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    • The present findings can be alternatively explained by

    2018-11-09

    The present findings can be alternatively explained by a progressive enhancement of the neural visual system while children learn to read. In this case, the present changes in Gefitinib responses to visual objects would be mainly due to a specific improvement of basic perceptual skills as the result of reading training. However, previously reported reading-related brain changes in primary visual areas were typically observed in earlier time windows (e.g., 100–200ms; Pegado et al., 2014) and they were usually bilaterally distributed (Dehaene et al., 2010, 2015). The greater involvement of the left hemisphere between 200 and 500ms during object recognition seems to be more likely related to a stronger linguistic decoding of visual stimuli. This interpretation is further supported by the presence of a negative correlation between the left posterior brain responses to visual objects and children’s ability to access linguistic codes given simple line drawings. The more children were able to verbalize schematic visual representations, the stronger the effect over left posterior sites. Consistently with these findings, behavioral studies showed that literates are better than illiterates at naming pictures and retrieving linguistic information based on visual representations of objects (Ardilla et al., 1989; Kremin et al., 1991; Manly et al., 1999; Reis et al., 1994, 2001). Interestingly, literates’ and illiterates’ performances during picture naming are different especially when the visual configurations are two dimensional, contour based, and black and white (Reis et al., 1994, 2001, 2006). This suggests that the more the visual material implies a certain level of abstraction and symbolic representation (as in the case of letter strings), the stronger the effect of literacy on object recognition. Since reading represents a training in accessing linguistic information based on conventional visual representations, acquiring a new writing system would generally entrench the verbal decoding of graphic material. The effects of this training would not be restricted to letter strings but they could be generalized to those visual configurations that require a certain level of symbolism and conventional meaning (e.g., line drawings). This might explain why previous neuroimaging studies did not find strong brain changes with photographs and tridimensional representations (Dehaene et al., 2010; Pegado et al., 2014; see Reis et al., 1994 for similar null effects at the behavioral level). The present findings enable us to reconcile previous contrasting and challenging findings reported in object recognition literature. For instance, reading expertise can help to explain why object detection areas are highly heterogeneous and particularly difficult to be mapped in children (Gathers et al., 2004). Similarly, the different patterns of response lateralization so far reported in visual object detection (i.e., left-lateralized, Sergent et al., 1992; Dawson et al., 2002) might be accounted by differences in participants’ reading skills. Moreover, our findings on visual objects seem to be in line with recent data on visual categorization (Franklin et al., 2008). In a visual-half field study on color categorization, a stronger involvement of left hemisphere was reported in adult readers compared to infants (Franklin et al., 2008). Although further investigations are needed in order to better define the exact role of literacy on visual analysis, this might suggest that reading acquisition has an effect not only on the way people decode figurative representations but also on the way they discriminate and categorize visual input. Finally, the comparison between correlations of different cognitive domains showed that children’s brain responses to visual configurations (i.e., words and objects) are more related to reading performance as compared to auditory brain changes. This suggests that during the first two years of formal education, reading has a stronger impact on the visual domain as compared to the auditory domain (Dehaene et al., 2010, 2015). The present result does not seem to support theoretical models that assume the presence of phonological changes before being able to observe any visual improvement (Blomert, 2011). Reading-related phonological brain changes might be more evident later on or might involve specific auditory subprocesses that were not examined in the present study (such as phonological awareness, Castles and Coltheart, 2004). Additional investigation is needed in order to draw definitive conclusions on this issue.