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Cited by 22Autism Spectrum Disorder ResearchGenetics and Neurodevelopmental DisordersHearing, Cochlea, Tinnitus, Genetics

Defining clusters of young autistic and typically developing children based on loudness-dependent auditory electrophysiological responses

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Dwyer, Patrick, Wang, Xiaodong, De Meo-Monteil, Rosanna, Hsieh, Fushing, Saron, Clifford D., Rivera, Susan M.·2020·Molecular Autism
DOI 10.1186/s13229-020-00352-3PMC PMC7294610

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Abstract

Background: Autistic individuals exhibit atypical patterns of sensory processing that are known to be related to quality of life, but which are also highly heterogeneous. Previous investigations of this heterogeneity have ordinarily used questionnaires and have rarely investigated sensory processing in typical development (TD) alongside autism spectrum development (ASD). Methods: The present study used hierarchical clustering in a large sample to identify subgroups of young autistic and typically developing children based on the normalized global field power (GFP) of their event-related potentials (ERPs) to auditory stimuli of four different loudness intensities (50, 60, 70, 80 dB SPL): that is, based on an index of the relative strengths of their neural responses across these loudness conditions. Results: Four clusters of participants were defined. Normalized GFP responses to sounds of different intensities differed strongly across clusters. There was considerable overlap in cluster assignments of autistic and typically developing participants, but autistic participants were more likely to display a pattern of relatively linear increases in response strength accompanied by a disproportionately strong response to 70 dB stimuli. Autistic participants displaying this pattern trended towards obtaining higher scores on assessments of cognitive abilities. There was also a trend for typically developing participants to disproportionately fall into a cluster characterized by disproportionately/nonlinearly strong 60 dB responses. Greater auditory distractibility was reported among autistic participants in a cluster characterized by disproportionately strong responses to the loudest (80 dB) sounds, and furthermore, relatively strong responses to loud sounds were correlated with auditory distractibility. This appears to provide evidence of coinciding behavioral and neural sensory atypicalities. Limitations: Replication may be needed to verify exploratory results. This analysis does not address variability related to classical ERP latencies and topographies. The sensory questionnaire employed was not specifically designed for use in autism. Hearing acuity was not measured. Variability in sensory responses unrelated to loudness is not addressed, leaving room for additional research. Conclusions: Taken together, these data demonstrate the broader benefits of using electrophysiology to explore individual differences. They illuminate different neural response patterns and suggest relationships between sensory neural responses and sensory behaviors, cognitive abilities, and autism diagnostic status.

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  • There was an overlap between ASD and TD participants in several clusters, suggesting that sensory impairments in ASD might be largely accounted for by wide interindividual variability within the spectrum.

    “However, there was an overlap between ASD and TD participants in several clusters (Dwyer et al. 2020, 2021), suggesting that sensory impairments in ASD might be largely accounted for the wide interindividual variability that exists within the spectrum.”

    From Autism Spectrum Disorder and auditory sensory alterations: a systematic review on the integrity of cognitive and neuronal functions related to auditory processing (2023) · cites this paper as Dwyer et al. 2020

    The Discussion (‘Overlap between diagnostic groups’; page not provided) reports that all clusters contained substantial numbers of both autistic and typically developing children. It interprets this as showing complexity in individual differences in auditory neural processing, but does not conclude that variability within ASD largely accounts for sensory impairments. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

  • A pattern of linear increases in response strength accompanied by a disproportionately strong response to 70 dB stimuli was found for ASD young children, correlated with auditory distractibility.

    “It was possible to verify a pattern of linear increases in response strength accompanied by a disproportionately strong response to 70 dB stimuli for ASD young children, correlated with auditory distractibility (Dwyer et al. 2020).”

