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Looking Back at the Next 40 Years of ASD Neuroscience Research

  • S.I. :Autism in Review: 1980-2020: 40 years after DSM-III
  • Published:
Journal of Autism and Developmental Disorders Aims and scope Submit manuscript

Abstract

During the last 40 years, neuroscience has become one of the most central and most productive approaches to investigating autism. In this commentary, we assemble a group of established investigators and trainees to review key advances and anticipated developments in neuroscience research across five modalities most commonly employed in autism research: magnetic resonance imaging, functional near infrared spectroscopy, positron emission tomography, electroencephalography, and transcranial magnetic stimulation. Broadly, neuroscience research has provided important insights into brain systems involved in autism but not yet mechanistic understanding. Methodological advancements are expected to proffer deeper understanding of neural circuitry associated with function and dysfunction during the next 40 years.

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References

  • Abdolzadegan, D., Moattar, M. H., & Ghoshuni, M. (2020). A robust method for early diagnosis of autism spectrum disorder from EEG signals based on feature selection and DBSCAN method. Biocybernetics and Biomedical Engineering, 40(1), 482–493.

    Article  Google Scholar 

  • Abujadi, C., Croarkin, P. E., Bellini, B. B., Brentani, H., & Marcolin, M. A. (2018). Intermittent theta-burst transcranial magnetic stimulation for autism spectrum disorder: an open-label pilot study. Revista Brasileira De Psiquiatria, 40(3), 309–311. https://doi.org/10.1590/1516-4446-2017-2279PMID-29236921

    Article  PubMed  Google Scholar 

  • Agam, Y., Joseph, R. M., Barton, J. J., & Manoach, D. S. (2010). Reduced cognitive control of response inhibition by the anterior cingulate cortex in autism spectrum disorders. NeuroImage, 52(1), 336–347. https://doi.org/10.1016/j.neuroimage.2010.04.010

    Article  PubMed  Google Scholar 

  • Ameis, S. H., Blumberger, D. M., Croarkin, P. E., Mabbott, D. J., Lai, M.-C., Desarkar, P., et al. (2020). Treatment of Executive Function Deficits in Autism Spectrum Disorder with Repetitive Transcranial Magnetic Stimulation: A double-blind, sham-controlled, pilot trial. Brain Stimulation, 13(3), 539–547. https://doi.org/10.1016/j.brs.2020.01.007

    Article  PubMed  PubMed Central  Google Scholar 

  • American Psychiatric Association. (1980). Diagnostic and statistical manual of mental disorders (3rd ed.). . American Psychiatric Association.

    Google Scholar 

  • American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders : DSM-5 (5th ed.). . American Psychiatric Association.

    Book  Google Scholar 

  • Anagnostou, E., Jones, N., Huerta, M., Halladay, A. K., Wang, P., Scahill, L., et al. (2015). Measuring social communication behaviors as a treatment endpoint in individuals with autism spectrum disorder. Autism, 19(5), 622–636. https://doi.org/10.1177/1362361314542955PMID-25096930

    Article  PubMed  Google Scholar 

  • Andersson, J. D., Matuskey, D., & Finnema, S. J. (2019). Positron emission tomography imaging of the gamma-aminobutyric acid system. Neuroscience Letters, 691, 35–43. https://doi.org/10.1016/j.neulet.2018.08.010

    Article  PubMed  Google Scholar 

  • Andersson, M., Tangen, Ä., Farde, L., Bölte, S., Halldin, C., Borg, J., et al. (2020). Serotonin transporter availability in adults with autism-a positron emission tomography study. Molecular Psychiatry. https://doi.org/10.1038/s41380-020-00868-3

    Article  PubMed  PubMed Central  Google Scholar 

  • Bajjalieh, S. M., Frantz, G. D., Weimann, J. M., McConnell, S. K., & Scheller, R. H. (1994). Differential expression of synaptic vesicle protein 2 (SV2) isoforms. Journal of Neuroscience, 14(9), 5223–5235. https://doi.org/10.1523/jneurosci.14-09-05223.1994

    Article  PubMed  Google Scholar 

  • Barahona-Corrêa, J. B., Velosa, A., Chainho, A., Lopes, R., & Oliveira-Maia, A. J. (2018). Repetitive Transcranial Magnetic Stimulation for Treatment of Autism Spectrum Disorder: A Systematic Review and Meta-Analysis. Frontiers in Integrative Neuroscience, 12, 27. https://doi.org/10.3389/fnint.2018.00027PMID-30038561

    Article  PubMed  PubMed Central  Google Scholar 

  • Barker, A. T., Jalinous, R., & Freeston, I. L. (1985). Non-invasive magnetic stimulation of human motor cortex. Lancet, 1(8437), 1106–1107. https://doi.org/10.1016/s0140-6736(85)92413-4

    Article  PubMed  Google Scholar 

  • Baron-Cohen, S., Wheelwright, S., Skinner, R., Martin, J., & Clubley, E. (2001). The autism-spectrum quotient (AQ): Evidence from asperger syndrome/high-functioning autism, malesand females, scientists and mathematicians. Journal of Autism and Developmental Disorders, 31(1), 5–17.

    Article  PubMed  Google Scholar 

  • Berg, J. M., & Geschwind, D. H. (2012). Autism genetics: searching for specificity and convergence. Genome Biology, 13(7), 247. https://doi.org/10.1186/gb4034

    Article  PubMed  PubMed Central  Google Scholar 

  • Beversdorf, D. Q., Nordgren, R. E., Bonab, A. A., Fischman, A. J., Weise, S. B., Dougherty, D. D., et al. (2012). 5-HT2 receptor distribution shown by [18F] setoperone PET in high-functioning autistic adults. Journal of Neuropsychiatry and Clinical Neurosciences, 24(2), 191–197. https://doi.org/10.1176/appi.neuropsych.11080202

    Article  PubMed  Google Scholar 

  • Bhandari, R., Kirilina, E., Caan, M., Suttrup, J., De Sanctis, T., De Angelis, L., et al. (2020). Does higher sampling rate (multiband plus SENSE) improve group statistics - an example from social neuroscience block design at 3T. NeuroImage. https://doi.org/10.1016/j.neuroimage.2020.116731

    Article  PubMed  PubMed Central  Google Scholar 

  • Bhat, A. N., Hoffman, M. D., Trost, S. L., Culotta, M. L., Eilbott, J., Tsuzuki, D., et al. (2017). Cortical activation during action observation, action execution, and interpersonal synchrony in adults: a functional near-infrared spectroscopy (fNIRS) study. Frontiers in Human Neuroscience, 11, 431.

    Article  PubMed  PubMed Central  Google Scholar 

  • Bhat, A. N., McDonald, N. M., Eilbott, J. E., & Pelphrey, K. A. (2019). Exploring cortical activation and connectivity in infants with and without familial risk for autism during naturalistic social interactions: A preliminary study. Infant Behavior and Development, 57, 101337.

    Article  PubMed  Google Scholar 

  • Boas, D. A., Elwell, C. E., Ferrari, M., & Taga, G. (2014). Twenty years of functional near-infrared spectroscopy: introduction for the special issue. Elsevier.

    Google Scholar 

  • Bosl, W. J., Tager-Flusberg, H., & Nelson, C. A. (2018). EEG analytics for early detection of autism spectrum disorder: a data-driven approach. Scientific Reports, 8(1), 1–20.

    Article  Google Scholar 

  • Brigadoi, S., Ceccherini, L., Cutini, S., Scarpa, F., Scatturin, P., Selb, J., et al. (2014). Motion artifacts in functional near-infrared spectroscopy: a comparison of motion correction techniques applied to real cognitive data. NeuroImage, 85, 181–191.

    Article  PubMed  Google Scholar 

  • Brihadiswaran, G., Haputhanthri, D., Gunathilaka, S., Meedeniya, D., & Jayarathna, S. (2019). EEG-based processing and classification methodologies for autism spectrum disorder: a review. Journal of Computer Science, 15(8).

  • Brothers, L. (1990). The social brain: a project for inegrating primate behavior and neuropsychology in a new domain. Concepts in Neuroscience, 1, 27–51.

    Google Scholar 

  • Brown, S. S. G., Rutland, J. W., Verma, G., Feldman, R. E., Alper, J., Schneider, M., et al. (2019). Structural MRI at 7T reveals amygdala nuclei and hippocampal subfield volumetric association with major depressive disorder symptom severity. Science and Reports, 9(1), 10166. https://doi.org/10.1038/s41598-019-46687-7

    Article  Google Scholar 

  • Bruneau, N., Roux, S., Adrien, J. L., & Barthélémy, C. (1999). Auditory associative cortex dysfunction in children with autism: evidence from late auditory evoked potentials (N1 wave–T complex). Clinical Neurophysiology, 110(11), 1927–1934.

    Article  PubMed  Google Scholar 

  • Buchwald, J. S., Erwin, R., Van Lancker, D., Guthrie, D., Schwafel, J., & Tanguay, P. (1992). Midlatency auditory evoked responses: P1 abnormalities in adult autistic subjects. Electroencephalography and Clinical Neurophysiology, 84(2), 164–171.

    Article  PubMed  Google Scholar 

  • Butler, L. K., Kiran, S., & Tager-Flusberg, H. (2020). Functional near-infrared spectroscopy in the study of speech and language impairment across the life span: a systematic review. American Journal of Speech-Language Pathology, 29(3), 1674–1701.

    Article  PubMed  PubMed Central  Google Scholar 

  • Buzsaki, G. (2006). Rhythms of the brain: Oxford University Press.

  • Campos, E., Hazlett, C., Tan, P., Truong, H., Loo, S., DiStefano, C., et al. (2020). Principle ERP reduction and analysis: Estimating and using principle ERP waveforms underlying ERPs across tasks, subjects and electrodes. NeuroImage, 212, 116630.

    Article  PubMed  Google Scholar 

  • Cantiani, C., Choudhury, N. A., Yu, Y. H., Shafer, V. L., Schwartz, R. G., & Benasich, A. A. (2016). From sensory perception to lexical-semantic processing: an ERP study in non-verbal children with autism. PLoS ONE, 11(8), e0161637.

