Research Article

A Brain Network Constructed on an L1-Norm Regression Model Is More Sensitive in Detecting Small World Network Changes in Early AD

Table 4

values of statistical tests on the small-world parameters using L1-norm regularization.

L1
HCs-MCIHCs-AD

DensityCpLpElocEgCpLpElocEg
0.100.64040.64010.20530.66980.00940.06090.00870.0650
0.110.87350.61500.44720.61070.05710.02760.04640.0289
0.120.25290.82560.64000.80830.15300.02400.027050.0221
0.130.33620.76390.75190.72100.11580.03090.23270.0249
0.140.52080.61250.78670.58410.29480.03210.74300.0250
0.150.19870.54900.26870.53390.40260.02400.93640.0188
0.160.06150.54340.03150.52730.59590.01640.54820.0128
0.170.10970.38250.04140.37020.46580.01060.57190.0077
0.180.17130.35040.03920.34550.44880.00860.55320.0056
0.190.19350.30350.03290.30010.38560.00880.71970.0058
0.200.29300.34420.07800.33600.43920.00520.61510.0031
0.210.23930.34400.06340.32920.46950.00900.56050.0061
0.220.28630.31610.07490.30600.38660.01620.83170.0117
0.230.19490.35890.02240.35220.49690.02050.58730.0176
0.240.15060.32470.01160.31070.56470.01510.62870.0132
0.250.15000.29470.02030.28760.50150.01550.82360.0131
0.260.12520.33620.00790.32720.58590.02260.60540.0204
0.270.12680.36250.00550.35280.52710.01570.59210.0146
0.280.12310.58060.00730.56300.47570.00630.67510.0058
0.290.10840.46270.00830.45030.44240.00200.87840.0019
0.300.12040.42880.00730.41580.39620.00280.99670.0026
0.310.13900.52070.01680.50650.40800.00450.89100.0043
0.320.15290.44810.02410.43240.41090.00500.83490.0048
0.330.14890.47870.02970.46260.43450.00720.80900.0070
0.340.15630.51080.03660.50220.46570.00670.88550.0065
0.350.17440.68420.04220.67020.47380.00380.94020.0037
0.360.13110.68120.03570.66820.58610.00420.95680.0041
0.370.11390.91210.03650.92620.58660.00170.97770.0017
0.380.10820.91400.03710.90140.63040.00180.95630.0017
0.390.11250.11250.94570.04700.66720.00240.96890.0024
0.400.96890.98240.05020.99360.75390.00410.93370.0041
0.410.08830.87230.05130.88200.78150.00960.95680.0096
0.420.09630.78820.05100.79590.81870.02530.94380.0253
0.430.08690.22720.04350.22630.84550.02930.91370.0293
0.440.09000.23010.05330.22930.86020.04000.94980.0400
0.450.05500.30390.02820.30310.97130.06410.77270.0641
0.460.04960.72390.02670.72250.96470.14260.79200.1426
0.470.04190.88470.02560.88380.92850.20160.78300.2016
0.480.04280.58870.02910.58820.93560.17120.82720.1712
0.490.03970.67680.02970.67650.82010.19530.73020.1953
0.500.04030.63580.03460.63550.72530.24240.67260.2424