To determine which PCs are significantly different from chance, w

To determine which PCs are significantly different from chance, we compared the semantic PCs to the PCs of the category stimulus matrix (see Experimental Procedures for details of why the stimulus PCs are an appropriate null hypothesis). First, we tested the significance of each subject’s own category model weight PCs. If there is a semantic space underlying category representation in the subject’s brain, then we should find that some of the subject’s selleck chemicals llc model weight PCs explain more of the variance in the

subject’s category model weights than is explained by the stimulus PCs. However, if there is no semantic space underlying category representation in the subject’s selleck chemical brain, then the stimulus PCs should explain the same amount of variance in the category model weights as do the subject’s PCs. The results of this analysis are shown in Figure 3. Six to eight PCs from individual subjects explain significantly more variance in category model weights than do the stimulus PCs (p < 0.001, bootstrap test). These individual subject PCs explain a total of 30%–35% of the variance in category model weights. Thus, our fMRI data are sufficient

to recover semantic spaces for individual subjects that consist of six to eight dimensions. Second, we used the same procedure to test the significance of group PCs constructed using data combined across subjects. To avoid overfitting, we constructed a separate group semantic space for each subject using combined data from the other four subjects. If the subjects share a common semantic space, then some of the group PCs should explain more of the variance in the selected subject’s category

model weights than do the stimulus PCs. However, if the subjects do not share a common semantic space, then the stimulus PCs should explain the same amount of variance in the category model weights as do the group PCs. The results of this analysis are also shown in Figure 3. The first four group PCs explain significantly more variance (p < 0.001, bootstrap test) than do the stimulus PCs in four out of five subjects. These four group PCs explain on average 19% of the total variance, 72% as much as do the first four individual Thalidomide subject PCs. In contrast, the first four stimulus PCs only explain 10% of the total variance, 38% as much variance as the individual subject PCs. This result suggests that the first four group PCs describe a semantic space that is shared across individuals. Third, we determined how much stimulus-related information is captured by the group PCs and full category model. For each model, we quantified stimulus-related information by testing whether the model could distinguish among BOLD responses to different movie segments (Kay et al., 2008; Nishimoto et al., 2011; see Experimental Procedures for details).

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