    Article  PubMed  PubMed Central  Google Scholar 

  • Casanova, M., Baruth, J., El-Baz, A., Tasman, A., Sears, L., & Sokhadze, E. (2012). Repetitive transcanial magnetic stimulation (RTMS) modulates event-related potential (ERP) indices of attention in autism. Translational Neuroscience, 3(2), 170–180. https://doi.org/10.2478/s13380-012-0022-0PMID-24683490

    Article  PubMed  Google Scholar 

  • Casanova, M. F., Shaban, M., Ghazal, M., El-Baz, A. S., Casanova, E. L., Opris, I., et al. (2020). Effects of Transcranial Magnetic Stimulation Therapy on Evoked and Induced Gamma Oscillations in Children with Autism Spectrum Disorder. Brain Sciences, 10(7), 423. https://doi.org/10.3390/brainsci10070423

    Article  PubMed Central  Google Scholar 

  • Casanova, M. F., Sokhadze, E. M., Casanova, E. L., & Li, X. (2020). Transcranial Magnetic Stimulation in Autism Spectrum Disorders: Neuropathological Underpinnings and Clinical Correlations. Seminars in Pediatric Neurology. https://doi.org/10.1016/j.spen.2020.100832

    Article  PubMed  PubMed Central  Google Scholar 

  • Cascio, C. J., Moana-Filho, E. J., Guest, S., Nebel, M. B., Weisner, J., Baranek, G. T., et al. (2012). Perceptual and neural response to affective tactile texture stimulation in adults with autism spectrum disorders. Autism Research, 5(4), 231–244. https://doi.org/10.1002/aur.1224

    Article  PubMed  PubMed Central  Google Scholar 

  • Cassia, V. M., Kuefner, D., Westerlund, A., & Nelson, C. A. (2006). A behavioural and ERP investigation of 3-month-olds’ face preferences. Neuropsychologia, 44(11), 2113–2125.

    Article  PubMed  Google Scholar 

  • Castelli, F., Frith, C., Happe, F., & Frith, U. (2002). Autism, asperger syndrome and brain mechanisms for the attribution of mental states to animated shapes. Brain, 125(Pt 8), 1839–1849. https://doi.org/10.1093/brain/awf189

    Article  PubMed  Google Scholar 

  • Catarino, A., Andrade, A., Churches, O., Wagner, A. P., Baron-Cohen, S., & Ring, H. (2013). Task-related functional connectivity in autism spectrum conditions: an EEG study using wavelet transform coherence. Mol Autism, 4(1), 1–14. https://doi.org/10.1186/2040-2392-4-1

    Article  PubMed  PubMed Central  Google Scholar 

  • Catarino, A., Churches, O., Baron-Cohen, S., Andrade, A., & Ring, H. (2011). Atypical EEG complexity in autism spectrum conditions: a multiscale entropy analysis. Clinical Neurophysiology, 122(12), 2375–2383.

    Article  PubMed  Google Scholar 

  • Chandrasekhar, T., & Sikich, L. (2015). Challenges in the diagnosis and treatment of depression in autism spectrum disorders across the lifespan. Dialogues in Clinical Neuroscience, 17(2), 219.

    Article  PubMed  PubMed Central  Google Scholar 

  • Chen, J. E., Polimeni, J. R., Bollmann, S., & Glover, G. H. (2019). On the analysis of rapidly sampled fMRI data. NeuroImage, 188, 807–820. https://doi.org/10.1016/j.neuroimage.2019.02.008

    Article  PubMed  Google Scholar 

  • Chiao, J. Y., & Cheon, B. K. (2010). The weirdest brains in the world. The Behavioral and Brain Sciences, 33(2–3), 88–90. https://doi.org/10.1017/S0140525X10000282

    Article  PubMed  Google Scholar 

  • Chugani, D. C., Muzik, O., Behen, M., Rothermel, R., Janisse, J. J., Lee, J., et al. (1999). Developmental changes in brain serotonin synthesis capacity in autistic and nonautistic children. Annals of Neurology, 45(3), 287–295. https://doi.org/10.1002/1531-8249(199903)45:3%3c287::aid-ana3%3e3.0.co;2-9

    Article  PubMed  Google Scholar 

  • Chugani, D. C., Muzik, O., Rothermel, R., Behen, M., Chakraborty, P., Mangner, T., et al. (1997). Altered serotonin synthesis in the dentatothalamocortical pathway in autistic boys. Annals of Neurology, 42(4), 666–669.

    Article  PubMed  Google Scholar 

  • Ciesielski, K. T., Knight, J. E., Prince, R. J., Harris, R. J., & Handmaker, S. D. (1995). Event-related potentials in cross-modal divided attention in autism. Neuropsychologia, 33(2), 225–246.

    Article  PubMed  Google Scholar 

  • Clarkson, T., Kang, E., Capriola-Hall, N., Lerner, M. D., Jarcho, J., & Prinstein, M. J. (2020). Meta-analysis of the RDoC social processing domain across units of analysis in children and adolescents. Journal of Clinical Child & Adolescent Psychology, 49(3), 297–321.

    Article  Google Scholar 

  • Clawson, A., Clayson, P. E., Worsham, W., Johnston, O., South, M., & Larson, M. J. (2014). How about watching others? Observation of error-related feedback by others in autism spectrum disorders. International Journal of Psychophysiology, 92(1), 26–34.

    Article  Google Scholar 

  • Cohen, M. X. (2014). Analyzing neural time series data: theory and practice: MIT press.

  • Cole, E. J., Enticott, P. G., Oberman, L. M., Gwynette, M. F., Casanova, M. F., Jackson, S. L. J., et al. (2018). The potential of repetitive transcranial magnetic stimulation for autism spectrum disorder: a consensus statement. Biological Psychiatry. https://doi.org/10.1016/j.biopsych.2018.06.003

    Article  PubMed  PubMed Central  Google Scholar 

  • Collaboration, O. S. (2015). Estimating the reproducibility of psychological science. Science. https://doi.org/10.1126/science.aac4716

    Article  Google Scholar 

  • Constantino, J. (2003). Social responsiveness scale. Los Angeles, CA: Western Psychological Services.

  • Constantino, J. N., Abbacchi, A. M., Saulnier, C., Klaiman, C., Mandell, D. S., Zhang, Y., et al. (2020). Timing of the diagnosis of autism in African American children. Pediatrics, 146(3). https://doi.org/10.1542/peds.2019-3629.

  • Courchesne, E., Campbell, K., & Solso, S. (2011). Brain growth across the life span in autism: age-specific changes in anatomical pathology. Brain Research, 1380, 138–145. https://doi.org/10.1016/j.brainres.2010.09.101

    Article  PubMed  Google Scholar 

  • Courchesne, E., Courchesne, R. Y., Hicks, G., & Lincoln, A. J. (1985). Functioning of the brain-stem auditory pathway in non-retarded autistic individuals. Electroencephalography and Clinical Neurophysiology, 61(6), 491–501.

    Article  PubMed  Google Scholar 

  • Courchesne, E., Lincoln, A. J., Kilman, B. A., & Galambos, R. (1985). Event-related brain potential correlates of the processing of novel visual and auditory information in autism. Journal of Autism and Developmental Disorders, 15(1), 55–76.

    Article  PubMed  Google Scholar 

  • Courchesne, E., Lincoln, A. J., Yeung-Courchesne, R., Elmasian, R., & Grillon, C. (1989). Pathophysiologic findings in nonretarded autism and receptive developmental language disorder. Journal of Autism and Developmental Disorders, 19(1), 1–17.

    Article  PubMed  Google Scholar 

  • Courchesne, E., & Pierce, K. (2005). Why the frontal cortex in autism might be talking only to itself: local over-connectivity but long-distance disconnection. Current Opinion in Neurobiology, 15(2), 225–230.

    Article  PubMed  Google Scholar 

  • Creak, M., & Pampiglione, G. (1969). Clinical and EEG studies on a group of 35 psychotic children. Developmental Medicine and Child Neurology, 11(2), 218–227.

    Article  PubMed  Google Scholar 

  • Cremone-Caira, A., Vaidyanathan, A., Hyatt, D., Gilbert, R., Clarkson, T., & Faja, S. (2020). Test-retest reliability of the N2 event-related potential in school-aged children with autism spectrum disorder (ASD). Clinical Neurophysiology, 131(2), 406–413.

    Article  PubMed  Google Scholar 

  • Cristancho, P., Akkineni, K., Constantino, J. N., Carter, A. R., & ’Reardon, J. P. O. . (2014). Transcranial Magnetic Stimulation in a 15-Year-Old Patient With Autism and Comorbid Depression. Journal of ECT, 30(4), e46-47.

    Article  PubMed  Google Scholar 

  • Cuthbert, B. N., & Insel, T. R. (2010). Toward new approaches to psychotic disorders: the NIMH Research Domain Criteria project. Oxford University Press.

    Google Scholar 

  • D’Mello, A. M., & Stoodley, C. J. (2015). Cerebro-cerebellar circuits in autism spectrum disorder. Frontiers in Neuroscience, 9, 408. https://doi.org/10.3389/fnins.2015.00408

    Article  PubMed  PubMed Central  Google Scholar 

  • David, N., Schneider, T., Peiker, I., Al-Jawahiri, R., Engel, A. K., & Milne, E. (2016). Variability of cortical oscillation patterns: a possible endophenotype in autism spectrum disorders? Neuroscience & Biobehavioral Reviews, 71, 590–600.

    Article  Google Scholar 

  • Dawson, G., Finley, C., Phillips, S., Galpert, L., & Lewy, A. (1988). Reduced P3 amplitude of the event-related brain potential: its relationship to language ability in autism. Journal Autism Dev Disord, 18(4), 493–504.

    Article  Google Scholar 

  • de Haan, M., & Nelson, C. A. (1999). Brain activity differentiates face and object processing in 6-month-old infants. Developmental Psychology, 35(4), 1113–1121.

    Article  PubMed  Google Scholar 

  • de la Torre-Ubieta, L., Won, H., Stein, J. L., & Geschwind, D. H. (2016). Advancing the understanding of autism disease mechanisms through genetics. Nature Medicine, 22(4), 345–361. https://doi.org/10.1038/nm.4071

    Article  PubMed  PubMed Central  Google Scholar 

  • Deykin, E. Y., & MacMahon, B. (1979). The incidence of seizures among children with autistic symptoms. American Journal of Psychiatry, 136(10), 1310–1312.

    Article  PubMed  Google Scholar 

  • Di, X., Azeez, A., Li, X., Haque, E., & Biswal, B. B. (2018). Disrupted focal white matter integrity in autism spectrum disorder: a voxel-based meta-analysis of diffusion tensor imaging studies. Progress in Neuro-Psychopharmacology and Biological Psychiatry, 82, 242–248. https://doi.org/10.1016/j.pnpbp.2017.11.007

    Article  PubMed  Google Scholar 

  • Diedrichsen, J., Maderwald, S., Kuper, M., Thurling, M., Rabe, K., Gizewski, E. R., et al. (2011). Imaging the deep cerebellar nuclei: a probabilistic atlas and normalization procedure. NeuroImage, 54(3), 1786–1794. https://doi.org/10.1016/j.neuroimage.2010.10.035

    Article  PubMed  Google Scholar 

  • Dikker, S., Wan, L., Davidesco, I., Kaggen, L., Oostrik, M., McClintock, J., et al. (2017). Brain-to-brain synchrony tracks real-world dynamic group interactions in the classroom. Current Biology, 27(9), 1375–1380.

    Article  PubMed  Google Scholar 

  • Dinstein, I., Pierce, K., Eyler, L., Solso, S., Malach, R., Behrmann, M., et al. (2011). Disrupted neural synchronization in toddlers with autism. Neuron, 70(6), 1218–1225.

