Journal of Autism and Developmental Disorders

, Volume 49, Issue 8, pp 3181–3190 | Cite as

A Spectrotemporal Correlate of Language Impairment in Autism Spectrum Disorder

  • Luke BloyEmail author
  • Kobey Shwayder
  • Lisa Blaskey
  • Timothy P. L. Roberts
  • David Embick
Original Paper


This study introduces an objective neurophysiological marker of language ability, the integral of event-related desynchronization in the 5–20 Hz band during 0.2–1 seconds post auditory stimulation with interleaved word/non-word tokens. This measure correlates with clinical assessment of language function in both ASD and neurotypical pediatric populations. The measure does not appear related to general cognitive ability nor autism symptom severity (beyond degree of language impairment). We suggest that this oscillatory brain activity indexes lexical search and thus increases with increased search in the mental lexicon. While specificity for language impairment in ASD remains to be determined, such an objective index has potential utility in low functioning individuals with ASD and young children during language acquisition.


Language impairment Oscillation Lexical access Magnetoencephalography (MEG) 



We would like to the thank all of the participants and their families for their cooperation and for participating in this study. This work was supported in part by NIH R01DC008871 (TR), NIH R01HD073258 (DE), NIH K01MH108762 (LB) and NIH U54HD086984, the institutional IDDRC (TR directs the Neuroimaging Neurocircuitry Core).

Authors Contribution

LB, Ph.D. is a Research Scientist at the Lurie Family Foundations MEG Imaging Center at the Children’s Hospital of Philadelphia (CHOP). KS, Ph.D. is a Post-Doctoral Researcher in the Radiology Department at CHOP and a Visiting Scholar in the Department of Linguistics at the University of Pennsylvania. LB, PhD, is a pediatric neuropsychologist in the Department of Child and Adolescent Psychiatry and Behavioral Sciences, the Center for Autism Research, and the Autism Integrated Care Program at CHOP. TPLR, PhD, is a professor of Radiology, Vicechair of Research for the Department of Radiology and the Oberkircher Family Endowed Chair in Pediatric Radiology at CHOP. DE, Ph.D. is a professor and chair of the Department of Linguistics at the University of Pennsylvania.

Compliance with Ethical Standards

Conflict of interest

Dr. Roberts declares consulting agreements (medical advisory boards) with CTF MEG, Ricoh, Spago Nanomedicine, Avexis Inc. and Acadia Pharmaceuticals as well as intellectual property under licensing negotiation. Drs. Bloy, Shwayder, Blaskey and Embick declare no conflicts of interest.

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee, and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed Consent

Written informed consent was obtained from all participant’s families and each participant (when competent to do so) gave verbal assent to participate in the study.



Event related desynchrony—task related decreases in oscillatory power relative to baseline


Event related synchrony—task related increases in oscillatory power relative to baseline






Autism spectrum disorder


Typically developing


Prominent middle and late components of the auditory evoked field


Relating to the words or vocabulary

Theta Band

Oscillatory activity between 4 and 6 Hz

Alpha Band

Oscillatory activity between 8 and 12 Hz

Beta Band

Oscillatory activity between 13 and 30 Hz

Gamma Band

Oscillatory activity above 30 Hz (typically below 100 Hz)


Superior temporal gyrus


Calibrated severity score derived from the autism diagnostic observation schedule


Perceptual reasoning index from the wechsler intelligence scale for children-IV


Core language standard score from the clinical evaluation of language fundamentals


