For corresponding regions. We rank-correlated activation profiles across regions to explore

For corresponding regions. We rank-correlated activation profiles across regions to explore which regions showed similar activation profiles. We performed our correlation analysis for all images, for faces only, and for places only. Results are shown both for the concatenation approach (left) and the averaging approach (right) for combining single-subject data. Each correlation matrix is mirror-symmetric about a diagonal of ones. We performed a standard one-sided test on Spearman’s r to determine whether inter-region correlations of activation profiles were significantly higher than expected by chance (H0: r 0). p values were corrected for multiple comparisons using Bonferroni correction for the whole figure (15 inter-region comparisons 6 matrices 90 comparisons). Results are shown for the ROI sizes that results were displayed at in Figures 1 (FFA and PPA) and 2 (hIT and EVC). Results show correlated activation profiles between EVC and IT, and between hemispheres for FFA and PPA. In addition, the activation profile of EVC is correlated with that of category-selective regions when considering the full image set, but not ARRY-334543 web within places for PPA, and within faces only for left (not right) FFA. This suggests that EVC is not a major contributor to the within-category activation profiles of PPA and right FFA.clearly weaker than those elicited by any of the face images (Tsao et al., 2006). Kiani et al. (2007) reported a similar finding: they measured responses of face-selective cells in macaque IT cortex, and reported imperfect face selectivity at the single-cell level but close-to-perfect face selectivity when responses were averaged over a small population of face-selective IT cells. These findings are consistent with the idea that category membership of natural objects is encoded at the population level (Vogels, 1999; Kiani et al., 2007; Kriegeskorte et al., 2008). In sum, our results suggest that category selectivity of FFA and PPA, conventionally investigated using Mikamycin IAMedChemExpress Pristinamycin IA category-average activation, might hold for single images. FFA single-image activation profiles appear similar to those described for the macaque middle face patch, consistent with a homology or functional analogy. If the recently reported place-selective region in the macaque (Bell et al., 2009) is the homolog or functional analog of the humanMur et al. ?Single-Image Activation of Category RegionsJ. Neurosci., June 20, 2012 ?32(25):8649 ?8662 ?Figure 8. Summary of results.Single-image designs for studying regional-average activation and pattern information The classical fMRI category-block-design studies (e.g., Kanwisher et al., 1997; Epstein and Kanwisher, 1998) averaged across stimuli within predefined categories and across response channels (i.e., voxels within contiguous regions). Haxby et al. (2001) studied pattern information, but still averaged patterns within predefined categories. Kriegeskorte et al. (2008) studied pattern information of single-image response patterns, enabling datadriven discovery of category structure (Edelman et al., 1998). The present study constitutes a missing link in the sense that it considers single-image responses, but in terms of regional-average activation levels. Building on previous single-image fMRI approaches (Edelman et al., 1998; Aguirre, 2007; Kriegeskorte et al., 2007, 2008; Eger et al., 2008; Haushofer et al., 2008; Kravitz et al., 2011), this study further demonstrates the feasibility of single-image fMRI experiments. Single-image.For corresponding regions. We rank-correlated activation profiles across regions to explore which regions showed similar activation profiles. We performed our correlation analysis for all images, for faces only, and for places only. Results are shown both for the concatenation approach (left) and the averaging approach (right) for combining single-subject data. Each correlation matrix is mirror-symmetric about a diagonal of ones. We performed a standard one-sided test on Spearman’s r to determine whether inter-region correlations of activation profiles were significantly higher than expected by chance (H0: r 0). p values were corrected for multiple comparisons using Bonferroni correction for the whole figure (15 inter-region comparisons 6 matrices 90 comparisons). Results are shown for the ROI sizes that results were displayed at in Figures 1 (FFA and PPA) and 2 (hIT and EVC). Results show correlated activation profiles between EVC and IT, and between hemispheres for FFA and PPA. In addition, the activation profile of EVC is correlated with that of category-selective regions when considering the full image set, but not within places for PPA, and within faces only for left (not right) FFA. This suggests that EVC is not a major contributor to the within-category activation profiles of PPA and right FFA.clearly weaker than those elicited by any of the face images (Tsao et al., 2006). Kiani et al. (2007) reported a similar finding: they measured responses of face-selective cells in macaque IT cortex, and reported imperfect face selectivity at the single-cell level but close-to-perfect face selectivity when responses were averaged over a small population of face-selective IT cells. These findings are consistent with the idea that category membership of natural objects is encoded at the population level (Vogels, 1999; Kiani et al., 2007; Kriegeskorte et al., 2008). In sum, our results suggest that category selectivity of FFA and PPA, conventionally investigated using category-average activation, might hold for single images. FFA single-image activation profiles appear similar to those described for the macaque middle face patch, consistent with a homology or functional analogy. If the recently reported place-selective region in the macaque (Bell et al., 2009) is the homolog or functional analog of the humanMur et al. ?Single-Image Activation of Category RegionsJ. Neurosci., June 20, 2012 ?32(25):8649 ?8662 ?Figure 8. Summary of results.Single-image designs for studying regional-average activation and pattern information The classical fMRI category-block-design studies (e.g., Kanwisher et al., 1997; Epstein and Kanwisher, 1998) averaged across stimuli within predefined categories and across response channels (i.e., voxels within contiguous regions). Haxby et al. (2001) studied pattern information, but still averaged patterns within predefined categories. Kriegeskorte et al. (2008) studied pattern information of single-image response patterns, enabling datadriven discovery of category structure (Edelman et al., 1998). The present study constitutes a missing link in the sense that it considers single-image responses, but in terms of regional-average activation levels. Building on previous single-image fMRI approaches (Edelman et al., 1998; Aguirre, 2007; Kriegeskorte et al., 2007, 2008; Eger et al., 2008; Haushofer et al., 2008; Kravitz et al., 2011), this study further demonstrates the feasibility of single-image fMRI experiments. Single-image.