Publications

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  • Udden, J., Hulten, A., Schoffelen, J.-M., Lam, N. H. L., Harbusch, K., Van den Bosch, A., Kempen, G., Petersson, K. M., & Hagoort, P. (2022). Supramodal sentence processing in the human brain: fMRI evidence for the influence of syntactic complexity in more than 200 participants. Neurobiology of Language, 3(4), 575-598. doi:10.1162/nol_a_00076.

    Abstract

    This study investigated two questions. One is: To what degree is sentence processing beyond single words independent of the input modality (speech vs. reading)? The second question is: Which parts of the network recruited by both modalities is sensitive to syntactic complexity? These questions were investigated by having more than 200 participants read or listen to well-formed sentences or series of unconnected words. A largely left-hemisphere frontotemporoparietal network was found to be supramodal in nature, i.e., independent of input modality. In addition, the left inferior frontal gyrus (LIFG) and the left posterior middle temporal gyrus (LpMTG) were most clearly associated with left-branching complexity. The left anterior temporal lobe (LaTL) showed the greatest sensitivity to sentences that differed in right-branching complexity. Moreover, activity in LIFG and LpMTG increased from sentence onset to end, in parallel with an increase of the left-branching complexity. While LIFG, bilateral anterior temporal lobe, posterior MTG, and left inferior parietal lobe (LIPL) all contribute to the supramodal unification processes, the results suggest that these regions differ in their respective contributions to syntactic complexity related processing. The consequences of these findings for neurobiological models of language processing are discussed.

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  • Araújo, S., Faísca, L., Bramão, I., Reis, A., & Petersson, K. M. (2015). Lexical and sublexical orthographic processing: An ERP study with skilled and dyslexic adult readers. Brain and Language, 141, 16-27. doi:10.1016/j.bandl.2014.11.007.

    Abstract

    This 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.
  • Araújo, S., Reis, A., Petersson, K. M., & Faísca, L. (2015). Rapid automatized naming and reading performance: A meta-analysis. Journal of Educational Psychology, 107(3), 868-883. doi:10.1037/edu0000006.

    Abstract

    Evidence that rapid naming skill is associated with reading ability has become increasingly prevalent in recent years. However, there is considerable variation in the literature concerning the magnitude of this relationship. The objective of the present study was to provide a comprehensive analysis of the evidence on the relationship between rapid automatized naming (RAN) and reading performance. To this end, we conducted a meta-analysis of the correlational relationship between these 2 constructs to (a) determine the overall strength of the RAN–reading association and (b) identify variables that systematically moderate this relationship. A random-effects model analysis of data from 137 studies (857 effect sizes; 28,826 participants) indicated a moderate-to-strong relationship between RAN and reading performance (r = .43, I2 = 68.40). Further analyses revealed that RAN contributes to the 4 measures of reading (word reading, text reading, non-word reading, and reading comprehension), but higher coefficients emerged in favor of real word reading and text reading. RAN stimulus type and type of reading score were the factors with the greatest moderator effect on the magnitude of the RAN–reading relationship. The consistency of orthography and the subjects’ grade level were also found to impact this relationship, although the effect was contingent on reading outcome. It was less evident whether the subjects’ reading proficiency played a role in the relationship. Implications for future studies are discussed.

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