior temporal gyrus L 21,22,41,42, ,-24, R 21,22,41,42, ,9, Rolandic operculum R 22,41,42, ,-18, L 22,41, ,-21, Supramarginalgryus L 22,42, ,-33, Middle temporal gyrus R 21, ,-54, m vs. NC 5

6 Superior temporal gyrus L 21,22,41,42, ,-12, m vs. NC None 1m vs. Pre Rolandic operculum R 22,41,42, ,6, L 22,41, ,-21, Superior Temporal Gyrus R 21,22,41,42, ,3, L 21,22,41,42, ,-27, Insula L 22,42, ,-6, m vs. Pre Superior temporal gyrus L 21,22,41,42, ,-39, R 21,22,41,42, ,-9, Rolandic operculum R 22,41,42, ,-12, m vs. 1m Superior temporal gyrus R 21,22,41,42, ,-15, Rolandic operculum R 22,41,42, ,-9, Visual Network (VN) Pre vs. NC Calcarine fissure R 17,18, ,-54, L 17,18, ,-54, Cuneus L 17,18, ,-84, R 17,18, ,-69, m vs. NC Calcarine fissure R 17,18, ,-66, Superior occipital gyrus R 17,18, ,-90, m vs. NC None 1m vs. Pre Calcarine fissure L 17,18, ,-54, R 17,18, ,-54, m vs. Pre 6

7 Calcarine fissure R 17,18, ,-72, Lingual gyrus L 17,18, ,-51, m vs. 1m None BA = Brodmann area; MNI= Montreal Neurological Institute; Pre= pretransplantation; NC=normal controls; 1m= 1 month after kidney transplantation; 6m= 6 months after kidney transplantation. 7

8 Supplementary Table 2 Relationships between the changes of functional connectivity and changes of neuropsychological scores before and 1-month/6-month after kidney transplantation. Dependent variable Default mode Network 1m vs. Pre Independent factors B SE P LR LR P TIME NCT DST Medial frontal gyrus (L) LTT SDT SAS SDS TIME NCT DST Medial frontal gyrus(r) LTT SDT SAS SDS TIME NCT

9 DST Superior Frontal Gyrus,medial(R) LTT SDT SAS SDS TIME < NCT DST Posterior cingulate cortex LTT SDT SAS SDS m vs. Pre TIME < NCT DST Superior frontal gyrus(r) LTT SDT SAS SDS TIME NCT

10 DST Posterior cingulate LTT m vs. 1m SDT SAS SDS TIME <0.001 NCT DST Medial superior frontal gyrus(l) LTT SDT SAS SDS Dorsal Attention Network (DAN) 1m vs. Pre TIME NCT DST Middle frontal gyrus(l) LTT SDT SAS SDS

11 TIME NCT DST Inferior frontal gyrus, triangular(l) LTT SDT SAS SDS TIME NCT DST Superior parietal gyrus(l) LTT SDT SAS SDS TIME NCT DST Inferior parietal gyrus(l) LTT SDT SAS SDS

12 TIME NCT DST Inferior frontal gyrus, opercular(r) LTT SDT SAS SDS TIME NCT DST Inferior frontal gyrus, opercular(l) LTT SDT SAS SDS TIME NCT DST Middle temporal gyru(l) LTT SDT SAS SDS

13 TIME NCT DST Inferior temporal gyrus(l) LTT SDT SAS SDS TIME NCT DST Middle frontal gyrus(r) LTT SDT SAS SDS m vs. Pre TIME NCT DST Middle frontal gyrus(r) LTT SDT SAS SDS

14 TIME NCT DST Inferior parietal gyrus(l) LTT SDT SAS SDS TIME NCT DST Inferior parietal gyrus(r) LTT SDT SAS SDS TIME <0.001 NCT DST Superior parietal lobule(l) LTT SDT SAS SDS

