Intact reading ability in spite of a spatially distributed visual word form 'area' in an individual born without the left superior temporal lobe

Abstract

The visual word form area (VWFA) is an experience-dependent region in the left ventral temporal cortex (VTC) of literate adults that responds selectively to visual words. Why does it emerge in this stereotyped location? Past research shows the VWFA is preferentially connected to the left-lateralized frontotemporal language network. However, it remains unclear whether the presence of a typical language network and its connections with VTC are critical for the VWFAs emergence, and whether alternative functional architectures may support reading ability. We explored these questions in an individual (EG) born without the left superior temporal lobe but exhibiting normal reading ability. We recorded fMRI activation to visual words, objects, faces, and scrambled words in EG and neurotypical controls. We did not observe word selectivity either in EGs right homotope of the VWFA (rVWFA)--the most expected location given that EGs language network is right-lateralized--or in her spared left VWFA (lVWFA), despite typical face selectivity in both the right and left fusiform face area (rFFA, lFFA). We replicated these results across scanning sessions (5 years apart). Moreover, in contrast with the idea that the VWFA is simply part of the language network that responds to general linguistic information, no part of EGs VTC showed selectivity to higher-level linguistic processing. Interestingly, multivariate pattern analyses revealed sets of voxels in EGs rVWFA and lVWFA that showed 1) higher within- than between-category correlations for words (e.g., Words-Words>Words-Faces), and 2) higher within-category correlations for words than other categories (e.g., Words-Words>Faces-Faces). These results suggest that a typical left-hemisphere language network may be necessary for the emergence of focal word selectivity within the VTC, and that orthographic processing can be supported by a distributed neural code.