  1. American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Association.Google Scholar
  2. Avants, B. B., Tustison, N. J., Song, G., Cook, P. A., Klein, A., & Gee, J. C. (2011). A reproducible evaluation of ANTs similarity metric performance in brain image registration. Neuroimage, 54(3), 2033–2044.Google Scholar
  3. Baio, J., Wiggins, L., Christensen, D. L., Maenner, M. J., Daniels, J., Warren, Z., et al. (2018). Prevalence of autism spectrum disorder among children aged 8 years—autism and developmental disabilities monitoring network, 11 Sites, United States, 2014. MMWR Surveillance Summaries, 67(6), 1–23. Scholar
  4. Balota, D. A., Yap, M. J., Cortese, M. J., Hutchison, K. A., Kessler, B., Loftis, B., et al. (2007). The english lexicon project. Behavior Research Methods, 39(3), 445–459.Google Scholar
  5. Bastiaansen, M. C., Mazaheri, A., & Jensen, O. (2012). Beyond ERPs: Oscillatory neuronal dynamics The Oxford handbook of event-related potential components (pp. 31–49). New York, NY, USA: Oxford University Press.Google Scholar
  6. Bastiaansen, M. C., Oostenveld, R., Jensen, O., & Hagoort, P. (2008). I see what you mean: Theta power increases are involved in the retrieval of lexical semantic information. Brain and Language, 106(1), 15–28. Scholar
  7. Bastiaansen, M. C., van der Linden, M., Ter Keurs, M., Dijkstra, T., & Hagoort, P. (2005). Theta responses are involved in lexical-semantic retrieval during language processing. Journal of Cognitive Neuroscience, 17(3), 530–541. Scholar
  8. Bishop, D. V., Bishop, S. J., Bright, P., James, C., Delaney, T., & Tallal, P. (1999). Different origin of auditory and phonological processing problems in children with language impairment: Evidence from a twin study. Journal of Speech, Language, and Hearing Research, 42(1), 155–168.Google Scholar
  9. Bishop, D. V., North, T., & Donlan, C. (1996). Nonword repetition as a behavioural marker for inherited language impairment: Evidence from a twin study. Journal of Child Psychology and Psychiatry, 37(4), 391–403.Google Scholar
  10. Boersma, P., & Van Heuven, V. (2001). Speak and unSpeak with PRAAT. Glot International, 5(9/10), 341–347.Google Scholar
  11. Brennan, J., Lignos, C., Embick, D., & Roberts, T. P. (2014). Spectro-temporal correlates of lexical access during auditory lexical decision. Brain and Language, 133, 39–46. Scholar
  12. Constantino, J. N., & Gruber, C. (2012). The social responsiveness scale (SRS-2) (2nd ed.). Torrance, CA: Western Psychological Services.Google Scholar
  13. Edgar, J. C., Khan, S. Y., Blaskey, L., Chow, V. Y., Rey, M., Gaetz, W., et al. (2015). Neuromagnetic oscillations predict evoked-response latency delays and core language deficits in autism spectrum disorders. Journal of Autism and Developmental Disorders, 45(2), 395–405. Scholar
  14. Embick, D., Hackl, M., Schaeffer, J., Kelepir, M., & Marantz, A. (2001). A magnetoencephalographic component whose latency reflects lexical frequency. Cognitive Brain Research, 10(3), 345–348.Google Scholar
  15. Fischl, B. (2012). FreeSurfer. Neuroimage, 62(2), 774–781.Google Scholar
  16. Gage, N. M., Siegel, B., & Roberts, T. P. (2003). Cortical auditory system maturational abnormalities in children with autism disorder: An MEG investigation. Developmental Brain Research, 144(2), 201–209.Google Scholar
  17. Gallon, N., Harris, J., & van der Lely, H. (2007). Non-word repetition: An investigation of phonological complexity in children with Grammatical SLI. Clinical Linguistics & Phonetics, 21(6), 435–455. Scholar
  18. Gilhooly, K. J., & Logie, R. H. (1980). Age-of-acquisition, imagery, concreteness, familiarity, and ambiguity measures for 1,944 words. Behavior Research Methods & Instrumentation, 12(4), 395–427.Google Scholar
  19. Gotham, K., Pickles, A., & Lord, C. (2009). Standardizing ADOS scores for a measure of severity in autism spectrum disorders. Journal of Autism and Developmental Disorders, 39(5), 693–705. Scholar