15 TIME NCT DST Postcentralgyrus(L) LTT SDT SAS SDS TIME NCT DST Postcentralgyrus(R) LTT SDT SAS SDS TIME NCT DST Middle occipital gyrus(l) LTT SDT SAS SDS

16 TIME NCT DST Inferior frontal gyrus, opercula(r) LTT SDT SAS SDS Central-Executive Network (CEN) 1m vs. Pre TIME NCT DST Supramarginalgryus(R) LTT SDT SAS SDS TIME NCT DST Inferior Parietal Lobule(R) LTT SDT SAS

17 SDS TIME <0.001 NCT DST Superior temporal gyrus(r) LTT SDT SAS SDS TIME NCT DST Middle temporal gyrus(r) LTT SDT SAS SDS m vs. Pre TIME NCT DST Supramarginalgyrus (L) LTT SDT SAS

18 SDS TIME NCT DST Supramarginalgyrus (R) LTT SDT SAS SDS TIME NCT DST Inferior parietal lobule(l) LTT SDT SAS SDS TIME <0.001 NCT DST Inferior parietal lobule(r) LTT SDT SAS

19 SDS TIME NCT DST Middle temporal gyrus(r) LTT SDT SAS SDS TIME NCT DST Superior temporal gyrus(r) LTT SDT SAS SDS m vs. 1m TIME NCT DST Supramarginalgyrus(L) LTT SDT SAS

20 SDS TIME NCT DST Postcentralgyrus(L) LTT Sensory-Motor Network (SMN) 1m-Pre SDT SAS SDS TIME <0.001 NCT DST Postcentralgyrus (R) LTT SDT SAS SDS TIME NCT DST Precentralgyrus(R) LTT SDT

21 SAS SDS m-Pre TIME NCT DST Supplementary motor area (L) LTT SDT SAS SDS TIME NCT DST Postcentralgyrus (R) LTT SDT SAS SDS TIME NCT DST Postcentralgyrus (L) LTT SDT

22 SAS SDS TIME NCT DST Precentralgyrus (R) LTT SDT SAS SDS TIME NCT DST Precentralgyrus (L) LTT SDT SAS SDS m-1m Auditory Network (AN) 1m-Pre TIME NCT DST

23 Rolandic operculum(r) LTT SDT SAS SDS TIME NCT DST Rolandic operculum(l) LTT SDT SAS SDS TIME NCT DST Superior Temporal Gyrus(R) LTT SDT SAS SDS TIME NCT DST

24 Superior Temporal Gyrus(L) LTT SDT SAS SDS TIME NCT DST Insula (L) LTT SDT SAS SDS m-Pre TIME < NCT DST Superior temporal gyrus (L) LTT SDT SAS SDS TIME NCT DST

25 Superior temporal gyrus(r) LTT SDT SAS SDS TIME < NCT DST Rolandic operculum (R) LTT SDT SAS SDS m-1m TIME NCT DST Superior temporal gyrus (R) LTT SDT SAS SDS TIME NCT DST

26 Rolandic operculum(r) LTT SDT SAS SDS Visual Network (VN) 1m-Pre Calcarine fissure(l) TIME NCT DST LTT SDT SAS SDS TIME NCT DST Calcarine fissure(r) LTT SDT SAS SDS m-Pre TIME NCT DST Calcarine fissure(r) LTT