    From Autism Spectrum Disorder and auditory sensory alterations: a systematic review on the integrity of cognitive and neuronal functions related to auditory processing (2023) · cites this paper as Dwyer et al. 2020

    The Results (Abstract; page unavailable) say autistic children were more likely to show the relatively linear response pattern with a disproportionately strong 70 dB response. The Results (Cluster-based permutation correlation analyses; page unavailable) also report a correlation between 70 dB response strength and auditory distractibility in autistic children. However, they do not establish that distractibility was associated with that specific linear, 70 dB–dominant cluster: the reported cluster-level association concerned a different cluster, characterized by a strong 80 dB response. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

  • Studies identifying data-driven subgroups of patients characterized by different EEG profiles, which appear associated with various clinical characteristics and different rates of treatment response, demonstrate this.

    “This is demonstrated by studies identifying data-driven subgroups of patients characterized by different EEG profiles, which appear associated with various clinical characteristics 75 and different rates of treatment response 76,77 .”

    From Candidate diagnostic biomarkers for neurodevelopmental disorders in children and adolescents: a systematic review (2023) · cites this paper as [75]

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  1. [2]American Psychiatric Association. Neurodevelopmental disorders. In: Diagnostic and statistical manual of mental disorders. 5th ed. 2013. 10.1176/appi.books.9780890425596.dsm01. · DOI
  2. [3]Robertson CE, Baron-Cohen S. Sensory perception in autism. Nat Rev Neurosci. 2017. 10.1038/nrn.2017.112. 28951611 · DOI · Paper page
  3. [5]Khalfa S, Bruneau N, Rogé B, Georgieff N, Veuillet E, Adrien J-L, et al. Increased perception of loudness in autism. Hear Res. 2004. 10.1016/j.heares.2004.07.006. 15617227 · DOI
  4. [6]Danesh AA, Lang D, Kaf W, Andreassen WD, Scott J, Eshraghi AA. Tinnitus and hyperacusis in autism spectrum disorders with emphasis on high functioning individuals diagnosed with Asperger’s Syndrome. Int J Pediatr Otorhinolaryngol. 2015. 10.1016/j.ijporl.2015.07.024. 26243502 · DOI
  5. [8]Wilson US, Sadler KM, Hancock KE, Guinan JJ, Lichtenhan JT. Efferent inhibition strength is a physiological correlate of hyperacusis in children with autism spectrum disorder. J Neurophysiol. 2017. 10.1016/j.ijporl.2015.07.024. PMC5547266 28592687 · DOI
  6. [9]Mostafa M Architecture for autism: Autism ASPECTSS(TM) in school design ArchNet iJAR Int J Archit Res. 2014 8 1 143 158 10.26687/archnet-ijar.v8i1.314 · DOI
  7. [10]Ismael N, Lawson LM, Hartwell J. Relationship between sensory processing and participation in daily occupations for children with autism spectrum disorder: A systematic review of studies that used Dunn’s sensory processing framework. Am J Occup Ther. 2018. 10.5014/ajot.2018.024075. 29689172 · DOI
  8. [11]Little LM, Ausderau K, Sideris J, Baranek GT. Activity participation and sensory features among children with autism spectrum disorders. J Autism Dev Disord. 2015. 10.1007/s10803-015-2460-3. PMC6452625 25975628 · DOI
  9. [12]Ausderau KK, Sideris J, Little LM, Furlong M, Bulluck JC, Baranek GT. Sensory subtypes and associated outcomes in children with autism spectrum disorders. Autism Res. 2016. 10.1002/aur.1626. 27135214 · DOI
  10. [14]Tomchek SD, Little LM, Dunn W. Sensory pattern contributions to developmental performance in children with autism spectrum disorder. Am J Occup Ther. 2015. 10.5014/ajot.2015.018044. 26356661 · DOI
  11. [15]Williams KL, Kirby AV, Watson LR, Sideris J, Bulluck J, Baranek GT. Sensory features as predictors of adaptive behaviors: A comparative longitudinal study of children with autism spectrum disorder and other developmental disabilities. Res Dev Disabil. 2018. 10.1016/j.ridd.2018.07.002. PMC7473611 30060977 · DOI
