We used coordinate-based meta-analysis to objectively quantify commonalities and differences of dyslexic functional brain abnormalities between alphabetic languages differing in orthographic depth. Specifically, we compared foci of under- and overactivation in dyslexic readers relative to nonimpaired readers reported in 14 studies in deep orthographies (DO: English) and in 14 studies in shallow orthographies (SO: Dutch, German, Italian, Swedish). The separate meta-analyses of the two sets of studies showed universal reading-related dyslexic underactivation in the left occipitotemporal cortex (including the visual word form area (VWFA)). The direct statistical comparison revealed higher convergence of underactivation for DO compared with SO in bilateral inferior parietal regions, but this abnormality disappeared when foci resulting from stronger dyslexic task-negative activation (i.e., deactivation relative to baseline) were excluded. Higher convergence of underactivation for DO compared with SO was further identified in the left inferior frontal gyrus (IFG) pars triangularis, left precuneus, and right superior temporal gyrus, together with higher convergence of overactivation in the left anterior insula. Higher convergence of underactivation for SO compared with DO was found in the left fusiform gyrus, left temporoparietal cortex, left IFG pars orbitalis, and left frontal operculum, together with higher convergence of overactivation in the left precentral gyrus. Taken together, the findings support the notion of a biological unity of dyslexia, with additional orthography-specific abnormalities and presumably different compensatory mechanisms. The results are discussed in relation to current functional neuroanatomical models of developmental dyslexia. Hum Brain Mapp 37:2676-2699, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.
Pubmed ID: 27061464 RIS Download
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Statistical method and software for conducting image- and coordinate-based meta-analysis of neuroimaging studies investigating differences in brain activity (e.g. BOLD response in fMRI, metabolism in PET) or structure (e.g. gray matter volume in VBM, voxel-based or TBSS white matter fractional anisotropy in DTI, etcetera).
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