27 SDT SAS SDS TIME NCT DST Lingual gyrus(l) LTT SDT SAS SDS

28 Supplemental material is neither peer-reviewed nor thoroughly edited by CJASN. The authors alone are responsible for the accuracy and presentation of the material. Supplementary texts: MR Imaging Data Acquisition MR imaging data were acquired using a 3T MR system (TIM Trio; Siemens Medical Solutions, Erlangen, Germany). All subjects were instructed to do lie still, keep their eyes closed, and stay awake during MRI. Foam padding was used to reduce head motion. T1-weighted and T2 fluid-attenuated inversion-recovery anatomic images of each subject were obtained for the detection of silent lesions using the following two sequences: (a) axial T1 fast low-angle shot sequence with 30 axial slices; slice thickness, 4 mm; slice gap, 0.4 mm; image matrix, 320 x 256; field of view, 240 x 240 mm 2 ; repetition time (TR) /echo time (TE), 350/2.46 ms and (b) axial T2 fluidattenuated inversion-recovery sequence with 25 axial slices; slice thickness, 4 mm; slice gap, 1.2 mm; image matrix, 232 x 256; field of view, 220 x 220 mm 2 ; TR/TE, 9000/93 ms; flip angle, 130 ; inversion time, 2500 ms, bandwidth 287 Hz/Px. Functional data were obtained using a gradient-echo echo-planar sequence: slice thickness, 4 mm; slice gap, 0.4 mm; matrix, 64 x 64; field of view, 240 x 240 mm 2 ; TR/TE, 2000/30 ms; flip angle, 90. Each functional MRI sequence contained 250 volumes, and each volume included 30 axial sections placed approximately along the anterior posterior commissure line. Each functional MRI scan lasted 500 seconds. Data Preprocessing Data were preprocessed and analyzed using statistical parametric mapping (SPM8, with a software platform (Matlab; MathWorks, Natick, Mass). The first 10 volumes of the functional images were discarded to allow image stabilization and participants adaptation to the environment. The section timing, head motion correction, and spatial normalization were adjusted to the standard Montreal Neurologic Institute template, with a resampled voxel size of 3 x 3 x 3 mm 3. Afterwards, the data were spatially smoothed by means of convolution with an isotropic Gaussian kernel of 8 mm. Independent component analysis and identification of resting state networks Group spatial independent component analysis was conducted using the GIFT software ( Vision 2.0d). Independent component analysis separates linear mixed data into spatially independent sources. To determine the numbers of independent components, dimension estimation of the smoothed data of the two groups was conducted using the minimum description length criterion. Then, functional MRI data from all subjects in each group were concatenated and the temporal dimension of the aggregate data set was reduced by means of principal component analysis, followed by an independent component estimation (with time- 28

29 Supplemental material is neither peer-reviewed nor thoroughly edited by CJASN. The authors alone are responsible for the accuracy and presentation of the material. courses and spatial maps) using the infomax algorithm. The spatial independent component analysis for 32 independent components was performed on the patient and control groups together to ensure that the resting state networks demonstrated similar spatial patterns in both groups. Independent component time-courses and spatial maps for each subject were back-reconstructed using the aggregated components and the results from the data reduction step. For each independent component, the time courses correspond to the waveform of a specific pattern of brain activity. The intensity of this pattern of brain activity across the voxels was expressed by the associated spatial map (1). Using the GIFT software, the components to be retained for further analysis were selected from among the 32 estimated independent components based on the largest spatial correlation with specific resting state network templates. To display the voxels that most strongly contributed to a particular independent component, the intensity values in each spatial map were converted to z-values. The z-values here reflect the degree to which the time courses of a given voxel correlate to the time courses of each special independent component. Seven resting state network templates were used in this study: dorsal attention network, central executive network, default mode network, self-referential network, sensorimotor network, visual network, and auditory network, which can be found in previous studies (2, 3). References 1. Greicius MD, Srivastava G, Reiss AL, Menon V: Default mode network activity distinguishes Alzheimer's disease from healthy aging: evidence from functional MRI. Proc Natl Acad Sci U S A, 101: , Qi R, Zhang LJ, Xu Q, Zhong J, Wu S, Zhang Z, Liao W, Ni L, Zhang Z, Chen H, Zhong Y, Jiao Q, Wu X, Fan X, Liu Y, Lu G: Selective impairments of resting state networks in minimal hepatic encephalopathy. PLoS One, 7: e37400, Mantini D, Corbetta M, Perrucci MG, Romani GL, Del Gratta C: Large scale brain networks account for sustained and transient activity during target detection. Neuroimage, 44: ,

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