    Article  PubMed  PubMed Central  Google Scholar 

  • Dirks, B., Romero, C., Voorhies, W., Kupis, L., Nomi, J. S., Dajani, D. R., et al. (2020). Neural Responses to a Putative Set-shifting Task in Children with Autism Spectrum Disorder. Autism Research, 13(9), 1501–1515. https://doi.org/10.1002/aur.2347

    Article  PubMed  Google Scholar 

  • DiStefano, C., Senturk, D., & Jeste, S. S. (2019). ERP evidence of semantic processing in children with ASD. Developmental Cognitive Neuroscience, 100640.

  • Drysdale, A. T., Grosenick, L., Downar, J., Dunlop, K., Mansouri, F., Meng, Y., et al. (2017). Resting-state connectivity biomarkers define neurophysiological subtypes of depression. Nature Medicine, 23(1), 28–38. https://doi.org/10.1038/nm.4246

    Article  PubMed  Google Scholar 

  • Easson, A. K., & McIntosh, A. R. (2019). BOLD signal variability and complexity in children and adolescents with and without autism spectrum disorder. Developmental Cognitive Neuroscience, 36, 100630. https://doi.org/10.1016/j.dcn.2019.100630

    Article  PubMed  PubMed Central  Google Scholar 

  • Eigsti, I. M., Schuh, J., Mencl, E., Schultz, R. T., & Paul, R. (2012). The neural underpinnings of prosody in autism. Child Neuropsychology, 18(6), 600–617. https://doi.org/10.1080/09297049.2011.639757

    Article  PubMed  Google Scholar 

  • Ellegood, J., Anagnostou, E., Babineau, B. A., Crawley, J. N., Lin, L., Genestine, M., et al. (2015). Clustering autism: using neuroanatomical differences in 26 mouse models to gain insight into the heterogeneity. Molecular Psychiatry, 20(1), 118–125. https://doi.org/10.1038/mp.2014.98

    Article  PubMed  Google Scholar 

  • Enticott, P. G., Fitzgibbon, B. M., Kennedy, H. A., Arnold, S. L., Elliot, D., Peachey, A., et al. (2014). A Double-blind, Randomized Trial of Deep Repetitive Transcranial Magnetic Stimulation (rTMS) for Autism Spectrum Disorder. Brain Stimulation, 7(2), 206–211. https://doi.org/10.1016/j.brs.2013.10.004PMID-24280031

    Article  PubMed  Google Scholar 

  • Esser, S. K., Huber, R., Massimini, M., Peterson, M. J., Ferrarelli, F., & Tononi, G. (2006). A direct demonstration of cortical LTP in humans: a combined TMS/EEG study. Brain Research Bulletin, 69(1), 86–94. https://doi.org/10.1016/j.brainresbull.2005.11.003

    Article  PubMed  Google Scholar 

  • Faja, S., Clarkson, T., & Webb, S. J. (2016). Neural and behavioral suppression of interfering flankers by children with and without autism spectrum disorder. Neuropsychologia, 93, 251–261.

    Article  PubMed  PubMed Central  Google Scholar 

  • Fan, J., Bekele, E., Warren, Z., & Sarkar, N. (2017). EEG analysis of facial affect recognition process of individuals with ASD performance prediction leveraging social context. In 2017 seventh international conference on affective computing and intelligent interaction workshops and demos (ACIIW) (pp. 38–43). IEEE.

  • Fan, J., Wade, J. W., Bian, D., Key, A. P., Warren, Z. E., Mion, L. C., et al. (2015). A step towards EEG-based brain computer interface for autism intervention. In 2015 37th annual international conference of the IEEE engineering in medicine and biology society (EMBC) (pp. 3767–3770). IEEE.

  • Fatemi, S. H., Wong, D. F., Brašić, J. R., Kuwabara, H., Mathur, A., Folsom, T. D., et al. (2018). Metabotropic glutamate receptor 5 tracer [(18)F]-FPEB displays increased binding potential in postcentral gyrus and cerebellum of male individuals with autism: a pilot PET study. Cerebellum & Ataxias, 5, 3–3. https://doi.org/10.1186/s40673-018-0082-1

    Article  Google Scholar 

  • Ferri, R., Elia, M., Agarwal, N., Lanuzza, B., Musumeci, S. A., & Pennisi, G. (2003). The mismatch negativity and the P3a components of the auditory event-related potentials in autistic low-functioning subjects. Clinical Neurophysiology, 114(9), 1671–1680.

    Article  PubMed  Google Scholar 

  • Finnema, S. J., Nabulsi, N. B., Eid, T., Detyniecki, K., Lin, S. F., Chen, M. K., et al. (2016). Imaging synaptic density in the living human brain. Science Translational Medicine, 8(348), 348ra396. https://doi.org/10.1126/scitranslmed.aaf6667.

  • Finnema, S. J., Nabulsi, N. B., Mercier, J., Lin, S. F., Chen, M. K., Matuskey, D., et al. (2018). Kinetic evaluation and test-retest reproducibility of [(11)C]UCB-J, a novel radioligand for positron emission tomography imaging of synaptic vesicle glycoprotein 2A in humans. Journal of Cerebral Blood Flow and Metabolism, 38(11), 2041–2052. https://doi.org/10.1177/0271678x17724947

    Article  PubMed  Google Scholar 

  • Fox, S. E., Wagner, J., Shrock, C. L., Flusberg, H. T., & Nelson, C. A. (2013). Neural processing of facial identity and emotion in infants at high-risk for autism spectrum disorders. Frontiers in Human Neuroscience, 7, 89.

    Article  PubMed  PubMed Central  Google Scholar 

  • Funabiki, Y., Murai, T., & Toichi, M. (2012). Cortical activation during attention to sound in autism spectrum disorders. Research in Developmental Disabilities, 33(2), 518–524.

    Article  PubMed  Google Scholar 

  • Fung, L. K., Flores, R. E., Gu, M., Sun, K. L., James, D., Schuck, R. K., et al. (2020). Thalamic and prefrontal GABA concentrations but not GABA(A) receptor densities are altered in high-functioning adults with autism spectrum disorder. Molecular Psychiatry. https://doi.org/10.1038/s41380-020-0756-y

    Article  PubMed  PubMed Central  Google Scholar 

  • Gómez, L., Vidal, B., Maragoto, C., Morales, L., Berrillo, S., Cuesta, H., et al. (2017). Non-Invasive Brain Stimulation for Children with Autism Spectrum Disorders: A Short-Term Outcome Study. Behavioral Sciences, 7(3), 63.

    Article  PubMed Central  Google Scholar 

  • Green, S. A., Hernandez, L., Bookheimer, S. Y., & Dapretto, M. (2017). Reduced modulation of thalamocortical connectivity during exposure to sensory stimuli in ASD. Autism Research, 10(5), 801–809. https://doi.org/10.1002/aur.1726

    Article  PubMed  Google Scholar 

  • Green, S. A., Hernandez, L., Tottenham, N., Krasileva, K., Bookheimer, S. Y., & Dapretto, M. (2015). Neurobiology of sensory overresponsivity in youth with autism spectrum disorders. JAMA Psychiatry, 72(8), 778–786. https://doi.org/10.1001/jamapsychiatry.2015.0737

    Article  PubMed  PubMed Central  Google Scholar 

  • Grillon, C., Courchesne, E., & Akshoomoff, N. (1989). Brainstem and middle latency auditory evoked potentials in autism and developmental language disorder. Journal of Autism and Developmental Disorders, 19(2), 255–269.

    Article  PubMed  Google Scholar 

  • Grossi, E., Olivieri, C., & Buscema, M. (2017). Diagnosis of autism through EEG processed by advanced computational algorithms: a pilot study. Computer Methods and Programs in Biomedicine, 142, 73–79.

    Article  PubMed  Google Scholar 

  • Grossi, E., Valbusa, G., & Buscema, M. (2020). Detection of an autism EEG signature from only two EEG channels through features extraction and advanced machine learning analysis. Clinical EEG and Neuroscience. 1550059420982424.

  • Guillon, Q., Rogé, B., Afzali, M. H., Baduel, S., Kruck, J., & Hadjikhani, N. (2016). Intact perception but abnormal orientation towards face-like objects in young children with ASD. Scientific Reports, 6(1), 1–9.

    Article  Google Scholar 

  • Gurau, O., Bosl, W. J., & Newton, C. R. (2017). How useful is electroencephalography in the diagnosis of autism spectrum disorders and the delineation of subtypes: a systematic review. Frontiers in Psychiatry, 8, 121.

    Article  PubMed  PubMed Central  Google Scholar 

  • Guye, M., Bartolomei, F., & Ranjeva, J. P. (2019). Malformations of cortical development: the role of 7-Tesla magnetic resonance imaging in diagnosis. Rev Neurol (paris), 175(3), 157–162. https://doi.org/10.1016/j.neurol.2019.01.393

    Article  Google Scholar 

  • Haar, S., Berman, S., Behrmann, M., & Dinstein, I. (2016). Anatomical abnormalities in autism? Cerebral Cortex, 26(4), 1440–1452. https://doi.org/10.1093/cercor/bhu242

    Article  PubMed  Google Scholar 

  • Haputhanthri, D., Brihadiswaran, G., Gunathilaka, S., Meedeniya, D., Jayarathna, S., Jaime, M., et al. (2020). Integration of facial thermography in EEG-based classification of ASD. International Journal of Automation and Computing, 1–18.

  • Hawco, C., Yoganathan, L., Voineskos, A. N., Lyon, R., Tan, T., Daskalakis, Z. J., et al. (2020). Greater individual variability in functional brain activity during working memory performance in young people with autism and executive function impairment. Neuroimage Clin, 27, 102260. https://doi.org/10.1016/j.nicl.2020.102260

    Article  PubMed  PubMed Central  Google Scholar 

  • Hazlett, H. C., Gu, H., Munsell, B. C., Kim, S. H., Styner, M., Wolff, J. J., et al. (2017). Early brain development in infants at high risk for autism spectrum disorder. Nature, 542(7641), 348–351. https://doi.org/10.1038/nature21369

    Article  PubMed  PubMed Central  Google Scholar 

  • Hazlett, H. C., Poe, M. D., Gerig, G., Styner, M., Chappell, C., Smith, R. G., et al. (2011). Early brain overgrowth in autism associated with an increase in cortical surface area before age 2 years. Archives of General Psychiatry, 68(5), 467–476. https://doi.org/10.1001/archgenpsychiatry.2011.39

    Article  PubMed  PubMed Central  Google Scholar 

  • Henderson, H., Schwartz, C., Mundy, P., Burnette, C., Sutton, S., Zahka, N., et al. (2006). Response monitoring, the error-related negativity, and differences in social behavior in autism. [Research Support, N.I.H., Extramural]. Brain and Cognition, 61(1), 96–109. https://doi.org/10.1016/j.bandc.2005.12.009.

  • Hendriks, M. H., Dillen, C., Vettori, S., Vercammen, L., Daniels, N., Steyaert, J., et al. (2021). Neural processing of facial identity and expression in adults with and without autism: A multi-method approach. NeuroImage: Clinical, 29, 102520.

