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. 2010 Dec 20;5(12):e15710. doi: 10.1371/journal.pone.0015710

Figure 6. Boxplots over all RSNs (excluding the artefactual ICA components) and over all 3 subjects, quantifying various image statistics.

Figure 6

The top row in each sub-figure shows a separate boxplot for each of the three TRs, and the bottom row shows the ratio of the 0.8 s and 0.4 s values to the 2.5 s values, the ratio being calculated separately for each RSN (and each subject) before feeding into the boxplot. Fig. 6a shows the results from a 100-dimensional ICA decomposition across all 3 TRs (separately for each subject) and Fig. 6b shows the results from a 10-dimensional regression of previously published large-scale RSNs from a separate study. For each regression type (multiple or single) and for each RSN map, we have a ‘mixture-model-corrected’ Z-stat image (see Methods). The two main measures we take from that Z-stat image are the peak value and the sum of all Z-stat values over a threshold. For the voxel having the peak Z-stat, we also report the parameter estimate (‘PE’, or RSN amplitude, shown as a % signal change) and the size of the regression residuals. Finally we also show the ratio of these two measures, which contains similar information to the Z-stat (i.e., CNR), but without taking into account the temporal DOF.