Baio J, Wiggins L, Christensen DL, Maenner MJ, Daniels J, Warren Z, et al. Prevalence of autism spectrum disorder among children aged 8 years—autism and developmental disabilities monitoring network, 11 sites, United States, 2014. MMWR Surveillance Summaries. 2018;67(6):1.

Wasilewska J, Klukowski M. Gastrointestinal symptoms and autism spectrum disorder: links and risks–a possible new overlap syndrome. Pediatric health, medicine and therapeutics. 2015;6:153.

Sabbagh HJ, Al-Jabri BA, Alsulami MA, Hashem LA, Aljubour AA, Alamoudi RA. Prevalence and characteristics of autistic children attending autism centres in 2 major cities in Saudi Arabia: A cross-sectional study. Saudi Medical Journal. 2021;42(4):419.

Dekhil O, Hajjdiab H, Shalaby A, Ali MT, Ayinde B, Switala A, et al. Using resting state functional mri to build a personalized autism diagnosis system. PloS one. 2018;13(10):e0206351.

Akhavan Aghdam M, Sharifi A, Pedram MM. Combination of rs-fMRI and sMRI data to discriminate autism spectrum disorders in young children using deep belief network. Journal of digital imaging. 2018;31(6):895-903.

Yerys BE, Pennington BF. How do we establish a biological marker for a behaviorally defined disorder? Autism as a test case. Wiley Online Library; 2011. p. 239-41.

Frye RE, Vassall S, Kaur G, Lewis C, Karim M, Rossignol D. Emerging biomarkers in autism spectrum disorder: a systematic review. Annals of translational medicine. 2019;7(23).

Tanner A, Dounavi K. The emergence of autism symptoms prior to 18 months of age: A systematic literature review. Journal of autism and developmental disorders. 2021;51(3):973-93.

Taberna GA, Samogin J, Mantini D. Automated head tissue modelling based on structural magnetic resonance images for electroencephalographic source reconstruction. Neuroinformatics. 2021;19(4):585-96.

Fischl B. FreeSurfer. NeuroImage. 2012;62(2):774-81.

Hashem S, Nisar S, Bhat AA, Yadav SK, Azeem MW, Bagga P, et al. Genetics of structural and functional brain changes in autism spectrum disorder. Translational Psychiatry. 2020;10(1):1-17.

Zhao X, Zhu S, Cao Y, Cheng P, Lin Y, Sun Z, et al. Abnormalities of Gray Matter Volume and Its Correlation with Clinical Symptoms in Adolescents with High-Functioning Autism Spectrum Disorder. Neuropsychiatr Dis Treat. 2022;18:717-30.

Riddle K, Cascio CJ, Woodward ND. Brain structure in autism: a voxel-based morphometry analysis of the Autism Brain Imaging Database Exchange (ABIDE). Brain imaging and behavior. 2017;11:541-51.

Lange N, Travers BG, Bigler ED, Prigge MB, Froehlich AL, Nielsen JA, et al. Longitudinal volumetric brain changes in autism spectrum disorder ages 6-35 years. Autism research : official journal of the International Society for Autism Research. 2015;8(1):82-93.

Courchesne E, Bartholomeusz H, Karns C, Townsend J. MRI and head circumference evidence of abnormal brain enlargement in young but not adult autistic patients. Biol Psychiatry.

Ni H-C, Lin H-Y, Tseng W-YI, Chiu Y-N, Wu Y-Y, Tsai W-C, et al. Neural correlates of impaired self-regulation in male youths with autism spectrum disorder: A voxel-based morphometry study. Progress in neuro-psychopharmacology and biological psychiatry. 2018;82:233-41.

Sato W, Kochiyama T, Uono S, Yoshimura S, Kubota Y, Sawada R, et al. Reduced gray matter volume in the social brain network in adults with autism spectrum disorder. Frontiers in human neuroscience. 2017;11:395.

Hanaie R, Mohri I, Kagitani‐Shimono K, Tachibana M, Matsuzaki J, Hirata I, et al. White matter volume in the brainstem and inferior parietal lobule is related to motor performance in children with autism spectrum disorder: A voxel‐based morphometry study. Autism Research. 2016;9(9):981-92.

Duerden EG, Mak‐Fan KM, Taylor MJ, Roberts SW. Regional differences in grey and white matter in children and adults with autism spectrum disorders: An activation likelihood estimate (ALE) meta‐analysis. Autism Research. 2012;5(1):49-66.

Zhao X, Zhu S, Cao Y, Cheng P, Lin Y, Sun Z, et al. Abnormalities of Gray Matter Volume and Its Correlation with Clinical Symptoms in Adolescents with High-Functioning Autism Spectrum Disorder. Neuropsychiatric Disease and Treatment. 2022;18:717.

Haar S, Berman S, Behrmann M, Dinstein I. Anatomical abnormalities in autism? Cerebral cortex. 2016;26(4):1440-52.