  • Henrich, J., Heine, S. J., & Norenzayan, A. (2010). The weirdest people in the world? The Behavioral and Brain Sciences, 33(2–3), 61–83. https://doi.org/10.1017/S0140525X0999152X

    Article  PubMed  Google Scholar 

  • Hermelin, B., & O’Connor, N. (1968). Measures of the occipital alpha rhythm in normal, subnormal and autistic children. British Journal of Psychiatry, 114(510), 603–610.

    Article  Google Scholar 

  • Herrmann, C. S., & Knight, R. T. (2001). Mechanisms of human attention: event-related potentials and oscillations. Neuroscience & Biobehavioral Reviews, 25(6), 465–476.

    Article  Google Scholar 

  • Horder, J., Andersson, M., Mendez, M. A., Singh, N., Tangen, Ä., Lundberg, J., et al. (2018). GABA(A) receptor availability is not altered in adults with autism spectrum disorder or in mouse models. Sci Transl Med. https://doi.org/10.1126/scitranslmed.aam8434

    Article  PubMed  Google Scholar 

  • Hubl, D., Nyffeler, T., Wurtz, P., Chaves, S., Pflugshaupt, T., Luthi, M., et al. (2008). Time course of blood oxygenation level-dependent signal response after theta burst transcranial magnetic stimulation of the frontal eye field. Neuroscience, 151(3), 921–928. https://doi.org/10.1016/j.neuroscience.2007.10.049

    Article  PubMed  Google Scholar 

  • Hudson, C. C., Hall, L., & Harkness, K. L. (2019). Prevalence of depressive disorders in individuals with autism spectrum disorder: a meta-analysis. Journal of Abnormal Child Psychology, 47(1), 165–175.

    Article  PubMed  Google Scholar 

  • Huettel, S. A., Song, A. W., & McCarthy, G. (2008). Functional magnetic resonance imaging. 2nd. Sunderland, MA: Sinauer Associates.

  • Hull, J. V., Dokovna, L. B., Jacokes, Z. J., Torgerson, C. M., Irimia, A., & Van Horn, J. D. (2016). Resting-state functional connectivity in autism spectrum disorders: a review. Front Psychiatry, 7, 205. https://doi.org/10.3389/fpsyt.2016.00205

    Article  PubMed  Google Scholar 

  • Huppert, T. J., Diamond, S. G., Franceschini, M. A., & Boas, D. A. (2009). HomER: a review of time-series analysis methods for near-infrared spectroscopy of the brain. Applied Optics, 48(10), D280–D298.

    Article  PubMed  PubMed Central  Google Scholar 

  • Hur, E. M., & Zhou, F. Q. (2010). GSK3 signalling in neural development. Nature Reviews Neuroscience, 11(8), 539–551. https://doi.org/10.1038/nrn2870

    Article  PubMed  PubMed Central  Google Scholar 

  • Hutt, S. J., Hutt, C., Lee, D., & Ounsted, C. (1965). A behavioural and electroencephalographic study of autistic children. Journal of Psychiatric Research, 3(3), 181–197.

    Article  PubMed  Google Scholar 

  • Insel, T., Cuthbert, B., Garvey, M., Heinssen, R., Pine, D. S., Quinn, K., et al. (2010). Research domain criteria (RDoC): toward a new classification framework for research on mental disorders. American Journal of Psychiatry, 167(7), 748–751. https://doi.org/10.1176/appi.ajp.2010.09091379

    Article  PubMed  Google Scholar 

  • Jack, A., & Morris, J. P. (2014). Neocerebellar contributions to social perception in adolescents with autism spectrum disorder. Developmental Cognitive Neuroscience, 10, 77–92. https://doi.org/10.1016/j.dcn.2014.08.001

    Article  PubMed  PubMed Central  Google Scholar 

  • Jack, A., & Pelphrey, K. A. (2017). Annual research review: understudied populations within the autism spectrum-current trends and future directions in neuroimaging research. Journal of Child Psychology and Psychiatry. https://doi.org/10.1111/jcpp.1268728102566

    Article  PubMed  Google Scholar 

  • Jones, T. (1996). The role of positron emission tomography within the spectrum of medical imaging. European Journal of Nuclear Medicine, 23(2), 207–211.

    Article  PubMed  Google Scholar 

  • Jurcak, V., Tsuzuki, D., & Dan, I. (2007). 10/20, 10/10, and 10/5 systems revisited: their validity as relative head-surface-based positioning systems. NeuroImage, 34(4), 1600–1611.

    Article  PubMed  Google Scholar 

  • Kaiser, M. D., Hudac, C. M., Shultz, S., Lee, S. M., Cheung, C., Berken, A. M., et al. (2010). Neural signatures of autism. Proceedings of the National Academy of Sciences, 107(49), 21223–21228.

    Article  Google Scholar 

  • Kaiser, M. D., Yang, D. Y., Voos, A. C., Bennett, R. H., Gordon, I., Pretzsch, C., et al. (2016). Brain mechanisms for processing affective (and nonaffective) touch are atypical in autism. Cerebral Cortex, 26(6), 2705–2714. https://doi.org/10.1093/cercor/bhv125

    Article  PubMed  Google Scholar 

  • Kang, E., Clarkson, T., Keifer, C. M., Rosen, T. E., & Lerner, M. D. (2019). Discrete electrocortical predictors of anxiety and anxiety-related treatment response in youth with autism spectrum disorder. Biological Psychology, 146, 107710.

    Article  PubMed  Google Scholar 

  • Kang, E., Keifer, C. M., Levy, E. J., Foss-Feig, J. H., McPartland, J. C., & Lerner, M. D. (2018). Atypicality of the N170 event-related potential in autism spectrum disorder: a meta-analysis. Biol Psychiatry Cogn Neurosci Neuroimaging, 3(8), 657–666. https://doi.org/10.1016/j.bpsc.2017.11.003

    Article  PubMed  Google Scholar 

  • Kang, J., Han, X., Song, J., Niu, Z., & Li, X. (2020). The identification of children with autism spectrum disorder by SVM approach on EEG and eye-tracking data. Computers in Biology and Medicine, 120, 103722.

    Article  PubMed  Google Scholar 

  • Kanner, L. (1943). Autistic disturbances of affective contact. Nervous Child, 2(3), 217–250.

    Google Scholar 

  • Katuwal, G. J., Baum, S. A., Cahill, N. D., & Michael, A. M. (2016). Divide and conquer: sub-grouping of ASD improves ASD detection based on brain morphometry. PLoS ONE. https://doi.org/10.1371/journal.pone.0153331

    Article  PubMed  PubMed Central  Google Scholar 

  • Keehn, B., Wagner, J., Tager-Flusberg, H., & Nelson, C. A. (2013). Functional connectivity in the first year of life in infants at-risk for autism: a preliminary near-infrared spectroscopy study. Frontiers in Human Neuroscience, 7, 444.

    Article  PubMed  PubMed Central  Google Scholar 

  • Keifer, C. M., Hauschild, K. M., Nelson, B. D., Hajcak, G., & Lerner, M. D. (2019). Differences in the late positive potential and P300 to emotional faces in individuals with autism spectrum disorder. Journal of Autism and Developmental Disorders, 49(12), 5009–5022.

    Article  PubMed  Google Scholar 

  • Kemner, C., van der Gaag, R. J., Verbaten, M., & van Engeland, H. (1999). ERP differences among subtypes of pervasive developmental disorders. Biological Psychiatry, 46(6), 781–789.

    Article  PubMed  Google Scholar 

  • Kemner, C., Verbaten, M. N., Cuperus, J. M., Camfferman, G., &, , et al. (1994). Visual and somatosensory event-related brain potentials in autistic children and three different control groups. Electroencephalography & Clinical Neurophysiology: Evoked Potentials, 92(3), 225–237.

    Article  Google Scholar 

  • Kinreich, S., Djalovski, A., Kraus, L., Louzoun, Y., & Feldman, R. (2017). Brain-to-brain synchrony during naturalistic social interactions. Scientific Reports, 7(1), 1–12.

    Article  Google Scholar 

  • Krigolson, O. E., Williams, C. C., Norton, A., Hassall, C. D., & Colino, F. L. (2017). Choosing MUSE: validation of a low-cost, portable EEG system for ERP research. Frontiers in Neuroscience, 11, 109.

    Article  PubMed  PubMed Central  Google Scholar 

  • Kuhl, P. K., Coffey-Corina, S., Padden, D., & Dawson, G. (2005). Links between social and linguistic processing of speech in preschool children with autism: behavioral and electrophysiological measures. Developmental Science, 8(1), F1–F12. https://doi.org/10.1111/j.1467-7687.2004.00384.x

    Article  PubMed  Google Scholar 

  • Kuper, M., Thurling, M., Stefanescu, R., Maderwald, S., Roths, J., Elles, H. G., et al. (2012). Evidence for a motor somatotopy in the cerebellar dentate nucleus-an FMRI study in humans. Human Brain Mapping, 33(11), 2741–2749. https://doi.org/10.1002/hbm.21400

    Article  PubMed  Google Scholar 

  • Lai, M. C., Lombardo, M. V., Auyeung, B., Chakrabarti, B., & Baron-Cohen, S. (2015). Sex/gender differences and autism: setting the scene for future research. Journal of the American Academy of Child and Adolescent Psychiatry, 54(1), 11–24. https://doi.org/10.1016/j.jaac.2014.10.003

    Article  PubMed  PubMed Central  Google Scholar 

  • Lange, N., Travers, B. G., Bigler, E. D., Prigge, M. B. D., Froehlich, A. L., Nielsen, J. A., et al. (2015). Longitudinal volumetric brain changes in autism spectrum disorder ages 6–35 years. [Peer Reviewed]. Autism Research. https://doi.org/10.1002/aur.142725381736.

  • Lee, L., Siebner, H., & Bestmann, S. (2006). Rapid modulation of distributed brain activity by transcranial magnetic stimulation of human motor cortex. Behavioural Neurology, 17(3–4), 135–148.

    Article  PubMed  PubMed Central  Google Scholar 

  • Lefevre, A., Beggiato, A., Bourgeron, T., & Toro, R. (2015). Neuroanatomical diversity of corpus callosum and brain volume in autism: meta-analysis, analysis of the autism brain imaging data exchange project, and simulation. Biological Psychiatry, 78(2), 126–134. https://doi.org/10.1016/j.biopsych.2015.02.010

    Article  Google Scholar 

  • Lefevre, A., Richard, N., Mottolese, R., Leboyer, M., & Sirigu, A. (2020). An association between serotonin 1A receptor, gray matter volume, and sociability in healthy subjects and in autism spectrum disorder. Autism Research, 13(11), 1843–1855. https://doi.org/10.1002/aur.2360

    Article  PubMed  Google Scholar 

  • Lelord, G., Laffont, F., Jusseaume, P., & Stephant, J. L. (1973). Comparative study of conditioning of averaged evoked responses by coupling sound and light in normal and autistic children. Psychophysiology, 10(4), 415–425.