  12. [16]Ben-Sasson A, Cermak SA, Orsmond GI, Tager-Flusberg H, Kadlec MB, Carter AS. Sensory clusters of toddlers with autism spectrum disorders: Differences in affective symptoms. J Child Psychol Psychiatry Allied Discip. 2008. 10.1111/j.1469-7610.2008.01899.x. 18498344 · DOI
  13. [17]Green SA, Ben-Sasson A, Soto TW, Carter AS. Anxiety and sensory over-responsivity in toddlers with autism spectrum disorders: Bidirectional effects across time. J Autism Dev Disord. 2012. 10.1007/s10803-011-1361-3. PMC4199633 21935727 · DOI
  14. [20]Lin L-Y, Huang P-C. Quality of life and its related factors for adults with autism spectrum disorder. Disabil Rehabil. 2019. 10.1080/09638288.2017.1414887. 29228834 · DOI
  15. [21]Uljarević M, Baranek G, Vivanti G, Hedley D, Hudry K, Lane A. Heterogeneity of sensory features in autism spectrum disorder: Challenges and perspectives for future research. Autism Res. 2017. 10.1002/aur.1747. 28266796 · DOI · Paper page
  16. [24]Lesko A Grandin T Chapter 7: Anita Lesko Different…Not less: Inspiring stories of achievement and successful employment from adults with autism, Asperger’s, and ADHD 2012 Arlington Future Horizons 183 208
  17. [25]Robertson AE, Simmons DR. The sensory experiences of adults with autism spectrum disorder: A qualitative analysis. Perception. 2015. 10.1068/p7833. 26422904 · DOI
  18. [27]DeBoth KK, Reynolds S. A systematic review of sensory-based autism subtypes. Res Autism Spectr Disord. 2017. 10.1016/j.rasd.2017.01.005. · DOI
  19. [28]Keith JM, Jamieson JP, Bennetto L. The importance of adolescent self-report in autism spectrum disorder: Integration of questionnaire and autonomic measures. J Abnorm Child Psychol. 2019. 10.1007/s10802-018-0455-1. PMC6359986 30073571 · DOI
  20. [29]Carter Leno V, Chandler S, White P, Yorke I, Charman T, Pickles A, et al. Alterations in electrophysiological indices of perceptual processing and discrimination are associated with co-occurring emotional and behavioural problems in adolescents with autism spectrum disorder. Mol Autism. 2018. 10.1186/s13229-018-0236-2. PMC6173917 30323914 · DOI
  21. [31]Iwanami A, Okajima Y, Ota H, Tani M, Yamada T, Yamagata B, et al. P300 component of event-related potentials in persons with Asperger disorder. J Clin Neurophysiol. 2014. 10.1097/WNP.0000000000000080. 25271690 · DOI
  22. [33]Vlaskamp C, Oranje B, Madsen GF, Møllegaard Jepsen JR, Durston S, Cantio C, et al. Auditory processing in autism spectrum disorder: Mismatch negativity deficits. Autism Res. 2017. 10.1002/aur.1821. 28639417 · DOI
  23. [34]Weismüller B, Thienel R, Youlden AM, Fulham R, Koch M, Schall U. Psychophysiological correlates of developmental changes in healthy and autistic boys. J Autism Dev Disord. 2015. 10.1007/s10803-015-2385-x. 25663626 · DOI
  24. [35]Chien YL, Hsieh MH, Gau SSF. Mismatch negativity and P3a in adolescents and young adults with autism spectrum disorders: Behavioral correlates and clinical implications. J Autism Dev Disord. 2017. 10.1007/s10803-017-3426-4. 29198040 · DOI
  25. [36]Donkers FCL, Schipul SE, Baranek GT, Cleary KM, Willoughby MT, Evans AM, et al. Attenuated auditory event-related potentials and associations with atypical sensory response patterns in children with autism. J Autism Dev Disord. 2015. 10.1007/s10803-013-1948-y. PMC4556131 24072639 · DOI
  26. [38]Karhson DS, Golob EJ. Atypical sensory reactivity influences auditory attentional control in adults with autism spectrum disorders. Autism Res. 2016. 10.1002/aur.1593. 26778164 · DOI
  27. [39]Ludlow A, Mohr B, Whitmore A, Garagnani M, Pulvermüller F, Gutierrez R. Auditory processing and sensory behaviours in children with autism spectrum disorders as revealed by mismatch negativity. Brain Cogn. 2014. 10.1016/j.bandc.2014.01.016. 24565813 · DOI
  28. [40]Bruneau N, Bonnet-Brilhault F, Gomot M, Adrien JL, Barthélémy C. Cortical auditory processing and communication in children with autism: Electrophysiological/behavioral relations. Int J Psychophysiol. 2003. 10.1016/S0167-8760(03)00149-1. 14629919 · DOI · Paper page
  29. [41]Bruneau N, Roux S, Adrien JL, Barthélémy C. Auditory associative cortex dysfunction in children with autism: Evidence from late auditory evoked potentials (N1 wave-T complex). Clin Neurophysiol. 1999. 10.1016/S1388-2457(99)00149-2. 10576489 · DOI
  30. [42]De Meo-Monteil R, Nordahl CW, Amaral DG, Rogers SJ, Harootonian SK, Martin J, et al. Differential altered auditory event-related potential responses in young boys on the autism spectrum with and without disproportionate megalencephaly. Autism Res. 2019. 10.1002/aur.2137. PMC7282708 31157516 · DOI
  31. [43]Little LM, Dean E, Tomchek SD, Dunn W. Classifying sensory profiles of children in the general population. Child Care Health Dev. 2017. 10.1111/cch.12391. 27545764 · DOI
  32. [44]Elwin M, Schröder A, Ek L, Wallsten T, Kjellin L. Sensory clusters of adults with and without autism spectrum conditions. J Autism Dev Disord. 2017. 10.1007/s10803-016-2976-1. PMC5352790 27921201 · DOI
  33. [45]Buchsbaum M Schwartz GE Self-regulation of stimulus intensity: Augmenting/reducing and the average evoked response Consciousness and Self-Regulation: Advances in Research 1976 New York Plenum Press 101 135
  34. [46]Prescott J, Connolly JF, Gruzelier JH. The augmenting/reducing phenomenon in the auditory evoked potential. Biol Psychol. 1984. 10.1016/0301-0511(84)90008-5. 6478002 · DOI
  35. [47]Tlumak A, Durrant J, Delgado R. The effect of stimulus intensity and carrier frequency on auditory middle- and long-latency evoked potentials using a steady-state-response approach. Am J Audiol. 2016. 10.1044/2016_AJA-15-0061. 26999323 · DOI
  36. [48]Lane AE, Molloy CA, Bishop SL. Classification of children with autism spectrum disorder by sensory subtype: A case for sensory-based phenotypes. Autism Res. 2014. 10.1002/aur.1368. 24639147 · DOI
  37. [50]Lord C, Risi S, Linda L, Cook EH Jr, Leventhal BL, Di Lavore PC, et al. The Autism Diagnostic Observation Schedule - Generic: A standard measure of social and communication deficits associated with the spectrum of autism. J Autism Dev Disord.. 10.1023/A:1005592401947. 11055457 · DOI · Paper page
  38. [51]Lord C, Rutter M, Le Couteur A. Autism Diagnostic Interview-Revised: A revised version of a diagnostic interview for caregivers of individuals with possible pervasive developmental disorders. J Autism Dev Disord. 1994. 10.1007/BF02172145. 7814313 · DOI · Paper page
  39. [52]Libero LE, Nordahl CW, Li DD, Ferrer E, Rogers SJ, Amaral DG. Persistence of megalencephaly in a subgroup of young boys with autism spectrum disorder. Autism Res. 2016. 10.1002/aur.1643. PMC5292980 27273931 · DOI
  40. [53]Nordahl CW, Lange N, Li DD, Barnett LA, Lee A, Buonocore MH, et al. Brain enlargement is associated with regression in preschool-age boys with autism spectrum disorders. Proc Natl Acad Sci. 2011. 10.1073/pnas.1107560108. PMC3250128 22123952 · DOI
  41. [55]Sparrow SS, Cichetti DV, Balla DA. Vineland adaptive behavior scales. 2nd ed. Minneapolis, MN: NCS Pearson; 2005.
  42. [57]Hand BN, Dennis S, Lane AE. Latent constructs underlying sensory subtypes in children with autism: A preliminary study. Autism Res. 2017. 10.1002/aur.1787. PMC8040070 28371523 · DOI
  43. [59]Tomchek SD, Huebner RA, Dunn W. Patterns of sensory processing in children with an autism spectrum disorder. Res Autism Spectr Disord. 2014. 10.1007/s10803-006-0218-7. · DOI · Paper page
  44. [60]Williams ZJ, Failla MD, Gotham KO, Woynaroski TG, Cascio C. Psychometric evaluation of the Short Sensory Profile in youth with autism spectrum disorder. J Autism Dev Disord. 2018. 10.1007/s10803-018-3678-7. PMC6219913 30019274 · DOI
  45. [64]Belouchrani A, Abed-Meraim K, Cardoso J-F, Moulines E. A blind source separation technique using second-order statistics. IEEE Trans Signal Process. 1997. 10.1109/78.554307. · DOI
  46. [65]Tang AC, Sutherland MT, McKinney CJ. Validation of SOBI components from high-density EEG. Neuroimage. 2005. 10.1016/j.neuroimage.2004.11.027. 15784433 · DOI
  47. [67]Saggar M, King BG, Zanesco AP, MacLean KA, Aichele SR, Jacobs TL, et al. Intensive training induces longitudinal changes in meditation state-related EEG oscillatory activity. Front Hum Neurosci. 2012. 10.3389/fnhum.2012.00256. PMC3437523 22973218 · DOI · Paper page
  48. [68]Perrin F, Pernier J, Bertrand O, Giard M, Echallier J. Mapping of scalp potentials by surface spline interpolation. Electroencephalogr Clin Neurophysiol. 1987. 10.1016/0013-4694(87)90141-6. 2431869 · DOI
  49. [69]Brunet D, Murray MM, Michel CM. Spatiotemporal analysis of multichannel EEG: CARTOOL. Computational Intelligence and Neuroscience. 2011. 10.1155/2011/813870. PMC3022183 21253358 · DOI
  50. [70]Skrandies W. Global field power and topographic similarity. Brain Topogr. 1990. 10.1007/BF01128870. 2094301 · DOI · Paper page
  51. [71]Frodl T, Meisenzahl EM, Müller D, Leinsinger G, Juckel G, Hahn K, et al. The effect of the skull on event-related P300. Clin Neurophysiol. 2001. 10.1016/S1388-2457(01)00587-9. 11514260 · DOI
  52. [72]Čeponienė R, Rinne T, Näätänen R. Maturation of cortical sound processing as indexed by event-related potentials. Clin Neurophysiol. 2002. 10.1016/S1388-2457(02)00078-0. 12048046 · DOI
  53. [73]Shafer VL, Yu YH, Wagner M. Maturation of cortical auditory evoked potentials (CAEPs) to speech recorded from frontocentral and temporal sites: Three months to eight years of age. Int J Psychophysiol. 2015. 10.1016/j.ijpsycho.2014.08.1390. PMC4346437 25219893 · DOI
  54. [74]Ponton C, Eggermont J, Khosla D, Kwong B, Don M. Maturation of human central auditory system activity: Separating auditory evoked potentials by dipole source modeling. Clin Neurophysiol. 2002. 10.1016/S1388-2457(01)00733-7. 11897541 · DOI
  55. [75]Keuiper FK, Fisher L. A Monte Carlo comparison of six clustering procedures. Biometrics. 1975. 10.2307/2529565. · DOI
  56. [76]Mojena R. Hierarchical grouping methods and stopping rules: an evaluation. Comput J. 1977. 10.1093/comjnl/20.4.359. · DOI
  57. [77]de Amorim RC. Feature relevance in Ward’s hierarchical clustering using the Lp Norm. J Classif. 2015. 10.1007/s00357-015-9167-1. · DOI
  58. [78]Fushing H, McAssey MP. Time, temperature, and data cloud geometry. Phys Rev. 2010. 10.1103/PhysRevE.82.061110. 21230647 · DOI
  59. [79]Cliff N. Dominance statistics: ordinal analyses to answer ordinal questions. Quant Methods Psychol. 1993. 10.1037/0033-2909.114.3.494. · DOI
  60. [80]MacCallum RC, Zhang S, Preacher KJ, Rucker DD. On the practice of dichotomization of quantitative variables. Psychol Methods. 2002. 10.1037//1082-989X.7.1.19. 11928888 · DOI · Paper page
  61. [81]Maris E, Oostenveld R. Nonparametric statistical testing of EEG- and MEG-data. J Neurosci Methods. 2007. 10.1016/j.jneumeth.2007.03.024. 17517438 · DOI · Paper page
  62. [83]O’Neill BV, Croft RJ, Nathan PJ. The loudness dependence of the auditory evoked potential (LDAEP) as an in vivo biomarker of central serotonergic function in humans: Rationale, evaluation and review of findings. Hum Psychopharmacol. 2008. 10.1002/hup.940. 18421800 · DOI
  63. [84]Rubenstein JLR, Merzenich MM. Model of autism: increased ratio of excitation / inhibition in key neural systems. Brain. 2003. 10.1046/j.1601-183X.2003.00037.x. PMC6748642 14606691 · DOI
  64. [85]Sohal VS, Rubenstein JLR. Excitation-inhibition balance as a framework for investigating mechanisms in neuropsychiatric disorders. Mol Psychiatry. 2019. 10.1038/s41380-019-0426-0. PMC6742424 31089192 · DOI · Paper page
  65. [86]Ward J. Individual differences in sensory sensitivity: A synthesising framework and evidence from normal variation and developmental conditions. Cogn Neurosci. 2019. 10.1080/17588928.2018.1557131. 30526338 · DOI

Cited by

Sorted by citations

Authors
Dwyer, P., Wang, X., De Meo-Monteil, R., Hsieh, F., Saron, C. D., & Rivera, S. M.
Affiliations
University of California, Davis (US)
Corresponding author
Dwyer, Patrick
ORCID
Venue
Molecular Autism
Publisher
Springer Science and Business Media LLC
Published
2020-06-15
Volume
11
Issue
1
Pages
48-48
ISSN
2040-2392 (ISSN-L)
DOI
10.1186/s13229-020-00352-3
PMC
PMC7294610
OpenAlex
W3035007273
Cited by
22
References
14
Citations by year
2025: 1 · 2024: 6 · 2023: 6 · 2022: 5 · 2021: 3 · 2020: 1
FWCI
2.02
Type
journal article
Language
en
Open access
Licence
Locations
  • Molecular Autism (publishedVersion, cc-by)
  • Research Square (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • eScholarship (California Digital Library) (submittedVersion)
Funders
  • MIND Institute, University of California, Davis
  • University of California, Davis (Deans’ Distinguished Graduate Fellowship)
  • National Institutes of Health (1R01 MH089626-01)
  • Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (P2LAP3_164911)
  • National Institute of Mental Health (U24MH081810)
  • Eunice Kennedy Shriver National Institute of Child Health and Human Development (P50 HD093079)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
  • Life Sciences › Neuroscience › Sensory Systems › Hearing, Cochlea, Tinnitus, Genetics
Keywords
autism spectrum disorder, sensory processing, auditory electrophysiology, event-related potentials, global field power, typically developing children, individual differences, cognitive ability, hierarchical clustering
MeSH terms
Autism Spectrum Disorder, Acoustic Stimulation, Adaptation, Psychological, Auditory Perception, Cognition, Electroencephalography, Evoked Potentials, Auditory, Female, Humans, Male, Quality of Life, Surveys and Questionnaires, Cluster Analysis, Caregivers, Genes, Reporter, Electrophysiological Phenomena, Self Report, Symptom Assessment

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