  20. Gramfort, A., Luessi, M., Larson, E., Engemann, D. A., Strohmeier, D., Brodbeck, C., et al. (2014). MNE software for processing MEG and EEG data. Neuroimage, 86, 446–460.Google Scholar
  21. Gröchenig, K. (2013). Foundations of time-frequency analysis. Boston: Birkhäuser.Google Scholar
  22. Hämäläinen, M. S., & Ilmoniemi, R. J. (1994). Interpreting magnetic fields of the brain: Minimum norm estimates. Medical & Biological Engineering & Computing, 32(1), 35–42.Google Scholar
  23. Hickok, G., & Poeppel, D. (2000). Towards a functional neuroanatomy of speech perception. Trends in Cognitive Sciences, 4(4), 131–138.Google Scholar
  24. Kandel, E. R., Schwartz, J. H., & Jessel, T. M. (2000). Principles of neural science (4th ed.). New York: McGraw-Hill.Google Scholar
  25. Kikuchi, M., Yoshimura, Y., Mutou, K., & Minabe, Y. (2016). Magnetoencephalography in the study of children with autism spectrum disorder. Psychiatry and Clinical Neurosciences, 70(2), 74–88. Scholar
  26. Krause, C. M., Pesonen, M., & Hamalainen, H. (2007). Brain oscillatory responses during the different stages of an auditory memory search task in children. NeuroReport, 18(3), 213–216. Scholar
  27. Lord, C., Luyster, R. J., Gotham, K., & Guthrie, W. (2012). Autism diagnostic observation schedule (ADOS): Manual (2nd ed.). Torrance: Western Psychological Services.Google Scholar
  28. Matsuzaki, J., Kagitani-Shimono, K., Sugata, H., Hanaie, R., Nagatani, F., Yamamoto, T., et al. (2017). Delayed mismatch field latencies in autism spectrum disorder with abnormal auditory sensitivity: A magnetoencephalographic study. Frontiers in Human Neuroscience, 11, 446. Scholar
  29. McFadden, K. L., Hepburn, S., Winterrowd, E., Schmidt, G. L., & Rojas, D. C. (2012). Abnormalities in gamma-band responses to language stimuli in first-degree relatives of children with autism spectrum disorder: An MEG study. BMC Psychiatry, 12, 213. Scholar
  30. Mody, M., & Belliveau, J. W. (2013). Speech and language impairments in autism: Insights from behavior and neuroimaging. North American Journal of Medicine & Science, 5(3), 157–161.Google Scholar
  31. Murray, W. S., & Forster, K. I. (2004). Serial mechanisms in lexical access: The rank hypothesis. Psychological Review, 111(3), 721.Google Scholar
  32. Nelson, D. L., McEvoy, C. L., & Schreiber, T. A. (1998). The University of South Florida word association, rhyme, and word fragment norms. Retrieved from
  33. Nolan, H., Whelan, R., & Reilly, R. (2010). FASTER: Fully automated statistical thresholding for EEG artifact rejection. Journal of Neuroscience Methods, 192(1), 152–162.Google Scholar
  34. Oram Cardy, J. E., Ferrari, P., Flagg, E. J., Roberts, W., & Roberts, T. P. (2004). Prominence of M50 auditory evoked response over M100 in childhood and autism. NeuroReport, 15(12), 1867–1870.Google Scholar
  35. Oram Cardy, J. E., Flagg, E. J., Roberts, W., & Roberts, T. P. (2008). Auditory evoked fields predict language ability and impairment in children. International Journal of Psychophysiology, 68(2), 170–175. Scholar
  36. Pesonen, M., Bjornberg, C. H., Hamalainen, H., & Krause, C. M. (2006). Brain oscillatory 1–30 Hz EEG ERD/ERS responses during the different stages of an auditory memory search task. Neuroscience Letters, 399(1–2), 45–50. Scholar
  37. Port, R. G., Edgar, J. C., Ku, M., Bloy, L., Murray, R., Blaskey, L., et al. (2016). Maturation of auditory neural processes in autism spectrum disorder—A longitudinal MEG study. Neuroimage: Clinical, 11, 566–577. Scholar
  38. Pylkkanen, L., & Marantz, A. (2003). Tracking the time course of word recognition with MEG. Trends in Cognitive Sciences, 7(5), 187–189.Google Scholar
  39. Pylkkanen, L., Stringfellow, A., & Marantz, A. (2002). Neuromagnetic evidence for the timing of lexical activation: An MEG component sensitive to phonotactic probability but not to neighborhood density. Brain and Language, 81(1–3), 666–678.Google Scholar