    Article  PubMed  Google Scholar 

  • Lerner, M. D., McPartland, J. C., & Morris, J. P. (2013). Multimodal emotion processing in autism spectrum disorders: an event-related potential study. Developmental Cognitive Neuroscience, 3, 11–21. https://doi.org/10.1016/j.dcn.2012.08.005

    Article  PubMed  Google Scholar 

  • Li, Y., & Yu, D. (2016). Weak network efficiency in young children with autism spectrum disorder: evidence from a functional near-infrared spectroscopy study. Brain and Cognition, 108, 47–55.

    Article  PubMed  Google Scholar 

  • Libsack, E., Clarkson, T., & Lerner, M. D. (2018). Unique perspectives: harnessing multimodal assessment to understand how children with autism decode the social world. Behavioral Health News, 6(1), 35.

    Google Scholar 

  • Liston, C., Chen, A. C., Zebley, B. D., Drysdale, A. T., Gordon, R., Leuchter, B., et al. (2014). Default mode network mechanisms of transcranial magnetic stimulation in depression. Biological Psychiatry, 76(7), 517–526.

    Article  PubMed  PubMed Central  Google Scholar 

  • Liu, J., Yao, L., Zhang, W., Xiao, Y., Liu, L., Gao, X., et al. (2017). Gray matter abnormalities in pediatric autism spectrum disorder: a meta-analysis with signed differential mapping. European Child and Adolescent Psychiatry, 26(8), 933–945. https://doi.org/10.1007/s00787-017-0964-4

    Article  PubMed  Google Scholar 

  • Liu, P., Xiao, G., He, K., Zhang, L., Wu, X., Li, D., et al. (2020). Increased Accuracy of Emotion Recognition in Individuals with Autism-Like Traits after Five Days of Magnetic Stimulations. Neural Plasticity, 2020, 1–10. https://doi.org/10.1155/2020/9857987

    Article  Google Scholar 

  • Lloyd-Fox, S., Blasi, A., & Elwell, C. E. (2010). Illuminating the developing brain: the past, present and future of functional near infrared spectroscopy. Neuroscience & Biobehavioral Reviews, 34(3), 269–284.

    Article  Google Scholar 

  • Lloyd-Fox, S., Blasi, A., Elwell, C. E., Charman, T., Murphy, D., & Johnson, M. H. (2013). Reduced neural sensitivity to social stimuli in infants at risk for autism. Proceedings of the Biological Sciences, 280(1758), 20123026. https://doi.org/10.1098/rspb.2012.3026

    Article  Google Scholar 

  • Lombardo, M. V., Lai, M. C., & Baron-Cohen, S. (2019). Big data approaches to decomposing heterogeneity across the autism spectrum. Molecular Psychiatry, 24(10), 1435–1450. https://doi.org/10.1038/s41380-018-0321-0

    Article  PubMed  PubMed Central  Google Scholar 

  • Loth, E., Charman, T., Mason, L., Tillmann, J., Jones, E. J. H. J. H., Wooldridge, C., et al. (2017). The EU-AIMS Longitudinal European Autism Project (LEAP): design and methodologies to identify and validate stratification biomarkers for autism spectrum disorders. Mol Autism, 8, 24. https://doi.org/10.1186/s13229-017-0146-8

    Article  PubMed  PubMed Central  Google Scholar 

  • Luck, S. J. (2005). An introduction to the event-related potential technique (Cognitive neuroscience). MIT Press.

    Google Scholar 

  • Luckhardt, C., Kröger, A., Cholemkery, H., Bender, S., & Freitag, C. M. (2017). Neural correlates of explicit versus implicit facial emotion processing in ASD. Journal of Autism and Developmental Disorders, 47(7), 1944–1955.

    Article  PubMed  Google Scholar 

  • Lushchekina, E., Khaerdinova, O. Y., Novototskii-Vlasov, V. Y., Lushchekin, V., & Strelets, V. (2016). Synchronization of EEG rhythms in baseline conditions and during counting in children with autism spectrum disorders. Neuroscience and Behavioral Physiology, 46(4), 382–389.

    Article  Google Scholar 

  • Luyster, R. J., Bick, J., Westerlund, A., & Nelson, C. A., III. (2019). Testing the effects of expression, intensity and age on emotional face processing in ASD. Neuropsychologia, 126, 128–137.

    Article  PubMed  Google Scholar 

  • Mandell, D. S. (2008). Psychiatric hospitalization among children with autism spectrum disorders. Journal of Autism and Developmental Disorders, 38(6), 1059–1065. https://doi.org/10.1007/s10803-007-0481-2

    Article  PubMed  Google Scholar 

  • Marsh, L. E., & Hamilton, A. F. (2011). Dissociation of mirroring and mentalising systems in autism. NeuroImage, 56(3), 1511–1519. https://doi.org/10.1016/j.neuroimage.2011.02.003

    Article  PubMed  Google Scholar 

  • Martineau, J., Andersson, F., Barthelemy, C., Cottier, J. P., & Destrieux, C. (2010). Atypical activation of the mirror neuron system during perception of hand motion in autism. Brain Research, 1320, 168–175. https://doi.org/10.1016/j.brainres.2010.01.035

    Article  PubMed  Google Scholar 

  • Martineau, J., Garreau, B., Barthelemy, C., & Lelord, G. (1984). Evoked potentials and P300 during sensory conditioning in autistic children. Annals of the New York Academy of Sciences, 425, 362–369.

    Article  PubMed  Google Scholar 

  • Mayor-Torres, J. M., Clarkson, T., Stepanov, E. A., Luhmann, C. C., Lerner, M. D., & Riccardi, G. (2018). Enhanced error decoding from error-related potentials using convolutional neural networks. In 2018 40th annual international conference of the IEEE engineering in medicine and biology society (EMBC) (pp. 360–363). IEEE.

  • Mazzoni, A., Grove, R., Eapen, V., Lenroot, R. K., & Bruggemann, J. (2019). The promise of functional near-infrared spectroscopy in autism research: what do we know and where do we go? Social Neuroscience, 14(5), 505–518.

    Article  PubMed  Google Scholar 

  • McBride, P. A., Anderson, G. M., Hertzig, M. E., Snow, M. E., Thompson, S. M., Khait, V. D., et al. (1998). Effects of diagnosis, race, and puberty on platelet serotonin levels in autism and mental retardation. Journal of the American Academy of Child and Adolescent Psychiatry, 37(7), 767–776. https://doi.org/10.1097/00004583-199807000-00017

    Article  PubMed  Google Scholar 

  • McClintock, S. M., Reti, I. M., Carpenter, L. L., McDonald, W. M., Dubin, M., Taylor, S. F., et al. (2017). Consensus recommendations for the clinical application of repetitive transcranial magnetic stimulation (rTMS) in the treatment of depression. The Journal of Clinical Psychiatry, 79(1).

  • McPartland, J., Dawson, G., Webb, S. J., Panagiotides, H., & Carver, L. J. (2004). Event-related brain potentials reveal anomalies in temporal processing of faces in autism spectrum disorder. Journal of Child Psychology and Psychiatry, 45(7), 1235–1245. https://doi.org/10.1111/j.1469-7610.2004.00318.x

    Article  PubMed  Google Scholar 

  • McPartland, J. C., Bernier, R. A., Jeste, S. S., Dawson, G., Nelson, C. A., Chawarska, K., et al. (2020). The autism biomarkers consortium for clinical trials (ABC-CT): scientific context, study design, and progress toward biomarker qualification. [Perspective]. Frontiers in Integrative Neuroscience. https://doi.org/10.3389/fnint.2020.00016.

  • Mendez, M. A., Horder, J., Myers, J., Coghlan, S., Stokes, P., Erritzoe, D., et al. (2013). The brain GABA-benzodiazepine receptor alpha-5 subtype in autism spectrum disorder: a pilot [(11)C]Ro15-4513 positron emission tomography study. Neuropharmacology, 68, 195–201. https://doi.org/10.1016/j.neuropharm.2012.04.008

    Article  PubMed  Google Scholar 

  • Menezes, M., Harkins, C., Robinson, M. F., & Mazurek, M. O. (2020). Treatment of depression in individuals with autism spectrum disorder: a systematic review. Research in Autism Spectrum Disorders, 78, 101639.

    Article  Google Scholar 

  • Mihailov, A., Philippe, C., Gloaguen, A., Grigis, A., Laidi, C., Piguet, C., et al. (2020). Cortical signatures in behaviorally clustered autistic traits subgroups: a population-based study. Translational Psychiatry, 10(1), 207. https://doi.org/10.1038/s41398-020-00894-3

    Article  PubMed  PubMed Central  Google Scholar 

  • Milne, E., Scope, A., Pascalis, O., Buckley, D., & Makeig, S. (2009). Independent component analysis reveals atypical electroencephalographic activity during visual perception in individuals with autism. Biological Psychiatry, 65(1), 22–30.

    Article  PubMed  Google Scholar 

  • Monk, C. S., Weng, S. J., Wiggins, J. L., Kurapati, N., Louro, H. M., Carrasco, M., et al. (2010). Neural circuitry of emotional face processing in autism spectrum disorders. Journal of Psychiatry and Neuroscience, 35(2), 105–114.

    Article  PubMed  PubMed Central  Google Scholar 

  • Mori, K., Toda, Y., Ito, H., Mori, T., Mori, K., Goji, A., et al. (2015). Neuroimaging in autism spectrum disorders: 1H-MRS and NIRS study. The Journal of Medical Investigation, 62(1.2), 29–36.

  • Mulder, E. J., Anderson, G. M., Kema, I. P., de Bildt, A., van Lang, N. D., den Boer, J. A., et al. (2004). Platelet serotonin levels in pervasive developmental disorders and mental retardation: diagnostic group differences, within-group distribution, and behavioral correlates. Journal of the American Academy of Child and Adolescent Psychiatry, 43(4), 491–499. https://doi.org/10.1097/00004583-200404000-00016

    Article  PubMed  Google Scholar 

  • Naganawa, M., Li, S., Nabulsi, N. B., Henry, S., Zheng, M.-Q., Pracitto, R., et al. (2020). First-in-human evaluation of 18F-SynVesT-1, a novel radioligand for PET imaging of synaptic vesicle protein 2A. Journal of Nuclear Medicine. https://doi.org/10.2967/jnumed.120.249144

    Article  PubMed  PubMed Central  Google Scholar 

  • Nakadoi, Y., Sumitani, S., Watanabe, Y., Akiyama, M., Yamashita, N., & Ohmori, T. (2012). Multi-channel near-infrared spectroscopy shows reduced activation in the prefrontal cortex during facial expression processing in pervasive developmental disorder. Psychiatry and Clinical Neurosciences, 66(1), 26–33.

