Language Processing in Atypical Development: Looking Below the Surface with MEG

  • Maria ModyEmail author
Reference work entry


Neurodevelopmental disorders like dyslexia and autism have witnessed an explosion of research in recent years, leading to detailed characterization of these conditions and paving the way for the identification of phenotypes. Common to both these disorders is an impairment of the language system. Deficits in phonological processing have been the single most consistent finding in individuals with dyslexia, affecting the acquisition of reading skills. In contrast, children and adults with autism spectrum disorder (ASD) have difficulty using semantic information, evident in their idiosyncratic vocabulary and excessively literal interpretation of statements. However, as the term implies, ASD is associated with very heterogeneous profiles, and poor language may be related to a broader deficit in social reciprocity and motivation. Regardless, given the important prognostic value of early language abilities in later developmental outcomes, there has been a tremendous drive to better understand the neurobiological basis of language impairments in developmental disorders. Over the years, a growing appreciation of the workings of the human brain has pushed to the forefront noninvasive neuroimaging. Methods like electroencephalography (EEG) and magnetoencephalography (MEG) are providing useful insights into connectivity patterns in the brain by yielding information about temporal coupling in the millisecond time scale across brain regions and frequency bands of neural oscillations. The resulting “spectral-temporal-spatial” patterns of brain activity, characteristic of different cognitive processes, are providing meaningful probes for use in neuroscience and genetic studies toward an improved understanding, assessment, and treatment of developmental disorders.


Children Dyslexia Autism Language Phonology Semantics Speech perception Reading Magnetoencephalography Electroencephalography Event-related potentials Brain oscillations Magnetic resonance imaging Diffusion tensor imaging 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School and Massachusetts General HospitalCharlestownUSA

Section editors and affiliations

  • Julia M. Stephen
    • 1
  1. 1.The Mind Research NetworkAlbuquerqueUSA

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