Effective connectivity of visual word recognition and homophone orthographic errors - Guàrdia-Olmos, Joan; Peró-Cebollero, Maribel; Zarabozo-Hurtado, Daniel; González-Garrido, Andrés A.; Gudayol-Ferré, Esteve (Frontiers in Psychology, 2015)
The study of orthographic errors in a transparent language like Spanish is an important topic in relation to writing acquisition. The development of neuroimaging techniques, particularly functional Magnetic Resonance Imaging (fMRI), has enabled the study of such relationships between brain areas. The main objective of the present study was to explore the patterns of effective connectivity by processing pseudohomophone orthographic errors among subjects with high and low spelling skills. Two groups of 12 Mexican subjects each, matched by age, were formed based on their results in a series of ad-hoc spelling-related out-scanner tests: a High Spelling Skills group (HSS) and a Low Spelling Skills group (LSS). During the fMRI session, two experimental tasks were applied (spelling recognition task and visuoperceptual recognition task). Regions of Interest (ROIs) and their signal values were obtained for both tasks. Based on these values, SEMs (Structural Equation Models) were obtained for each group of spelling competence (HSS and LSS) and task through ML (Maximum Likelihood) estimation, and the model with the best fit was chosen in each case. Likewise, DCM (Dynamic Causal Models) were estimated for all the conditions across tasks and groups. The HSS group’s SEM results suggest that, in the spelling recognition task, the right middle temporal gyrus, and, to a lesser extent, the left parahippocampal gyrus receive most of the significant effects, whereas the DCM results in the visuoperceptual recognition task show less complex effects, but still congruent with the previous results, with an important role in several areas. In general, these results are consistent with the major findings in partial studies about linguistic activities but they are the first analyses of statistical effective brain connectivity in transparent languages.