    Article  PubMed  Google Scholar 

  • Nakamura, K., Sekine, Y., Ouchi, Y., Tsujii, M., Yoshikawa, E., Futatsubashi, M., et al. (2010). Brain serotonin and dopamine transporter bindings in adults with high-functioning autism. Archives of General Psychiatry, 67(1), 59–68. https://doi.org/10.1001/archgenpsychiatry.2009.137

    Article  PubMed  Google Scholar 

  • Nakatani, C., Ito, J., Nikolaev, A. R., Gong, P., Leeuwen, C., & v. . (2005). Phase synchronization analysis of EEG during attentional blink. Journal of Cognitive Neuroscience, 17(12), 1969–1979.

    Article  PubMed  Google Scholar 

  • Narayanaswami, V., Dahl, K., Bernard-Gauthier, V., Josephson, L., Cumming, P., & Vasdev, N. (2018). Emerging PET radiotracers and targets for imaging of neuroinflammation in neurodegenerative diseases: outlook beyond TSPO. Molecular Imaging, 17, 1536012118792317. https://doi.org/10.1177/1536012118792317

    Article  PubMed  PubMed Central  Google Scholar 

  • Nelson, C. A., & De Haan, M. (1996). Neural correlates of infants’ visual responsiveness to facial expressions of emotion. Developmental Psychobiology, 29(7), 577–595. https://doi.org/10.1002/dev.20532

    Article  PubMed  Google Scholar 

  • Ni, H.-C., Hung, J., Wu, C.-T., Wu, Y.-Y., Chang, C.-J., Chen, R.-S., et al. (2017). The impact of single session intermittent theta-burst stimulation over the dorsolateral prefrontal cortex and posterior superior temporal sulcus on adults with autism spectrum disorder. Frontiers in Neuroscience, 11, 255.

    Article  PubMed  PubMed Central  Google Scholar 

  • Novick, B., Kurtzberg, D., & Vaughn, H. G., Jr. (1979). An electrophysiologic indication of defective information storage in childhood autism. Psychiatry Research, 1(1), 101–108.

    Article  PubMed  Google Scholar 

  • Novick, B., Vaughan, H. G., Jr., Kurtzberg, D., & Simson, R. (1980). An electrophysiologic indication of auditory processing defects in autism. Psychiatry Research, 3(1), 107–114.

    Article  PubMed  Google Scholar 

  • O’Connor, K., Hamm, J. P., & Kirk, I. J. (2005). The neurophysiological correlates of face processing in adults and children with asperger’s syndrome. Brain and Cognition, 59(1), 82–95.

    Article  PubMed  Google Scholar 

  • O’Reilly, C., Lewis, J. D., & Elsabbagh, M. (2017). Is functional brain connectivity atypical in autism? A systematic review of EEG and MEG studies. PLoS ONE, 12(5), e0175870.

    Article  PubMed  PubMed Central  Google Scholar 

  • Oades, R. D., Stern, L. M., Walker, M. K., Clark, C. R., & Kapoor, V. (1990). Event-related potentials and monoamines in autistic children on a clinical trial of fenfluramine. International Journal of Psychophysiology, 8(3), 197–212.

    Article  PubMed  Google Scholar 

  • Oades, R. D., Walker, M. K., Geffen, L. B., & Stern, L. M. (1988). Event-related potentials in autistic and healthy children on an auditory choice reaction time task. International Journal of Psychophysiology, 6(1), 25–37.

    Article  PubMed  Google Scholar 

  • Oberman, L. M., Hubbard, E. M., McCleery, J. P., Altschuler, E. L., Ramachandran, V. S., & Pineda, J. A. (2005). EEG evidence for mirror neuron dysfunction in autism spectrum disorders. Brain Research. Cognitive Brain Research, 24(2), 190–198.

    Article  PubMed  Google Scholar 

  • Okubo, G., Okada, T., Yamamoto, A., Kanagaki, M., Fushimi, Y., Okada, T., et al. (2016). MP2RAGE for deep gray matter measurement of the brain: a comparative study with MPRAGE. Journal of Magnetic Resonance Imaging, 43(1), 55–62. https://doi.org/10.1002/jmri.24960

    Article  PubMed  Google Scholar 

  • Ornitz, E. M., Tanguay, P. E., Lee, J. C., Ritvo, E. R., Sivertsen, B., & Wilson, C. (1972). The effect of stimulus interval on the auditory evoked response during sleep in autistic children. Journal of Autism and Childhood Schizophrenia, 2(2), 140–150.

    Article  PubMed  Google Scholar 

  • Ozonoff, S., & Jensen, J. (1999). Brief report: specific executive function profiles in three neurodevelopmental disorders. Journal of Autism & Developmental Disorders, 29(2), 171–177.

    Article  Google Scholar 

  • Padmanabhan, A., Lynch, C. J., Schaer, M., & Menon, V. (2017). The default mode network in autism. Biol Psychiatry Cogn Neurosci Neuroimaging, 2(6), 476–486. https://doi.org/10.1016/j.bpsc.2017.04.004

    Article  PubMed  PubMed Central  Google Scholar 

  • Pagani, M., Manouilenko, I., Stone-Elander, S., Odh, R., Salmaso, D., Hatherly, R., et al. (2012). Brief report: Alterations in cerebral blood flow as assessed by PET/CT in adults with autism spectrum disorder with normal IQ. Journal of Autism and Developmental Disorders, 42(2), 313–318. https://doi.org/10.1007/s10803-011-1240-y

    Article  PubMed  Google Scholar 

  • Pagnozzi, A. M., Conti, E., Calderoni, S., Fripp, J., & Rose, S. E. (2018). A systematic review of structural MRI biomarkers in autism spectrum disorder: a machine learning perspective. International Journal of Developmental Neuroscience, 71, 68–82. https://doi.org/10.1016/j.ijdevneu.2018.08.010

    Article  PubMed  Google Scholar 

  • Patriquin, M. A., DeRamus, T., Libero, L. E., Laird, A., & Kana, R. K. (2016). Neuroanatomical and neurofunctional markers of social cognition in autism spectrum disorder. Human Brain Mapping, 37(11), 3957–3978. https://doi.org/10.1002/hbm.23288

    Article  PubMed  PubMed Central  Google Scholar 

  • Pedersen, W. S., Muftuler, L. T., & Larson, C. L. (2017). Disentangling the effects of novelty, valence and trait anxiety in the bed nucleus of the stria terminalis, amygdala and hippocampus with high resolution 7T fMRI. NeuroImage, 156, 293–301. https://doi.org/10.1016/j.neuroimage.2017.05.009

    Article  PubMed  Google Scholar 

  • Pellissier, L. P., Gandía, J., Laboute, T., Becker, J. A. J., & Le Merrer, J. (2018). μ opioid receptor, social behaviour and autism spectrum disorder: reward matters. British Journal of Pharmacology, 175(14), 2750–2769. https://doi.org/10.1111/bph.13808

    Article  PubMed  Google Scholar 

  • Pelphrey, K. A., Morris, J. P., McCarthy, G., & Labar, K. S. (2007). Perception of dynamic changes in facial affect and identity in autism. Soc Cogn Affect Neurosci, 2(2), 140–149. https://doi.org/10.1093/scan/nsm010

    Article  PubMed  PubMed Central  Google Scholar 

  • Pelphrey, K. A., Shultz, S., Hudac, C. M., & Vander Wyk, B. C. (2011). Research review: constraining heterogeneity: the social brain and its development in autism spectrum disorder. Journal of Child Psychology and Psychiatry, 52(6), 631–644. https://doi.org/10.1111/j.1469-7610.2010.02349.x

    Article  PubMed  Google Scholar 

  • Peng, Z. W., Chen, J. R., Jin, L. L., Han, H. Y., Dong, C. J., Guo, Y., et al. (2020). Social brain dysfunctionality in individuals with autism spectrum disorder and their first-degree relatives: an activation likelihood estimation meta-analysis. Psychiatry Research-Neuroimaging. https://doi.org/10.1016/j.pscychresns.2020.111063

    Article  PubMed  Google Scholar 

  • Pennington, B. F., & Ozonoff, S. (1996). Executive functions and developmental psychopathology. Journal of Child Psychology & Psychiatry & Allied Disciplines, 37(1), 51–87.

    Article  Google Scholar 

  • Picci, G., Gotts, S. J., & Scherf, K. S. (2016). A theoretical rut: revisiting and critically evaluating the generalized under/over-connectivity hypothesis of autism. Developmental Science, 19(4), 524–549. https://doi.org/10.1111/desc.12467

    Article  PubMed  Google Scholar 

  • Pineda, J., Brang, D., Hecht, E., Edwards, L., Carey, S., Bacon, M., et al. (2008). Positive behavioral and electrophysiological changes following neurofeedback training in children with autism. Research in Autism Spectrum Disorders, 2(3), 557–581.

    Article  Google Scholar 

  • Poulin-Lord, M. P., Barbeau, E. B., Soulieres, I., Monchi, O., Doyon, J., Benali, H., et al. (2014). Increased topographical variability of task-related activation in perceptive and motor associative regions in adult autistics. Neuroimage Clin, 4, 444–453. https://doi.org/10.1016/j.nicl.2014.02.008

    Article  PubMed  PubMed Central  Google Scholar 

  • Power, J. D., Barnes, K. A., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E. (2012). Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. NeuroImage, 59(3), 2142–2154. https://doi.org/10.1016/j.neuroimage.2011.10.018

    Article  PubMed  Google Scholar 

  • Ragert, P., Franzkowiak, S., Schwenkreis, P., Tegenthoff, M., & Dinse, H. R. (2008). Improvement of tactile perception and enhancement of cortical excitability through intermittent theta burst rTMS over human primary somatosensory cortex. Experimental Brain Research, 184(1), 1–11. https://doi.org/10.1007/s00221-007-1073-2

    Article  PubMed  Google Scholar 

  • Rane, P., Cochran, D., Hodge, S. M., Haselgrove, C., Kennedy, D. N., & Frazier, J. A. (2015). Connectivity in autism: a review of MRI connectivity studies. Harvard Review of Psychiatry, 23(4), 223–244. https://doi.org/10.1097/Hrp.0000000000000072

    Article  PubMed  PubMed Central  Google Scholar 

  • Rimland, B. (1964). Infantile autism.

  • Ritvo, E. R., Ornitz, E. M., Walter, R. D., & Hanley, J. (1970). Correlation of psychiatric diagnoses and EEG findings: a double-blind study of 184 hospitalized children. American Journal of Psychiatry, 126(7), 988–996.

    Article  PubMed  Google Scholar 

  • Rosenblau, G., Kliemann, D., Dziobek, I., & Heekeren, H. R. (2017). Emotional prosody processing in autism spectrum disorder. Soc Cogn Affect Neurosci, 12(2), 224–239. https://doi.org/10.1093/scan/nsw118

    Article  PubMed  Google Scholar 

  • Rounis, E., Lee, L., Siebner, H. R., Rowe, J. B., Friston, K. J., Rothwell, J. C., et al. (2005). Frequency specific changes in regional cerebral blood flow and motor system connectivity following rTMS to the primary motor cortex. NeuroImage, 26(1), 164–176. https://doi.org/10.1016/j.neuroimage.2005.01.037

    Article  PubMed  Google Scholar 

  • Rubenstein, J. L., & Merzenich, M. M. (2003). Model of autism: increased ratio of excitation/inhibition in key neural systems. Genes, Brain, and Behavior, 2(5), 255–267. https://doi.org/10.1034/j.1601-183x.2003.00037.x

    Article  PubMed  PubMed Central  Google Scholar 

  • Rutter, M. (1968). Concepts of autism: a review of research. Journal of Child Psychology and Psychiatry, 9(1), 1–25.

    Article  PubMed  Google Scholar 

  • Sahi, A., Rai, P., Oh, S., Ramasamy, M., Harbaugh, R. E., & Varadan, V. K. (2014). Neural activity based biofeedback therapy for autism spectrum disorder through wearable wireless textile EEG monitoring system. In Nanosensors, biosensors, and info-tech sensors and systems 2014 (Vol. 9060, pp. 90600D). International Society for Optics and Photonics.

  • Salomons, T. V., Dunlop, K., Kennedy, S. H., Flint, A., Geraci, J., Giacobbe, P., et al. (2014). Resting-state cortico-thalamic-striatal connectivity predicts response to dorsomedial prefrontal rTMS in major depressive disorder. Neuropsychopharmacology, 39(2), 488–498.

    Article  PubMed  Google Scholar 

  • Saran, P. K., & Pirouz, M. (2020). EEG analysis for predicting early autism spectrum disorder traits. In Proceedings of the future technologies conference (pp. 658–675). Springer.

  • Sato, W., & Uono, S. (2019). The atypical social brain network in autism: advances in structural and functional MRI studies. Current Opinion in Neurology, 32(4), 617–621. https://doi.org/10.1097/Wco.0000000000000713

    Article  PubMed  Google Scholar 

  • Schain, R. J., & Freedman, D. X. (1961). Studies on 5-hydroxyindole metabolism in autistic and other mentally retarded children. The Journal of Pediatrics, 58(3), 315–320.

    Article  PubMed  Google Scholar 

  • Schain, R. J., & Yannet, H. (1960). Infantile autism: an analysis of 50 cases and a consideration of certain relevant neurophysiologic concepts. The Journal of Pediatrics, 57(4), 560–567.

    Article  PubMed  Google Scholar 

  • Scholkmann, F., Kleiser, S., Metz, A. J., Zimmermann, R., Pavia, J. M., Wolf, U., et al. (2014). A review on continuous wave functional near-infrared spectroscopy and imaging instrumentation and methodology. NeuroImage, 85, 6–27.

    Article  PubMed  Google Scholar 

  • Seymour, R. A., Rippon, G., Gooding-Williams, G., Sowman, P. F., & Kessler, K. (2020). Reduced auditory steady state responses in autism spectrum disorder. Mol Autism, 11(1), 1–13.

    Article  Google Scholar 

  • Shen, M. D. (2018). Cerebrospinal fluid and the early brain development of autism. Journal of Neurodevelopmental Disorders. https://doi.org/10.1186/s11689-018-9256-7

    Article  PubMed  PubMed Central  Google Scholar 

  • Siegel, B. V., Jr., Nuechterlein, K. H., Abel, L., Wu, J. C., & Buchsbaum, M. S. (1995). Glucose metabolic correlates of continuous performance test performance in adults with a history of infantile autism, schizophrenics, and controls. Schizophrenia Research, 17(1), 85–94.

    Article  PubMed  Google Scholar 

  • Sinha, N., Maszczyk, T., Wanxuan, Z., Tan, J., & Dauwels, J. (2016). EEG hyperscanning study of inter-brain synchrony during cooperative and competitive interaction. In 2016 IEEE international conference on systems, man, and cybernetics (SMC) (pp. 004813–004818). IEEE.

  • Small, J. G. (1975). EEG and neurophysiological studies of early infantile autism. Biological Psychiatry, 10(4), 385–397.

    PubMed  Google Scholar 

  • Small, J. G., DeMyer, M. K., & Milstein, V. (1971). CNV responses of autistic and normal children. Journal of Autism and Childhood Schizophrenia, 1(2), 215–231.

    Article  PubMed  Google Scholar 

  • Small, J. G., Milstein, V., DeMyer, M. K., & Moore, J. E. (1977). Electroencephalographic (EEG) and clinical studies of early infantile autism. Clinical Electroencephalography, 8(1), 27–35.

    Article  Google Scholar 

  • Smith, S. M., & Nichols, T. E. (2018). Statistical challenges in “big data’’’ human neuroimaging.” Neuron, 97(2), 263–268. https://doi.org/10.1016/j.neuron.2017.12.018

    Article  PubMed  Google Scholar 

  • Sokhadze, E., Baruth, J., Tasman, A., Mansoor, M., Ramaswamy, R., Sears, L., et al. (2010). Low-frequency repetitive transcranial magnetic stimulation (rTMS) affects event-related potential measures of novelty processing in autism. Applied Psychophysiology and Biofeedback, 35(2), 147–161. https://doi.org/10.1007/s10484-009-9121-2

    Article  PubMed  PubMed Central  Google Scholar 

  • Sokhadze, E., Casanova, M., El-Baz, A., Farag, H. E., Li, X., & Wang, Y. (2016). TMS-based neuromodulation of evoked and induced gamma oscillations and event-related potentials in children with autism. NeuroRegulation, 3(3), 101–126. https://doi.org/10.15540/nr.3.3.101

    Article  Google Scholar 

  • Sokhadze, E. M., El-Baz, A., Baruth, J., Mathai, G., Sears, L., & Casanova, M. F. (2009). Effects of low frequency repetitive transcranial magnetic stimulation (rTMS) on gamma frequency oscillations and event-related potentials during processing of illusory figures in autism. Journal of Autism and Developmental Disorders, 39(4), 619–634. https://doi.org/10.1007/s10803-008-0662-7PMID-19030976

    Article  PubMed  Google Scholar 

  • Sokhadze, E. M., El-Baz, A. S., Tasman, A., Sears, L. L., Wang, Y., Lamina, E. V., et al. (2014). Neuromodulation Integrating rTMS and Neurofeedback for the Treatment of Autism Spectrum Disorder: An Exploratory Study. Applied Psychophysiology and Biofeedback, 39(3–4), 237–257.

    Article  PubMed  PubMed Central  Google Scholar 

  • Sokhadze, E. M., Lamina, E. V., Casanova, E. L., Kelly, D. P., Opris, I., Tasman, A., et al. (2018). Exploratory study of rTMS neuromodulation effects on electrocortical functional measures of performance in an oddball test and behavioral symptoms in autism. Frontiers in Systems Neuroscience. https://doi.org/10.3389/fnsys.2018.00020

    Article  PubMed  PubMed Central  Google Scholar 

  • Sokhadze, G., Casanova, M., Kelly, D., Casanova, E., Russell, B., & Sokhadze, E. (2017). Neuromodulation based on rTMS affects behavioral measures and autonomic nervous system activity in children with autism. NeuroRegulation, 4(2), 65–78. https://doi.org/10.15540/nr.4.2.65

    Article  Google Scholar 

  • Solomon, M., Ozonoff, S. J., Ursu, S., Ravizza, S., Cummings, N., Ly, S., et al. (2009). The neural substrates of cognitive control deficits in autism spectrum disorders. Neuropsychologia, 47(12), 2515–252604.019.

  • Strang, J. F., van der Miesen, A. I. R., Caplan, R., Hughes, C., daVanport, S., & Lai, M. C. (2020). Both sex- and gender-related factors should be considered in autism research and clinical practice. Autism, 24(3), 539–543. https://doi.org/10.1177/1362361320913192

    Article  PubMed  Google Scholar 

  • Su, W.-C., Culotta, M., Mueller, J., Tsuzuki, D., Pelphrey, K., & Bhat, A. (2020a). Differences in cortical activation patterns during action observation, action execution, and interpersonal synchrony between children with or without autism spectrum disorder (ASD): An fNIRS pilot study. PLoS ONE, 15(10), e0240301.

    Article  PubMed  PubMed Central  Google Scholar 

  • Su, W.-C., Culotta, M. L., Hoffman, M. D., Trost, S. L., Pelphrey, K. A., Tsuzuki, D., et al. (2020b). Developmental differences in cortical activation during action observation, action execution and interpersonal synchrony: an fNIRS study. Frontiers in Human Neuroscience, 14, 57.

    Article  PubMed  PubMed Central  Google Scholar 

  • Sutoko, S., Sato, H., Maki, A., Kiguchi, M., Hirabayashi, Y., Atsumori, H., et al. (2016). Tutorial on platform for optical topography analysis tools. Neurophotonics, 3(1), 010801.

    Article  PubMed  PubMed Central  Google Scholar 

  • Suzuki, K., Sugihara, G., Ouchi, Y., Nakamura, K., Futatsubashi, M., Takebayashi, K., et al. (2013). Microglial activation in young adults with autism spectrum disorder. JAMA Psychiatry, 70(1), 49–58. https://doi.org/10.1001/jamapsychiatry.2013.272

    Article  PubMed  Google Scholar 

  • Taft, L., & Cohen, H. (1971). Hypsarrhythmia and infantile autism: a clinical report. Journal of Autism and Childhood Schizophrenia, 1(3), 327–336.

    Article  PubMed  Google Scholar 

  • Tak, S., & Ye, J. C. (2014). Statistical analysis of fNIRS data: a comprehensive review. NeuroImage, 85, 72–91.

    Article  PubMed  Google Scholar 

  • Thabtah, F. (2019). Machine learning in autistic spectrum disorder behavioral research: a review and ways forward. Informatics for Health and Social Care, 44(3), 278–297.

    Article  PubMed  Google Scholar 

  • Tokuda, T., Yoshimoto, J., Shimizu, Y., Okada, G., Takamura, M., Okamoto, Y., et al. (2018). Identification of depression subtypes and relevant brain regions using a data-driven approach. Scientific Reports. https://doi.org/10.1038/s41598-018-32521-z

    Article  PubMed  PubMed Central  Google Scholar 

  • Townsend, J., Westerfield, M., Leaver, E., Makeig, S., Jung, T., Pierce, K., et al. (2001). Event-related brain response abnormalities in autism: evidence for impaired cerebello-frontal spatial attention networks. Cognitive Brain Research, 11(1), 127–145.

    Article  PubMed  Google Scholar 

  • Tsuzuki, D., & Dan, I. (2014). Spatial registration for functional near-infrared spectroscopy: from channel position on the scalp to cortical location in individual and group analyses. NeuroImage, 85, 92–103.

    Article  PubMed  Google Scholar 

  • Tuchman, R., Cuccaro, M., & Alessandri, M. (2010). Autism and epilepsy: historical perspective. Brain and Development, 32(9), 709–718.

