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Morphological awareness, or sensitivity to units of meaning in language, is an essential component of learning to read. It is easier to read long, polysyllabic words such as un-help-ful if one can also recognize their morphemic components. In dyslexia remediation, morphemic instruction is thought to bolster word reading mechanisms to compensate for phonological difficulties (Goodwin & Ahn, 2010). Yet, how the mechanisms underlying morphological processing may differ in dyslexia remains generally unknown. This study addresses this gap by examining the neurocognitive mechanisms underlying morphological processing in typical readers and readers with dyslexia.
Children with dyslexia (N=25, mean age=9.77) and a younger group of typically developing children matched on word reading skill (N=25, mean age=7.46) completed an auditory derivational (friend-LY) and root compound (snow-MAN) morphology task during fNIRS neuroimaging, along with standardized literacy assessments.
Aligned with prior work (Marks et al., 2021), typical readers demonstrated greater activation for derivational processing in temporal and parietal regions associated with integrating units of sound, meaning, and print. However, the pattern was strikingly different among impaired readers. Children with dyslexia exhibited reduced activation during derivational morphology, and stronger temporal activation in regions associated with meaning processing during compound morphology. In other words, while children with dyslexia fail to engage key language regions of the brain when manipulating fine-grained derivational affixes, they demonstrate robust activation for larger, more concrete semantic units. These findings are aligned with theories that lexico-semantic processes may serve as a compensatory mechanism for word analyses in dyslexia, advancing our understanding of reading impairment and neuro-cognitive mechanisms for learning to read.
Rachel Eggleston, University of Michigan - Ann Arbor
Presenting Author
Rebecca Marks, University of Michigan - Ann Arbor
Xin Sun, University of British Columbia (UBC)
Chi-Lin Yu, University of Michigan - Ann Arbor
Kehui Zhang, University of Michigan
Nia Nickerson, University of Michigan - Ann Arbor
Xiaosu Hu, University of Michigan
Ioulia Kovelman, University of Michigan - Ann Arbor