No abstract

In this study, event related potentials (ERPs) were used to investigate the extent to which dyslexics (aged 9-13 years) differ from normally reading controls in early ERPs, which reflect prelexical orthographic processing, and in late ERPs, which reflect implicit phonological processing. The participants performed an implicit reading task, which was manipulated in terms of letter-specific processing, orthographic familiarity, and phonological structure. Comparing consonant- and symbol sequences, the results showed significant differences in the P1 and N1 waveforms in the control but not in the dyslexic group. The reduced P1 and N1 effects in pre-adolescent children with dyslexia suggest a lack of visual specialization for letter-processing. The P1 and N1 components were not sensitive to the familiar vs. less familiar orthographic sequence contrast. The amplitude of the later N320 component was larger for phonologically legal (pseudowords) compared to illegal (consonant sequences) items in both controls and dyslexics. However, the topographic differences showed that the controls were more left-lateralized than the dyslexics. We suggest that the development of the mechanisms that support literacy skills in dyslexics is both delayed and follows a non-normal developmental path. This contributes to the hemispheric differences observed and might reflect a compensatory mechanism in dyslexics.

a b s t r a c tThis ERP study investigated the cognitive nature of the P1-N1 components during orthographic processing. We used an implicit reading task with various types of stimuli involving different amounts of sublexical or lexical orthographic processing (words, pseudohomophones, pseudowords, nonwords, and symbols), and tested average and dyslexic readers. An orthographic regularity effect (pseudowords-nonwords contrast) was observed in the average but not in the dyslexic group. This suggests an early sensitivity to the dependencies among letters in word-forms that reflect orthographic structure, while the dyslexic brain apparently fails to be appropriately sensitive to these complex features. Moreover, in the adults the N1-response may already reflect lexical access: (i) the N1 was sensitive to the familiar vs. less familiar orthographic sequence contrast; (ii) and early effects of the phonological form (words-pseudohomophones contrast) were also found. Finally, the later N320 component was attenuated in the dyslexics, suggesting suboptimal processing in later stages of phonological analysis.

To clarify whether the neural pathways concerning color processing are the same for natural objects, for artifacts objects and for non-objects we examined brain responses measured with functional magnetic resonance imaging (FMRI) during a covert naming task including the factors color (color vs. black&white (B&W)) and stimulus type (natural vs. artifacts vs. non-objects). Our results indicate that the superior parietal lobule and precuneus (BA 7) bilaterally, the right hippocampus and the right fusifom gyrus (V4) make part of a network responsible for color processing both for natural objects and artifacts, but not for non-objects. When color objects (both natural and artifacts) were contrasted with color non-objects we observed activations in the right parahippocampal gyrus (BA 35/36), the superior parietal lobule (BA 7) bilaterally, the left inferior middle temporal region (BA 20/21) and the inferior and superior frontal regions (BA 10/11/47). These additional activations suggest that colored objects recruit brain regions that are related to visual semantic information/retrieval and brain regions related to visuo-spatial processing. Overall, the results suggest that color information is an attribute that can improve object recognition (behavioral results) and activate a specific neural network related to visual semantic information that is more extensive than for B&W objects during object recognition.

No abstract

In this study, we used event-related potentials (ERPs) to evaluate the contribution of surface color and color knowledge information in object identification. We constructed two color-object verification tasks - a surface and a knowledge verification task - using high color diagnostic objects; both typical and atypical color versions of the same object were presented. Continuous electroencephalogram was recorded from 26 subjects. A cluster randomization procedure was used to explore the differences between typical and atypical color objects in each task. In the color knowledge task, we found two significant clusters that were consistent with the N350 and late positive complex (LPC) effects. Atypical color objects elicited more negative ERPs compared to typical color objects. The color effect found in the N350 time window suggests that surface color is an important cue that facilitates the selection of a stored object representation from long-term memory. Moreover, the observed LPC effect suggests that surface color activates associated semantic knowledge about the object, including color knowledge representations. We did not find any significant differences between typical and atypical color objects in the surface color verification task, which indicates that there is little contribution of color knowledge to resolve the surface color verification. Our main results suggest that surface color is an important visual cue that triggers color knowledge, thereby facilitating object identification.

In this study, we investigated the level of visual processing at which surface color information improves the recognition of color diagnostic and non-color diagnostic objects. Continuous electroencephalograms were recorded while participants performed a visual object naming task in which colored and black-and-white versions of both types of objects were presented. The blackand-white and the color presentations were compared in two groups of event-related potentials (ERPs): (1) the P1 and N1 components, indexing early visual processing; and (2) the N400 component, which index late visual processing. A color effect was observed in the P1 and N1 components, for both color and non-color diagnostic objects. In addition, for color diagnostic objects, a color effect was observed in the N400 component. These results suggest that color information is important for the recognition of color and non-color diagnostic objects at different levels of visual processing. It thus appears that the visual system uses color information, during recognition of both object types, at early visual stages; however for the color diagnostic objects recognition, color information is also recruited during the late visual processing stages. ACKNOWLEDGMENTS

This study investigates the implicit sequence learning abilities of dyslexic children using an artificial grammar learning task with an extended exposure period. Twenty children with developmental dyslexia participated in the study and were matched with two control groups-one matched for age and other for reading skills. During 3 days, all participants performed an acquisition task, where they were exposed to colored geometrical forms sequences with an underlying grammatical structure. On the last day, after the acquisition task, participants were tested in a grammaticality classification task. Implicit sequence learning was present in dyslexic children, as well as in both control groups, and no differences between groups were observed. These results suggest that implicit learning deficits per se cannot explain the characteristic reading difficulties of the dyslexics.