    Article  PubMed  Google Scholar 

  • Turner, A. H., Greenspan, K. S., & van Erp, T. G. M. (2016). Pallidum and lateral ventricle volume enlargement in autism spectrum disorder. Psychiatry Research-Neuroimaging, 252, 40–45. https://doi.org/10.1016/j.pscychresns.2016.04.003

    Article  PubMed  PubMed Central  Google Scholar 

  • Tye, C., Mercure, E., Ashwood, K. L., Azadi, B., Asherson, P., Johnson, M. H., et al. (2013). Neurophysiological responses to faces and gaze direction differentiate children with ASD, ADHD and ASD+ADHD. Developmental Cognitive Neuroscience, 5, 71–85. https://doi.org/10.1016/j.dcn.2013.01.001

    Article  PubMed  PubMed Central  Google Scholar 

  • van Noordt, S., Wu, J., Venkataraman, A., Larson, M. J., South, M., & Crowley, M. J. (2017). Inter-trial coherence of medial frontal theta oscillations linked to differential feedback processing in youth and young adults with autism. Research in Autism Spectrum Disorders, 37, 1–10.

    Article  PubMed  PubMed Central  Google Scholar 

  • Vlamings, P. H., Jonkman, L. M., Hoeksma, M. R., van Engeland, H., & Kemner, C. (2008). Reduced error monitoring in children with autism spectrum disorder: an ERP study. European Journal of Neuroscience, 28(2), 399–406. https://doi.org/10.1111/j.1460-9568.2008.06336.x

    Article  PubMed  Google Scholar 

  • Webb, S. J., Dawson, G., Bernier, R., & Panagiotides, H. (2006). ERP evidence of atypical face processing in young children with autism. Journal of Autism and Developmental Disorders, 36(7), 881–890. https://doi.org/10.1007/s10803-006-0126-x

    Article  PubMed  PubMed Central  Google Scholar 

  • Webb, S. J., Jones, E. J., Merkle, K., Venema, K., Greenson, J., Murias, M., et al. (2011). Developmental change in the ERP responses to familiar faces in toddlers with autism spectrum disorders versus typical development. [Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't]. Child Development, 82(6), 1868–1886. https://doi.org/10.1111/j.1467-8624.2011.01656.x

  • Webb, S. J., Long, J. D., & Nelson, C. A. (2005). A longitudinal investigation of visual event-related potentials in the first year of life. Developmental Science, 8(6), 605–616. https://doi.org/10.1111/j.1467-7687.2005.00452.x

    Article  PubMed  Google Scholar 

  • Webb, S. J., & Nelson, C. A. (2001). Perceptual priming for upright and inverted faces in infants and adults. Journal of Experimental Child Psychology, 79(1), 1–22.

    Article  PubMed  Google Scholar 

  • White, P. T., DeMyer, W., & DeMyer, M. (1964). EEG abnormalities in early childhood schizophrenia: a double-blind study of psychiatrically disturbed and normal children during promazine sedation. American Journal of Psychiatry, 120(10), 950–958.

    Article  PubMed  Google Scholar 

  • White, T., Blok, E., & Calhoun, V. D. (2020). Data sharing and privacy issues in neuroimaging research: opportunities, obstacles, challenges, and monsters under the bed. Human Brain Mapping. https://doi.org/10.1002/hbm.25120

    Article  PubMed  PubMed Central  Google Scholar 

  • Whitehouse, A. J. O., & Bishop, D. V. M. (2008). Do children with autism ‘switch off’ to speech sounds? An investigation using event-related potentials. Developmental Science, 11(4), 516–524.

    Article  PubMed  Google Scholar 

  • Wolff, J. J., Gerig, G., Lewis, J. D., Soda, T., Styner, M. A., Vachet, C., et al. (2015). Altered corpus callosum morphology associated with autism over the first 2 years of life. Brain, 138(7), 2046–2058.

    Article  PubMed  PubMed Central  Google Scholar 

  • Wong, T., Fung, P., Chua, S., & McAlonan, G. (2008). Abnormal spatiotemporal processing of emotional facial expressions in childhood autism: dipole source analysis of event-related potentials. European Journal of Neuroscience, 28(2), 407–416. https://doi.org/10.1111/j.1460-9568.2008.06328.x

    Article  PubMed  Google Scholar 

  • Xu, L., Geng, X., He, X., Li, J., & Yu, J. (2019). Prediction in autism by deep learning short-time spontaneous hemodynamic fluctuations. Frontiers in Neuroscience, 13, 1120.

    Article  PubMed  PubMed Central  Google Scholar 

  • Xu, L., Liu, Y., Yu, J., Li, X., Yu, X., Cheng, H., et al. (2020). Characterizing autism spectrum disorder by deep learning spontaneous brain activity from functional near-infrared spectroscopy. Journal of Neuroscience Methods, 331, 108538.

    Article  PubMed  Google Scholar 

  • Yang, H., & Chen, C. (2008). Cyclooxygenase-2 in synaptic signaling. Current Pharmaceutical Design, 14(14), 1443–1451. https://doi.org/10.2174/138161208784480144

    Article  PubMed  PubMed Central  Google Scholar 

  • Yang, X., Si, T. J., Gong, Q. Y., Qiu, L. H., Jia, Z. Y., Zhou, M., et al. (2016). Brain gray matter alterations and associated demographic profiles in adults with autism spectrum disorder: a meta-analysis of voxel-based morphometry studies. Australian and New Zealand Journal of Psychiatry, 50(8), 741–753. https://doi.org/10.1177/0004867415623858

    Article  PubMed  Google Scholar 

  • Ye, J. C., Tak, S., Jang, K. E., Jung, J., & Jang, J. (2009). NIRS-SPM: statistical parametric mapping for near-infrared spectroscopy. NeuroImage, 44(2), 428–447.

    Article  PubMed  Google Scholar 

  • Yerys, B. E., Antezana, L., Weinblatt, R., Jankowski, K. F., Strang, J., Vaidya, C. J., et al. (2015). Neural correlates of set-shifting in children with autism. Autism Research, 8(4), 386–397. https://doi.org/10.1002/aur.1454

    Article  PubMed  PubMed Central  Google Scholar 

  • Yeung, M. K., Lee, T. L., & Chan, A. S. (2019). Frontal lobe dysfunction underlies the differential word retrieval impairment in adolescents with high-functioning autism. Autism Research, 12(4), 600–613.

    Article  PubMed  Google Scholar 

  • Yu, L., Wang, S., Huang, D., Wu, X., & Zhang, Y. (2018). Role of inter-trial phase coherence in atypical auditory evoked potentials to speech and nonspeech stimuli in children with autism. Clinical Neurophysiology, 129(7), 1374–1382.

    Article  PubMed  Google Scholar 

  • Yücel, M. A., Selb, J. J., Huppert, T. J., Franceschini, M. A., & Boas, D. A. (2017). Functional near infrared spectroscopy: enabling routine functional brain imaging. Current Opinion in Biomedical Engineering, 4, 78–86.

    Article  PubMed  PubMed Central  Google Scholar 

  • Zantomio, D., Chana, G., Laskaris, L., Testa, R., Everall, I., Pantelis, C., et al. (2015). Convergent evidence for mGluR5 in synaptic and neuroinflammatory pathways implicated in ASD. Neuroscience and Biobehavioral Reviews, 52, 172–177. https://doi.org/10.1016/j.neubiorev.2015.02.006

    Article  PubMed  Google Scholar 

  • Zhang, F., & Roeyers, H. (2019). Exploring brain functions in autism spectrum disorder: a systematic review on functional near-infrared spectroscopy (fNIRS) studies. International Journal of Psychophysiology, 137, 41–53.

    Article  PubMed  Google Scholar 

  • Zhang, J., Jadavji, Z., Zewdie, E., & Kirton, A. (2019). Evaluating if children can use simple brain computer interfaces. Frontiers in Human Neuroscience, 13, 24.

    Article  PubMed  PubMed Central  Google Scholar 

  • Zhu, H., Fan, Y., Guo, H., Huang, D., & He, S. (2014). Reduced interhemispheric functional connectivity of children with autism spectrum disorder: evidence from functional near infrared spectroscopy studies. Biomedical Optics Express, 5(4), 1262–1274.

    Article  PubMed  PubMed Central  Google Scholar 

  • Zilbovicius, M., Boddaert, N., Belin, P., Poline, J. B., Remy, P., Mangin, J. F., et al. (2000). Temporal lobe dysfunction in childhood autism: a PET study. Positron Emission Tomography. Am J Psychiatry, 157(12), 1988–1993. https://doi.org/10.1176/appi.ajp.157.12.1988

    Article  PubMed  Google Scholar 

  • Zivoder, I., Martic-Biocina, S., Kosic, A., & Bosak, J. (2015). Neurofeedback application in the treatment of autistic spectrum disorders (ASD). Psychiatria Danubina, 27(1), 391–394.

    Google Scholar 

  • Zürcher, N. R., Loggia, M. L., Mullett, J. E., Tseng, C., Bhanot, A., Richey, L., et al. (2020). [11C]PBR28 MR–PET imaging reveals lower regional brain expression of translocator protein (TSPO) in young adult males with autism spectrum disorder. Molecular Psychiatry. https://doi.org/10.1038/s41380-020-0682-z

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgments

Support was provided by the Hilibrand Foundation (JM, DT), Alan B. Slifka Foundation (JM), NIMH U19 MH108206 (JM), NIMH R01 MH100173 (JM), NIMH R01 MH107426 (JM), NIMH R01 MH111629 (JM), NIMH R21 MH122202 (JM), NIMH R21 MH113955 (DM, JM), NARSAD Young Investigator Award Grant from the Brain & Behavior Foundation ID 27542 (DM), NICHD R03 HD100771 (AJ), NIMH R01 MH100028 (AJ), George Mason Department of Psychology (AJ, GAM), Stony Brook Renaissance School of Medicine (MDL), Autism Research Institute (MDL), Society of Clinical Child and Adolescent Psychology (MDL), NIMH R01 MH114906 (MDL), NIMH R01 MH110585 (MDL), Autism Speaks Postdoctoral Fellowship POID 11808 (GAM), Dana Foundation (AB), NIH NIGMS IDEA P20 GM103446 (AB), F31MH122091 (TC), the Temple University Public Policy Lab Graduate Fellowship (TC), the American Psychological Association (APA) Dissertation Research Award (TC), and the Dr. Phillip J Bersh Memorial Student Award (TC).

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JM and ML contributed to manuscript design. All authors contributed to writing and editing the manuscript, and all authors approved the final manuscript.

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JM consults with Customer Value Partners, Bridgebio, Determined Health, and BlackThorn Therapeutics, has received research funding from Janssen Research and Development, serves on the Scientific Advisory Boards of Pastorus and Modern Clinics, and receives royalties from Guilford Press, Lambert, and Springer.

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McPartland, J.C., Lerner, M.D., Bhat, A. et al. Looking Back at the Next 40 Years of ASD Neuroscience Research. J Autism Dev Disord 51, 4333–4353 (2021). https://doi.org/10.1007/s10803-021-05095-5

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  • DOI: https://doi.org/10.1007/s10803-021-05095-5

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