In the next sections, we describe two types of ROI analyses (see Section 2) with greater detection power, in which tool versus animal word-processing is explored NVP-BKM120 price specifically within picture-category selective ROIs. To test whether the cortical areas with a selectivity for tool or animal pictures depicted in the activation maps in Fig. 2 showed a corresponding selectivity for tool or animal words, we extracted each individual’s BOLD-response to tool words (vs. fixation) and animal words (vs. fixation) from all voxels in age-specific clusters and computed each age group’s average category preference for words (tool words – animal words). The results are displayed in the bottom graphs in Fig. 2. Red bars
indicate areas where subjects showed a significant preference for tool pictures and a corresponding stronger response to tool words. Similarly, blue bars indicate areas AZD2281 where the age group showed a significant preference for animal pictures and a corresponding preference for
animal words. Grey bars indicate areas where the category preference for pictures and words did not correspond (e.g., a tool picture selective cluster with a stronger response to animal words). If printed words activate the same brain regions as their corresponding pictures, the category preference for animal and tool words should have the same direction as the local category preference for animal and tool pictures. In adults, this is clearly the case in all 6 ROIs. Overall, there was a significant category preference for tool and animals words in adult tool- and animal-picture selective cortical areas (F(1, 12) = 9.22, p = 0.010), and a trend towards an interaction effect of ROI × Category (F(5, 8) = 3.56, p = 0.055), indicating that category selectivity for words varied marginally across the 6 ROIs. In the group of 9- to 10-year-olds, the category preference for pictures and words was clearly less consistent, Nintedanib (BIBF 1120) with corresponding response patterns in 4 out of 9 ROIs. There was no significant overall category preference (F(1, 9) = 0.647, p = 0.44), and no interaction of ROI × Category (F(8, 2) = 2.45, p = 0.33).
Similarly, in 7- to 8-year-olds, 4 out of 7 regions showed a corresponding category preference for pictures and words and an ANOVA revealed no significant effects of Category (F(1, 10) = 0.025, p = 0.88) or Category × ROI (F(3.1, 31.1) = 1.74, p = 0.92. Due to the application of a statistical threshold, significant clusters from different age groups differ in number and areas of the brain they encompass (see Appendix A, Table 2). This limits the comparability of activation patterns in individual ROIs across age. To test if the age differences in category selectivity for animal versus tool words in these ROIs were significant, we therefore compared the response to tool and animal names averaged across all picture-selective ROIs.