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. Author manuscript; available in PMC: 2011 Oct 15.
Published in final edited form as: Neuroimage. 2010 May 23;53(1):103–118. doi: 10.1016/j.neuroimage.2010.05.051

Figure 7. Normalization of response patterns across stimuli or across voxels had no significant effect on classification accuracy.

Figure 7

Mean classification accuracies for raw patterns of t-values and for normalized patterns. Patterns were initially defined by t-values (red bars). Error bars show the standard error of the mean across subjects. The left-column panels show across-stimuli normalizations: the patterns were normalized by subtracting the mean across stimuli (green bars) and then additionally dividing by the standard deviation across stimuli for each voxel (blue bars). The right-column panels show across-voxels normalizations: the data were normalized by subtracting the mean across voxels (green bars) and then additionally dividing by the standard deviation across voxels for each stimulus (blue bars). Results are shown separately for leave-one-run-out cross-validation (a) and leave-one-stimulus-pair-out cross-validation (b), but averaged across ROIs, ROI sizes, category dichotomies, and subjects. The statistical analysis was performed separately for each ROI, ROI size, category dichotomy, and subject. We found no significant effects of the four different pattern normalizations (paired t tests across stimuli, p < 0.05, Bonferroni-corrected, in at least two of four subjects).