  40. Roberts, T. P., Cannon, K. M., Tavabi, K., Blaskey, L., Khan, S. Y., Monroe, J. F., et al. (2011). Auditory magnetic mismatch field latency: A biomarker for language impairment in autism. Biological Psychiatry, 70(3), 263–269. Scholar
  41. Roberts, T. P., Khan, S. Y., Rey, M., Monroe, J. F., Cannon, K., Blaskey, L., et al. (2010). MEG detection of delayed auditory evoked responses in autism spectrum disorders: Towards an imaging biomarker for autism. Autism Research, 3(1), 8–18. Scholar
  42. Rojas, D. C., Teale, P. D., Maharajh, K., Kronberg, E., Youngpeter, K., Wilson, L. B., et al. (2011). Transient and steady-state auditory gamma-band responses in first-degree relatives of people with autism spectrum disorder. Molecular Autism, 2, 11. Scholar
  43. Rutter, M., Bailey, A., & Lord, C. (2003a). The social communication questionnaire: Manual. Los Angeles: Western Psychological Services.Google Scholar
  44. Rutter, M., Le Couteur, A., & Lord, C. (2003b). Autism diagnostic interview-revised (ADI–R) manual. Los Angeles: Western Psychological Services.Google Scholar
  45. Schwartz, S., Shinn-Cunningham, B., & Tager-Flusberg, H. (2018). Meta-analysis and systematic review of the literature characterizing auditory mismatch negativity in individuals with autism. Neuroscience and Biobehavioral Reviews, 87, 106–117. Scholar
  46. Semel, E., Wiig, E., & Secord, W. (2003). Clinical evaluation of language fundamentals (CELF-4). San Antonio, TX: The Psychological Corporation.Google Scholar
  47. Tager-Flusberg, H., Joseph, R., & Folstein, S. (2001). Current directions in research on autism. Mental Retardation and Developmental Disabilities Research Reviews, 7(1), 21–29.;2-3.Google Scholar
  48. Tager-Flusberg, H., & Kasari, C. (2013). Minimally verbal school-aged children with autism spectrum disorder: The neglected end of the spectrum. Autism Research, 6(6), 468–478. Scholar
  49. Tavabi, K., Embick, D., & Roberts, T. P. (2011). Spectral–temporal analysis of cortical oscillations during lexical processing. NeuroReport, 22(10), 474–478.Google Scholar
  50. Volden, J., Coolican, J., Garon, N., White, J., & Bryson, S. (2009). Brief report: Pragmatic language in autism spectrum disorder: Relationships to measures of ability and disability. Journal of Autism and Developmental Disorders, 39(2), 388–393. Scholar
  51. Wechsler, D. (2003). Wechsler intelligence scale for children-WISC-IV (4th ed.). San Antonio, TX: Psychological Corporation.Google Scholar
  52. Wilson, M. (1988). MRC psycholinguistic database: Machine-usable dictionary, version 2.00. Behavior Research Methods, Instruments, & Computers, 20(1), 6–10.Google Scholar
  53. Wilson, T. W., Rojas, D. C., Reite, M. L., Teale, P. D., & Rogers, S. J. (2007). Children and adolescents with autism exhibit reduced MEG steady-state gamma responses. Biological Psychiatry, 62(3), 192–197. Scholar
  54. Yoshimura, Y., Kikuchi, M., Shitamichi, K., Ueno, S., Munesue, T., Ono, Y., et al. (2013). Atypical brain lateralisation in the auditory cortex and language performance in 3- to 7-year-old children with high-functioning autism spectrum disorder: A child-customised magnetoencephalography (MEG) study. Molecular Autism, 4(1), 38. Scholar
  55. Young, E. C., Diehl, J. J., Morris, D., Hyman, S. L., & Bennetto, L. (2005). The use of two language tests to identify pragmatic language problems in children with autism spectrum disorders. Language, Speech, and Hearing Services in Schools, 36(1), 62–72.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Radiology, Lurie Family Foundations MEG Imaging CenterChildren’s Hospital of PhiladelphiaPhiladelphiaUSA
  2. 2.Department of LinguisticsUniversity of PennsylvaniaPhiladelphiaUSA

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