Zielinski BA, Prigge MB, Nielsen JA, Froehlich AL, Abildskov TJ, Anderson JS, et al. Longitudinal changes in cortical thickness in autism and typical development. Brain. 2014;137(6):1799-812.

Nunes AS, Vakorin VA, Kozhemiako N, Peatfield N, Ribary U, Doesburg SM. Atypical age-related changes in cortical thickness in autism spectrum disorder. Scientific reports. 2020;10(1):1-15.

Jiao Y, Chen R, Ke X, Chu K, Lu Z, Herskovits EH. Predictive models of autism spectrum disorder based on brain regional cortical thickness. NeuroImage. 2010;50(2):589-99.

Khundrakpam BS, Lewis JD, Kostopoulos P, Carbonell F, Evans AC. Cortical thickness abnormalities in autism spectrum disorders through late childhood, adolescence, and adulthood: a large-scale MRI study. Cerebral Cortex. 2017;27(3):1721-31.

Bethlehem RA, Seidlitz J, Romero-Garcia R, Trakoshis S, Dumas G, Lombardo MV. A normative modelling approach reveals age-atypical cortical thickness in a subgroup of males with autism spectrum disorder. Communications biology. 2020;3(1):1-10.

Mei T, Llera A, Floris DL, Forde NJ, Tillmann J, Durston S, et al. Gray matter covariations and core symptoms of autism: the EU-AIMS Longitudinal European Autism Project. Molecular autism. 2020;11(1):1-13.

Maier S, van Elst LT, Perlov E, Düppers AL, Nickel K, Fangmeier T, et al. Cortical properties of adults with autism spectrum disorder and an IQ> 100. Psychiatry Research: Neuroimaging. 2018;279:8-13.

Mishra M, Pati UC. Autism detection using surface and volumetric morphometric feature of sMRI with Machine learning approach. 2021.

Seiger R, Ganger S, Kranz GS, Hahn A, Lanzenberger R. Cortical thickness estimations of FreeSurfer and the CAT12 toolbox in patients with Alzheimer's disease and healthy controls. Journal of Neuroimaging. 2018;28(5):515-23.

Maisel H, Eack S. Psychiatric Comorbidity and Neuromorphometry in Adults With Autism Spectrum Disorder. Biological Psychiatry. 2020;87(9):S326-S7.

Wolff N, Stroth S, Kamp-Becker I, Roepke S, Roessner V. Autism Spectrum Disorder and IQ–A Complex Interplay. Frontiers in Psychiatry. 2022;13:856084.

Chan W, Smith LE, Hong J, Greenberg JS, Mailick MR. Validating the social responsiveness scale for adults with autism. Autism Research. 2017;10(10):1663-71.

Ganji Z, Hakak MA, Zamanpour SA, Zare H. Automatic Detection of Focal Cortical Dysplasia Type II in MRI: Is the Application of Surface-Based Morphometry and Machine Learning Promising? Frontiers in Human Neuroscience. 2021;15.

Ganji Z, Aghaee Hakak M, Zare H. Comparison of machine learning methods for the detection of focal cortical dysplasia lesions: decision tree, support vector machine and artificial neural network. Neurological research. 2022;44(12):1142-9.

Ashburner J, Friston KJ. Unified segmentation. NeuroImage. 2005;26(3):839-51.

Klein A, Andersson J, Ardekani BA, Ashburner J, Avants B, Chiang MC, et al. Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration. NeuroImage. 2009;46(3):786-802.

Ay U, Kizilates-Evin G, Bayram A, Kurt E, Demiralp T. Comparison of FreeSurfer and CAT12 Software in Parcel-Based Cortical Thickness Calculations. Brain topography. 2022;35(5-6):572-82.

Yotter RA, Dahnke R, Thompson PM, Gaser C. Topological correction of brain surface meshes using spherical harmonics. Hum Brain Mapp. 2011;32(7):1109-24.

Khadem-Reza ZK, Zare H. Evaluation of brain structure abnormalities in children with autism spectrum disorder (ASD) using structural magnetic resonance imaging. The Egyptian Journal of Neurology, Psychiatry and Neurosurgery. 2022;58(1):1-14.

Desikan RS, Ségonne F, Fischl B, Quinn BT, Dickerson BC, Blacker D, et al. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. NeuroImage. 2006;31(3):968-80.

Hammers A, Allom R, Koepp MJ, Free SL, Myers R, Lemieux L, et al. Three‐dimensional maximum probability atlas of the human brain, with particular reference to the temporal lobe. Human brain mapping. 2003;19(4):224-47.

Desikan RS, Ségonne F, Fischl B, Quinn BT, Dickerson BC, Blacker D, et al. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. NeuroImage. 2006;31(3):968-80.

Greimel E, Nehrkorn B, