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Arutiunian V, Buyanova I, Minnigulova A, Davydova E, Pereverzeva D, Sorokin A, Tyushkevich S, Mamokhina U, Danilina K, Dragoy O. Left-hemispheric atypicalities in the primary auditory cortex are associated with language comprehension and social skills in children with Autism Spectrum Disorder. Cereb Cortex 2025; 35:bhaf055. [PMID: 40083153 DOI: 10.1093/cercor/bhaf055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2024] [Revised: 02/14/2025] [Accepted: 02/19/2025] [Indexed: 03/16/2025] Open
Abstract
Low-level auditory processing difficulties have been previously reported in children with Autism Spectrum Disorder (ASD), and some studies showed the relationship between these difficulties in the primary auditory cortex and language impairment in ASD. However, there is still a limited number of studies that comprehensively assess (i) amplitudes, latencies, and sensory gating effects in all early components of auditory processing (M50-M100-M200 complex) at the source level in magnetoencephalography with their relation to structural anatomy (gray matter volume, thickness, gyrification) (ii) and the association between brain metrics and clinical phenotype in the same group of children. To address this question, we used a standard paired-clicks paradigm in magnetoencephalography and brain morphometry analysis in children with and without ASD (NASD = 20, NTD = 20). First, the results revealed a reduction of M200 and altered M200 sensory gating effect in the left auditory cortex in children with ASD. Second, these alterations were related to lower language comprehension skills and higher autistic symptom severity. Finally, altered MEG responses were associated with gray matter thickness reduction as well as abnormal gyrification in the primary auditory cortex in ASD. The study revealed low-level functional and structural atypicalities in children with ASD and their relation to clinical phenotype.
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Affiliation(s)
- Vardan Arutiunian
- Center for Child Health, Behavior and Development, Seattle Children's Research Institute, 1920 Terry Avenue, Seattle, WA 98101, United States
| | - Irina Buyanova
- Center for Language and Brain, HSE University, Krivokolenny pereulok, 3, Moscow 101000, Russia
- University of Otago, 362 Leith Street, Dunedin North, Dunedin 9016, New Zealand
| | - Alina Minnigulova
- Center for Language and Brain, HSE University, Krivokolenny pereulok, 3, Moscow 101000, Russia
| | - Elizaveta Davydova
- Federal Resource Center for ASD, Moscow State University of Psychology and Education, Ulitsa Kashenkin Lug, 7, Moscow 127427, Russia
- Chair of Differential Psychology and Psychophysiology, Moscow State University of Psychology and Education, Shelepikhinskaya Naberezhnaya, 2А, Moscow 123290, Russia
| | - Darya Pereverzeva
- Federal Resource Center for ASD, Moscow State University of Psychology and Education, Ulitsa Kashenkin Lug, 7, Moscow 127427, Russia
| | - Alexander Sorokin
- Federal Resource Center for ASD, Moscow State University of Psychology and Education, Ulitsa Kashenkin Lug, 7, Moscow 127427, Russia
- Haskins Laboratories, 300 George Street, Suite 900, New Haven, CT 06511, United States
| | - Svetlana Tyushkevich
- Federal Resource Center for ASD, Moscow State University of Psychology and Education, Ulitsa Kashenkin Lug, 7, Moscow 127427, Russia
| | - Uliana Mamokhina
- Federal Resource Center for ASD, Moscow State University of Psychology and Education, Ulitsa Kashenkin Lug, 7, Moscow 127427, Russia
| | - Kamilla Danilina
- Federal Resource Center for ASD, Moscow State University of Psychology and Education, Ulitsa Kashenkin Lug, 7, Moscow 127427, Russia
- Scientific Research and Practical Center of Pediatric Psychoneurology, Michurinskiy Prospekt, 74, Moscow 119602, Russia
| | - Olga Dragoy
- Center for Language and Brain, HSE University, Krivokolenny pereulok, 3, Moscow 101000, Russia
- Institute of Linguistics, Russian Academy of Sciences, Bolshoy Kislovsky Ln, 1, Moscow 125009, Russia
- Center for Language and Brain, HSE University, Saint Petersburg, Russia
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Dmytriw AA, Hadjinicolaou A, Ntolkeras G, Tamilia E, Pesce M, Berto LF, Grant PE, Pang E, Ahtam B. Magnetoencephalography for the pediatric population, indications, acquisition and interpretation for the clinician. Neuroradiol J 2025; 38:7-20. [PMID: 38864180 PMCID: PMC11571317 DOI: 10.1177/19714009241260801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/13/2024] Open
Abstract
Magnetoencephalography (MEG) is an imaging technique that enables the assessment of cortical activity via direct measures of neurophysiology. It is a non-invasive and passive technique that is completely painless. MEG has gained increasing prominence in the field of pediatric neuroimaging. This dedicated review article for the pediatric population summarizes the fundamental technical and clinical aspects of MEG for the clinician. We discuss methods tailored for children to improve data quality, including child-friendly MEG facility environments and strategies to mitigate motion artifacts. We provide an in-depth overview on accurate localization of neural sources and different analysis methods, as well as data interpretation. The contemporary platforms and approaches of two quaternary pediatric referral centers are illustrated, shedding light on practical implementations in clinical settings. Finally, we describe the expanding clinical applications of MEG, including its pivotal role in presurgical evaluation of epilepsy patients, presurgical mapping of eloquent cortices (somatosensory and motor cortices, visual and auditory cortices, lateralization of language), its emerging relevance in autism spectrum disorder research and potential future clinical applications, and its utility in assessing mild traumatic brain injury. In conclusion, this review serves as a comprehensive resource of clinicians as well as researchers, offering insights into the evolving landscape of pediatric MEG. It discusses the importance of technical advancements, data acquisition strategies, and expanding clinical applications in harnessing the full potential of MEG to study neurological conditions in the pediatric population.
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Affiliation(s)
- Adam A. Dmytriw
- Department of Radiology, Boston Children’s Hospital, Boston, MA, USA
- Division of Neuroradiology, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
| | - Aristides Hadjinicolaou
- Division of Neurology, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
- Department of Neurology, Division of Epilepsy and Clinical Neurophysiology, Boston Children’s Hospital, Boston, MA, USA
| | - Georgios Ntolkeras
- Department of Pediatrics, Division of Newborn Medicine, Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children’s Hospital, Boston, MA, USA
| | - Eleonora Tamilia
- Department of Pediatrics, Division of Newborn Medicine, Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children’s Hospital, Boston, MA, USA
| | - Matthew Pesce
- Department of Pediatrics, Division of Newborn Medicine, Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children’s Hospital, Boston, MA, USA
| | - Laura F. Berto
- Department of Pediatrics, Division of Newborn Medicine, Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children’s Hospital, Boston, MA, USA
| | - P. Ellen Grant
- Department of Radiology, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Division of Newborn Medicine, Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children’s Hospital, Boston, MA, USA
| | - Elizabeth Pang
- Division of Neurology, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
| | - Banu Ahtam
- Department of Pediatrics, Division of Newborn Medicine, Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children’s Hospital, Boston, MA, USA
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Taddei M, Cuesta P, Annunziata S, Bulgheroni S, Esposito S, Visani E, Granvillano A, Dotta S, Rossi DS, Panzica F, Franceschetti S, Varotto G, Riva D. Correlation between autistic traits and brain functional connectivity in preschoolers with autism spectrum disorder: a resting state MEG study. Neurol Sci 2024; 45:4549-4561. [PMID: 38639894 DOI: 10.1007/s10072-024-07528-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 04/09/2024] [Indexed: 04/20/2024]
Abstract
BACKGROUND Neurophysiological studies recognized that Autism Spectrum Disorder (ASD) is associated with altered patterns of over- and under-connectivity. However, little is known about network organization in children with ASD in the early phases of development and its correlation with the severity of core autistic features. METHODS The present study aimed at investigating the association between brain connectivity derived from MEG signals and severity of ASD traits measured with different diagnostic clinical scales, in a sample of 16 children with ASD aged 2 to 6 years. RESULTS A significant correlation emerged between connectivity strength in cortical brain areas implicated in several resting state networks (Default mode, Central executive, Salience, Visual and Sensorimotor) and the severity of communication anomalies, social interaction problems, social affect problems, and repetitive behaviors. Seed analysis revealed that this pattern of correlation was mainly caused by global rather than local effects. CONCLUSIONS The present evidence suggests that altered connectivity strength in several resting state networks is related to clinical features and may contribute to neurofunctional correlates of ASD. Future studies implementing the same method on a wider and stratified sample may further support functional connectivity as a possible biomarker of the condition.
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Affiliation(s)
- Matilde Taddei
- Unit for Neurogenetic Syndromes With Intellectual Disabilities and Autism Spectrum Disorders, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy
| | - Pablo Cuesta
- Department of Radiology, Rehabilitation, and Physiotherapy, Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid, Spain
| | - Silvia Annunziata
- Unit for Neurogenetic Syndromes With Intellectual Disabilities and Autism Spectrum Disorders, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy
- Fondazione Don Carlo Gnocchi Onlus-IRCCS S. Maria Nascente, Via Capecelatro 66, 20148, Milan, Italy
| | - Sara Bulgheroni
- Unit for Neurogenetic Syndromes With Intellectual Disabilities and Autism Spectrum Disorders, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy
| | - Silvia Esposito
- Unit for Neurogenetic Syndromes With Intellectual Disabilities and Autism Spectrum Disorders, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy
| | - Elisa Visani
- Neurophysiopathology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy
| | - Alice Granvillano
- Neurophysiopathology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy
| | - Sara Dotta
- Neurophysiopathology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy
| | - Davide Sebastiano Rossi
- Neurophysiopathology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy
| | - Ferruccio Panzica
- Clinical Engineering Service, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Silvana Franceschetti
- Neurophysiopathology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy
| | - Giulia Varotto
- Neurophysiopathology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy.
- Epilepsy Unit, Bioengineering Group, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy.
- Laboratory for Clinical Neuroscience, Center for Biomedical Technology, University Politécnica de Madrid, Madrid, Spain.
| | - Daria Riva
- Unit for Neurogenetic Syndromes With Intellectual Disabilities and Autism Spectrum Disorders, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy
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Ahlfors SP, Graham S, Bharadwaj H, Mamashli F, Khan S, Joseph RM, Losh A, Pawlyszyn S, McGuiggan NM, Vangel M, Hämäläinen MS, Kenet T. No Differences in Auditory Steady-State Responses in Children with Autism Spectrum Disorder and Typically Developing Children. J Autism Dev Disord 2024; 54:1947-1960. [PMID: 36932270 PMCID: PMC11463296 DOI: 10.1007/s10803-023-05907-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/23/2022] [Indexed: 03/19/2023]
Abstract
Auditory steady-state response (ASSR) has been studied as a potential biomarker for abnormal auditory sensory processing in autism spectrum disorder (ASD), with mixed results. Motivated by prior somatosensory findings of group differences in inter-trial coherence (ITC) between ASD and typically developing (TD) individuals at twice the steady-state stimulation frequency, we examined ASSR at 25 and 50 as well as 43 and 86 Hz in response to 25-Hz and 43-Hz auditory stimuli, respectively, using magnetoencephalography. Data were recorded from 22 ASD and 31 TD children, ages 6-17 years. ITC measures showed prominent ASSRs at the stimulation and double frequencies, without significant group differences. These results do not support ASSR as a robust ASD biomarker of abnormal auditory processing in ASD. Furthermore, the previously observed atypical double-frequency somatosensory response in ASD did not generalize to the auditory modality. Thus, the hypothesis about modality-independent abnormal local connectivity in ASD was not supported.
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Affiliation(s)
- Seppo P Ahlfors
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.
- Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA.
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 13th Street, Rm. 2301, Charlestown, MA, 02129, USA.
| | - Steven Graham
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
| | - Hari Bharadwaj
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
- Department of Speech, Language, and Hearing Sciences, Boston University, Boston, MA, USA
- Department of Speech, Language, & Hearing Sciences and Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, USA
| | - Fahimeh Mamashli
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
| | - Sheraz Khan
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
| | - Robert M Joseph
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA
| | - Ainsley Losh
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
| | - Stephanie Pawlyszyn
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
| | - Nicole M McGuiggan
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
| | - Mark Vangel
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
| | - Matti S Hämäläinen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
| | - Tal Kenet
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
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5
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Demopoulos C, Jesson X, Gerdes MR, Jurigova BG, Hinkley LB, Ranasinghe KG, Desai S, Honma S, Mizuiri D, Findlay A, Nagarajan SS, Marco EJ. Global MEG Resting State Functional Connectivity in Children with Autism and Sensory Processing Dysfunction. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.26.577499. [PMID: 38352614 PMCID: PMC10862722 DOI: 10.1101/2024.01.26.577499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
Sensory processing dysfunction not only affects most individuals with autism spectrum disorder (ASD), but at least 5% of children without ASD also experience dysfunctional sensory processing. Our understanding of the relationship between sensory dysfunction and resting state brain activity is still emerging. This study compared long-range resting state functional connectivity of neural oscillatory behavior in children aged 8-12 years with autism spectrum disorder (ASD; N=18), those with sensory processing dysfunction (SPD; N=18) who do not meet ASD criteria, and typically developing control participants (TDC; N=24) using magnetoencephalography (MEG). Functional connectivity analyses were performed in the alpha and beta frequency bands, which are known to be implicated in sensory information processing. Group differences in functional connectivity and associations between sensory abilities and functional connectivity were examined. Distinct patterns of functional connectivity differences between ASD and SPD groups were found only in the beta band, but not in the alpha band. In both alpha and beta bands, ASD and SPD cohorts differed from the TDC cohort. Somatosensory cortical beta-band functional connectivity was associated with tactile processing abilities, while higher-order auditory cortical alpha-band functional connectivity was associated with auditory processing abilities. These findings demonstrate distinct long-range neural synchrony alterations in SPD and ASD that are associated with sensory processing abilities. Neural synchrony measures could serve as potential sensitive biomarkers for ASD and SPD.
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Affiliation(s)
- Carly Demopoulos
- Department of Psychiatry, University of California San Francisco, 675 18 Street, San Francisco, CA 94107
- Department of Radiology & Biomedical Imaging, University of California-San Francisco, 513 Parnassus Avenue, S362, San Francisco, CA 94143
| | - Xuan Jesson
- Department of Psychology, Palo Alto University, 1791 Arastradero Road, Palo Alto, CA 94304
| | - Molly Rae Gerdes
- Cortica Healthcare, Department of Neurodevelopmental Medicine, 4000 Civic Center Drive, San Rafael, CA 94903
| | - Barbora G. Jurigova
- Cortica Healthcare, Department of Neurodevelopmental Medicine, 4000 Civic Center Drive, San Rafael, CA 94903
| | - Leighton B. Hinkley
- Department of Radiology & Biomedical Imaging, University of California-San Francisco, 513 Parnassus Avenue, S362, San Francisco, CA 94143
| | - Kamalini G. Ranasinghe
- University of California-San Francisco, Department of Neurology, 675 Nelson Rising Lane, San Francisco, CA 94143
| | - Shivani Desai
- University of California-San Francisco, Department of Neurology, 675 Nelson Rising Lane, San Francisco, CA 94143
| | - Susanne Honma
- Department of Radiology & Biomedical Imaging, University of California-San Francisco, 513 Parnassus Avenue, S362, San Francisco, CA 94143
| | - Danielle Mizuiri
- Department of Radiology & Biomedical Imaging, University of California-San Francisco, 513 Parnassus Avenue, S362, San Francisco, CA 94143
| | - Anne Findlay
- Department of Radiology & Biomedical Imaging, University of California-San Francisco, 513 Parnassus Avenue, S362, San Francisco, CA 94143
| | - Srikantan S. Nagarajan
- Department of Radiology & Biomedical Imaging, University of California-San Francisco, 513 Parnassus Avenue, S362, San Francisco, CA 94143
| | - Elysa J. Marco
- Cortica Healthcare, Department of Neurodevelopmental Medicine, 4000 Civic Center Drive, San Rafael, CA 94903
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Tavella A, Uhlhaas PJ. Magnetoencephalography in Psychiatry: A Perspective on Translational Research and Applications. ADVANCES IN NEUROBIOLOGY 2024; 40:143-156. [PMID: 39562444 DOI: 10.1007/978-3-031-69491-2_6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/21/2024]
Abstract
Magnetoencephalography (MEG) is a neuroimaging technique that has excellent temporal as well as good spatial resolution for measuring neural activity and has been extensively employed in cognitive neuroscience. However, MEG has only been more recently applied to investigations of brain networks and biomarkers in psychiatry. Besides providing new insights into the pathophysiology of major psychiatry syndromes, especially in schizophrenia, a major objective of current research is the identification of biomarkers that could inform early intervention and novel treatments. This chapter will provide a state-of-the-art overview of MEG as applied to schizophrenia, autism spectrum disorders, and Alzheimer's disease, summarizing methodological approaches and studies investigating alterations during resting-state and task-related paradigms. In addition, we will highlight future methodological developments and their potential for applications of MEG in psychiatry.
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Affiliation(s)
- Angelantonio Tavella
- Department of Translational Biomedicine and Neuroscience, University of Bari, Bari, Italy
- Department of Mental Health, ASL Bari, Bari, Italy
| | - Peter J Uhlhaas
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, UK.
- Department of Child and Adolescent Psychiatry, Charité Universitätsmedizin, Berlin, Germany.
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7
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Green HL, Shen G, Franzen RE, Mcnamee M, Berman JI, Mowad TG, Ku M, Bloy L, Liu S, Chen YH, Airey M, McBride E, Goldin S, Dipiero MA, Blaskey L, Kuschner ES, Kim M, Konka K, Roberts TPL, Edgar JC. Differential Maturation of Auditory Cortex Activity in Young Children with Autism and Typical Development. J Autism Dev Disord 2023; 53:4076-4089. [PMID: 35960416 PMCID: PMC9372967 DOI: 10.1007/s10803-022-05696-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/22/2022] [Indexed: 11/20/2022]
Abstract
Maturation of auditory cortex neural encoding processes was assessed in children with typical development (TD) and autism. Children 6-9 years old were enrolled at Time 1 (T1), with follow-up data obtained ~ 18 months later at Time 2 (T2), and ~ 36 months later at Time 3 (T3). Findings suggested an initial period of rapid auditory cortex maturation in autism, earlier than TD (prior to and surrounding the T1 exam), followed by a period of faster maturation in TD than autism (T1-T3). As a result of group maturation differences, post-stimulus group differences were observed at T1 but not T3. In contrast, stronger pre-stimulus activity in autism than TD was found at all time points, indicating this brain measure is stable across time.
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Affiliation(s)
- Heather L Green
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.
| | - Guannan Shen
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Rose E Franzen
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Marybeth Mcnamee
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Jeffrey I Berman
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Theresa G Mowad
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Matthew Ku
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Luke Bloy
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Song Liu
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Yu-Han Chen
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Megan Airey
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Emma McBride
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Sophia Goldin
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Marissa A Dipiero
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Lisa Blaskey
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Autism Research, Department of Pediatrics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Emily S Kuschner
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Center for Autism Research, Department of Pediatrics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Mina Kim
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Kimberly Konka
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Timothy P L Roberts
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - J Christopher Edgar
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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8
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Williams ZJ, Abdelmessih PG, Key AP, Woynaroski TG. Cortical Auditory Processing of Simple Stimuli Is Altered in Autism: A Meta-analysis of Auditory Evoked Responses. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2021; 6:767-781. [PMID: 33229245 PMCID: PMC8639293 DOI: 10.1016/j.bpsc.2020.09.011] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Revised: 09/15/2020] [Accepted: 09/15/2020] [Indexed: 12/29/2022]
Abstract
BACKGROUND Auditory perceptual abnormalities are common in persons on the autism spectrum. The neurophysiologic underpinnings of these differences have frequently been studied using auditory event-related potentials (ERPs) and event-related magnetic fields (ERFs). However, no study to date has quantitatively synthesized this literature to determine whether early auditory ERP/ERF latencies or amplitudes in autistic persons differ from those of typically developing control subjects. METHODS We searched PubMed and ProQuest for studies comparing 1) latencies/amplitudes of P1/M50, N1b, N1c, M100, P2/M200, and/or N2 ERP/ERF components evoked by pure tones and 2) paired-click sensory gating (P1/N1b amplitude suppression) in autistic individuals and typically developing control subjects. Effects were synthesized using Bayesian 3-level meta-analysis. RESULTS In response to pure tones, autistic individuals exhibited prolonged P1/M50 latencies (g = 0.341 [95% credible interval = 0.166, 0.546]), prolonged M100 latencies (g = 0.319 [0.093, 0.550]), reduced N1c amplitudes (g = -0.812 [-1.278, -0.187]), and reduced N2 amplitudes (g = -0.374 [-0.633, -0.179]). There were no practically significant group differences in P2/M200 latencies, N2 latencies, P1/M50 amplitudes, N1b amplitudes, M100 amplitudes, or P2/M200 amplitudes. Paired-click sensory gating was also reduced in autistic individuals (g = -0.389 [-0.619, -0.112]), although this effect was primarily driven by smaller responses to the first click stimulus. CONCLUSIONS Relative to typically developing control subjects, autistic individuals demonstrate multiple alterations in early cortical auditory processing of simple stimuli. However, most group differences were modest in size and based on small numbers of heterogeneous studies with variable quality. Future work is necessary to understand whether these neurophysiologic measures can predict clinically meaningful outcomes or serve as stratification biomarkers for the autistic population.
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Affiliation(s)
- Zachary J Williams
- Medical Scientist Training Program, Vanderbilt University School of Medicine, Nashville, Tennessee; Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee; Frist Center for Autism and Innovation, Vanderbilt University, Nashville, Tennessee; Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, Tennessee.
| | - Peter G Abdelmessih
- Neuroscience Undergraduate Program, Vanderbilt University, Nashville, Tennessee
| | - Alexandra P Key
- Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, Tennessee; Vanderbilt Kennedy Center, Vanderbilt University Medical Center, Nashville, Tennessee; Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Tiffany G Woynaroski
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee; Frist Center for Autism and Innovation, Vanderbilt University, Nashville, Tennessee; Department of Hearing and Speech Sciences, Vanderbilt University Medical Center, Nashville, Tennessee; Vanderbilt Kennedy Center, Vanderbilt University Medical Center, Nashville, Tennessee
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