SUPPLEMENTARY MATERIAL Method The False Discovery Rate (FDR) method offers an objective way to select a p- value threshold that is automatically adaptive to each mapping result. The p- value threshold was determined based on the following equation: p(i) ≤ { (i/V) · [q/c(V)] } [S1] • V denotes the total number of voxels been tested; • p(i) denotes the i-th order statistic among the p-values from all voxels: p(1) ≤ p(2) ≤ ... ≤ p(i) ≤ … ≤ p(V); • q controls the proportion of declared-active voxels which are false positive. We set q to 0.05, 0.1 and 0.2 to compare activity patterns at different false discovery rates; • c(V) = log(V)+0.5772 (Benjamini and Yekutieli, 2001). The largest p(i) satisfying the equation would be the threshold. False positive error analysis of the statistical parameter mapping To examine the efficiency of Gaussian filtering to minimize the number of false positive errors during multiple comparisons, we compared the number of significant voxels produced by Gaussian filtering and by the FDR method (Genovese et al., 2002). FDR analysis enables estimates to be made of the p- value distribution in multiple comparisons, and calculates the threshold pth corresponding to a defined q-value, where the parameter q represents the upper bound on the proportion of declared-active voxels which are false. The FDR - 1 - method was used to assess the statistical mapping at 40 kHz, 89 dB peak SPL. After setting FDR q-parameter at values between 0.1 and 0.8, the maximum p- value was calculated to fit in the FDR equation (S1). These maximum p-values were then defined as the pth for the FDR 3D statistical p–maps, and the same processing was performed for visualizing the p-maps as with Gaussian filtering. When we applied the FDR-derived pth to the original statistical images, there was reasonable agreement in the spatial patterns and numbers of active voxels in the IC. The FDR p-maps can be compared to those derived after Gaussian filtering (GF) (Suppl. Table 1): GF with pth=0.05 (Fig. 2C) vs q=0.8, FDR pth=0.013 (Suppl. Fig. 1B); GF with pth=0.02 (Fig. 2F) vs q=0.2, FDR pth=0.0012 (Suppl. Fig. 1D); GF with pth=0.01 (Fig. 2I) vs q=0.15, FDR pth=0.0005 (Suppl. Fig. 1F). These results indicate that Gaussian filtering effectively adjusted the pth in the original statistical images, showing the threshold pth=0.05 in Gaussian filtered statistical images has similar constraining power to the threshold pth=0.013 without filtering. Nevertheless, we need to set a much lower pth to reduce the proportion of false positive voxels among the declared-active voxels. For example, when pth=0.0005, the FDR results estimate that less than 15% (q=0.15) of the active voxels are likely to be false positive (Suppl Fig 1E). However, the FDR method is too conservative to characterize the active IC regions in the 77dB and 65 dB stimulated mice since no choice of q gives statistical significance for any voxel (Data not shown). In contrast, GF with pth=0.05 shows a clear trend in the active region size and location after stimulation with peak amplitude between 89 and 65 dB SPL (Fig 3). These results show that Gaussian filtering is a less - 2 - conservative method for minimizing false positive statistical errors while preserving the biologically meaningful results of the statistical parameter maps. REFERENCES Benjamini, Y., Yekutieli, D., 2001. The control of the false discovery rate in multiple testing under dependency. Ann. Statist. 29, 1165-1188. Genovese, C.R., Lazar, N.A., Nichols T.E., 2002. Thresholding of statistical maps in functional neuroimaging using the false discovery rate. NeuroImage 15, 870-878. - 3 - Suppl. Fig. 1. FDR analysis of the statistical images after 40kHz, 89-dB SPL stimulation. When FDR q was set at 0.8, 0.2 and 0.15, the corresponding p thresholds were determined: q=0.8: pth=0.013; q=0.2: pth=0.0012; q=0.15, pth=0.0005. The 3D p-maps were represented in the original statistical images at the resulting p thresholds (A, C, E). A constrained smoothing function was employed to smooth the surface of the activity contour. For display purposes only, the smoothed p-maps (B, D, F) were shown to compare with the 3D p-maps after Gaussian filtering. - 4 - Suppl. Table 1 FDR determines the pth and active IC volumes for different q-values. Suprathreshold FDR q FDR pth voxel 0.8 0.013 901 0.2 0.0012 337 0.15 0.0005 166 The pth was determined by FDR analysis with pre-set q values (0.8, 0.2 and 0.15). The number of active voxels was calculated in the original statistical maps at the given pth. - 5 - .