Fig 1.
Evolution of reading performance as a function of schooling in each child across the 7 measurement times.
Each color represents the performance of a given child. The norms for the number of words read per minute is 36.7 (±15.8) at the end of the second year of French school (LUM). S1 Data. LUM, “Lecture en une minute.”
Fig 2.
Category-specific activations across all 7 sessions and 10 children.
(A) Each category is contrasted relative to the other pictures (omitting the grids) while pooling across all 7 sessions. On the right, one example of each presented visual category. The color of the frame indicates the visual category of the specific activation on the slices and of the lines in the plots. The significant clusters (p < 0.001 corrected at the cluster level at p < .05) are presented over an individual child brain. No significant cluster was observed for numbers. See S2 Fig to see the activation for each category separately and S3 Fig for an example in an individual child (child 2). (B) Plots show the evolution over sessions of the betas for each category, at the primary peak in ventral visual cortex for each category and (C) at the peaks of the word specific activations in the whole brain. The first 6 sessions were evenly spaced during the first year of school, while the seventh session occurred at the end of the second year. Note that while the contrast used to create this image weighted all 7 sessions equally, plots revealed linear (e.g., VWFA) as well as quadratic (e.g., parietal, IFG) profiles, which are further analyzed in the text. (https://neurovault.org/collections/3457/). IFGoper, inferior frontal gyrus opercularis; IFGtri, inferior frontal gyrus triangularis; pSTS, posterior superior temporal sulcus; VWFA, visual word form area.
Fig 3.
Evolution of activation in a child (child 2) who was scanned 7 times (top to bottom).
The left columns show the evolution of words > others on whole-brain flat maps and on a slightly inflated view of the left hemisphere. There was no activation of the RR circuit in the first 2 sessions, prior to school onset. Once schooling started, a VWFA activation was quickly detected, increasing in intensity with time and remaining detectable 1 year later. Parietal and prefrontal areas were transiently activated. In the middle column, zoom on the left ventral visual region. The green arrow indicates the VWFA. The right-hand column, ventral areas viewed from the back, illustrates the stability of face-related activations (contrast = faces > others, red arrows). See S3 Fig for the other categories. All contrasts at voxelwise p < 0.001 and clusterwise p < 0.05 FWE corrected. FWE, family-wise error; RR, reading-related; VWFA, visual word form area.
Table 1.
Linear increase of the word activation relative to rest across the 7 sessions in all children.
Fig 4.
Brain activations correlating with reading speed as it evolves across scanning sessions, independently of age.
(A) Effect of reading speed (LUM) on word-evoked activations relative to rest, in a model in which age was also entered as a covariable. (B) Reading speed effect on the activation evoked by faces, words, and numbers. Activation to words (green) and numbers (blue) increased with reading speed in the left occipitotemporal pathway. Reading expertise was also associated with increased responses to faces in the right fusiform gyrus (red). No significant effect was seen for the other categories. All contrasts at voxelwise p < 0.001 and clusterwise p < 0.05 FWE corrected. FWE, family-wise error; LUM, “Lecture en une minute.”
Fig 5.
Evolution of the volume of activity evoked by the different categories in ventral visual cortex.
(A) Slices showing the analyzed ventral visual region (“ventral mask”). (B) Percentage of voxels showing activity specific to at least 1 visual category (i.e., voxels whose activity was significant at p < .001 in the contrast of one category relative to all others). The active volume was expressed, in each child, as a proportion of ventral visual volume (i.e., the intersection of each child’s gray matter mask and the left and right ventral masks). (C) total volume (in mm3) of voxels showing significantly more activity for a given category relative to all others (voxelwise p < 0.001, uncorrected). For reference, the search regions were 36,080 mm3 (left) and 35,896 mm3 (right), and the volume expected by chance would therefore be approximately 36 mm3. S2 Data.
Fig 6.
Evolution of responses in left-hemispheric voxels that ultimately specialize for a given category.
For each child, we subdivided left ventral temporal voxels into the ROI formed by those selective for a given category during the final sessions 6 and 7 (category > others, p < 0.001) and the remaining voxels. We then went back in time and asked how these 2 sets of voxels differed in their responsivity to the various categories of stimuli in the preceding sessions 1–5. Each plot shows the difference in activation evoked by a given stimulus (e.g., words) relative to other categories (excluding words), in voxels within and outside the specified ROI. For instance, the green curve at left indicates that word-selective voxels in sessions 6 and 7 showed no specificity for words during sessions 1 and 2 (values not different from 0) but became selective in sessions 3, 4, and 5 (positive values). Therefore, there is a clear emergence of selectivity for words in RR voxels. The fact that other (nongreen) curves in this panel are indistinguishable from 0 indicates that the VWFA voxels cannot be anticipated by their responsivity to other categories. By contrast, voxels selective to tools, houses, faces, or bodies in sessions 6 and 7 already exhibit their category specificity in the very first sessions. S3 Data. ROI, region of interest; RR, reading-related; VWFA, visual word form area.
Fig 7.
Representation similarity analysis.
In each graph, the thick line shows the within-category correlation coefficient r between 2 independently measured activation patterns, measuring the reproducibly of activation patterns in a given area, and the dotted line shows the between-category baseline (r was measured within each subject, then averaged; bar = ±1 standard error). A significant difference between those curves indicates a reliable category-specific activation. (A) When averaging over sessions, reliable patterns were present for all categories in the left ventral mask. (B) Temporal evolution across sessions of the r coefficient for words and for the average of nonsymbolic images (tools, bodies, faces, and houses) in the left ventral mask. (C) and (D), same as (A) and (B), restricted to the visual word form area. (E) and (F), similarity of the word-induced activation pattern in each ROI selective for a given category relative to others, respectively within the left and right ventral masks. All comparisons within versus between category are significant, except those indicated as ns. Underlying data found in S4 Data. FFA, fusiform face area; ns, nonsignificant; ROI, region of interest; VWFA, visual word form area.
Fig 8.
Schematic model of ventral visual development.
Hexagons depict cortical patches or columns specialized for a given category (tools, faces, houses) or in an uncommitted labile state. Each group of hexagons schematizes the state of the left-hemispheric ventral visual mosaic at a given age. Prior to schooling (left), some columns are already committed to a given category, with a systematic lateral-to-mesial organization (left-to-right), but many are still labile. When schooling starts, some columns commit to written words (top right). In the absence of schooling, the same columns are progressively invaded by nearby representations of tools and faces (bottom right). The dashed yellow box illustrates how a single fMRI voxel may comprise a mixture of cortical responses to tools and words. The model can explain why, (1) in literate children, VWFA voxels become selective to words while maintaining their prior response to tools; (2) literacy blocks the expansion of face responses in the left hemisphere, restricting their growth to the right hemisphere; and (3) in illiterate subjects, relative to literate ones, face responses are larger in the left hemisphere and thus less asymmetrical in favor of the right hemisphere. F, faces; fMRI, functional magnetic resonance imaging; H, houses; L, labile; T, tools; VWFA, visual word form area.