Reading relies on the ability to map written symbols with speech sounds. A specific part of the left ventral occipitotemporal cortex, known as the Visual Word Form Area (VWFA), plays a crucial role in this process. Through the automatization of the mapping ability, this area progressively becomes specialized in written word recognition. Yet, despite its key role in reading, the area also responds to speech. This observation raises questions about the actual nature of neural representations encoded in the VWFA and, therefore, the underlying mechanism of the cross-modal responses. Here, we addressed this issue by applying fine-grained analyses of within- and cross-modal repetition suppression effects (RSEs) and Multi-Voxel Pattern Analyses in fMRI and sEEG experiments. Convergent evidence across analysis methods and protocols showed significant RSEs and successful decoding in both within-modal visual and auditory conditions, suggesting that populations of neurons within the VWFA distinctively encode written and spoken language. This functional organization of neural populations enables the area to respond to both written and spoken inputs. The finding opens further discussions on how the human brain may be prepared and adapted for an acquisition of a complex ability such as reading.

It has been argued that university students with dyslexia compensate for their reading deficits by a neural re-organization of the typical reading network, where the lexical representations of words are (re-)structured according to semantic rather than orthographic information. To investigate the re-organization of neural word representations more directly, we used multivariate representational similarity analyses (RSA) to find out which brain regions of the reading network respond to orthographic and semantic similarity between 544 pairs of words and whether there were any differences between typical and dyslexic readers. In accordance with the re-organization hypothesis, we predicted greater similarity (i.e., correlation of neural dissimilarity matrices) in adult dyslexic than in typical readers in regions associated with semantic processing and weaker similarity in regions associated with orthographic processing. Our results did not confirm these predictions. First, we found sensitivity to semantic similarity in all three subparts of the fusiform gyrus (FG1, FG2, and FG3) bilaterally. Adults with dyslexia showed less (rather than more) sensitivity to semantic similarity in the posterior subpart of fusiform gyrus (FG1) in the left hemisphere. Second, in typical readers, sensitivity to orthographic information was not only found in the left fusiform gyrus (FG1, FG2, and FG3) but also in left inferior frontal gyrus (IFG). Adults with dyslexia, in contrast, did not show sensitivity to orthographic information in left IFG. However, they showed increased sensitivity to orthographic information in the right hemisphere FG1. Together, the results show abnormal orthographic processing in left IFG and right FG1 and reduced semantic information in left FG1. While we found evidence for compensatory re-organization in adult dyslexia, the present results do not support the hypothesis according to which adults with dyslexia rely more heavily on semantic information. Instead, they revealed atypical hemispheric organization of the reading network that is not restricted to the typical left language hemisphere.