It has been suggested that there is a close relationship between visual attention span (VAS) and fluent reading. This relation may be modulated by participants’ age, and exhibits various patterns in different reading modes (i.e. oral v.s. silent reading) and different reading levels (e.g. sentence v.s. character/word levels). Moreover, the modulation effects from the above factors might be more remarkable in the framework of languages with a deep orthography. Therefore, the present study investigated the developmental pattern of the relationship between (...) VAS skills and reading fluency in Chinese, a language with particularly deep orthography, by recruiting 292 participants from primary schools, middle schools and universities. Two tests were utilized to assess fluent reading skills at the single-character and sentence levels with oral and silent reading modes. A visual 1-back task was adopted to reflect VAS capacity with non-verbal stimuli and no verbal response. Results showed that the VAS capacity of low-grade primary school students could significantly account for the variance in single-character reading fluency in the oral mode and that it was a significant predictor of sentence reading fluency in the oral mode among high-grade primary school students. VAS abilities of middle school students allowed a unique and stable prediction of their silent sentence reading. With increasing reading ability, VAS skills of adults showed significant and similar predictive power for estimating the variations in fluent sentence reading in both silent and oral modes. These results revealed developmental changes in the contribution of VAS to fluent reading in Chinese, and provided evidence unveiling whether the underlying mechanisms of oral and silent reading were shared or different. (shrink)

Dual task is known to affect postural stabilty in children. We explored the effect of visual tasks on postural control in dyslexic and in age-matched non-dyslexic children. Thirty dyslexic children (mean age: 9.80 ± 0.28 years) were compared with thirty non-dyslexic children (mean age: 9.92 ± 0.35 years). All children underwent ophthalmologic and optometric evaluation. Eye movements were recorded by a video-oculography system (EyeBrain ® T2) and postural sway was recorded simultaneously by a force platform (TechnoConept®). Both groups of children (...) performed fixations, pursuits, pro- and anti-saccades tasks. Dyslexic children showed significantly poor near fusional vergence ranges (convergence and divergence) with respect to the non-dyslexic children. During the postural task, quality of fixation and anti-saccade performance in dyslexic children were significantly worse compared to non-dyslexic children. In contrast, the number of catch-up saccades during pursuits and the latency of pro-and anti-saccades were similar in both groups of children examined. Concerning postural quality, dyslexic children were more unstable than age-matched non-dyslexic children. For both groups of children tested we also observed that executing saccades (pro- and anti-saccades) reduced postural values significantly in comparison with fixation and pursuit tasks. The impairment in convergence and divergence fusional capabilities could be due to an immaturity in cortical structures controlling the vergence system. The poor oculomotor performance reported in dyslexic children suggested a deficit in allocating visual attention and their postural instability observed is in line with the cerebellar impairment previously reported in dyslexic children. Finally, pro- or anti-saccades reduce postural values compared to fixation and pursuit tasks in both groups of children tested, suggesting a different influence of visual tasks on postural control according to their attentional demand. (shrink)

Although developmental dyslexia (DD) is frequently associate to a phonological deficit, the underlying neurobiological cause remain undetermined. One prominent hypothesis suggests a specific deficit in magnocellular-dorsal (M-D) pathway. Here we investigated the visual M-D and parvocellular-ventral (P-V) pathway in dyslexic and in chronological age and IQ-matched normally reading children by measuring dynamic (frequency doubling illusion) and static stimuli sensibility, respectively. A specific deficit in M-D task was found. Importantly, the M-D deficit was selectively shown in poor phonological decoders. M-D deficit (...) appears to be frequent because 75% of poor pseudo-word readers were at least 1 SD below the mean of the controls. Finally, a replication study by using a new group of poor phonological decoders and reading level controls suggests a possible role of M-D deficit in DD. These results showed that a M-D deficit might impair the sub-lexical mechanisms that are critical for reading development. The possible link between these findings and the oscillatory “temporal sampling” framework is discussed. (shrink)

This study was aimed at predicting individual differences in text reading fluency. The basic proposal included two factors, i.e., the ability to decode letter strings (measured by discrete pseudo-word reading) and integration of the various sub-components involved in reading (measured by Rapid Automatized Naming, RAN). Subsequently, a third factor was added to the model, i.e., naming of discrete digits. In order to use homogeneous measures, all contributing variables considered the entire processing of the item, including pronunciation time. The model, which (...) was based on commonality analysis, was applied to data from a group of 43 typically developing readers (11- to 13-year-olds) and a group of 25 chronologically matched dyslexic children. In typically developing readers, both orthographic decoding and integration of reading sub-components contributed significantly to the overall prediction of text reading fluency. The model prediction was higher (from ca. 37% to 52% of the explained variance) when we included the naming of discrete digits variable, which had a suppressive effect on pseudo-word reading. In the dyslexic readers, the variance explained by the two-factor model was high (69%) and did not change when the third factor was added. The lack of a suppression effect was likely due to the prominent individual differences in poor orthographic decoding of the dyslexic children. Analyses on data from both groups of children were replicated by using patches of colours as stimuli (both in the RAN task and in the discrete naming task) obtaining similar results. We conclude that it is possible to predict much of the variance in text-reading fluency using basic processes, such as orthographic decoding and integration of reading sub-components, even without taking into consideration higher-order linguistic factors such as lexical, semantic and contextual abilities. The approach validity of using proximal vs distal causes to predict reading fluency is discussed. (shrink)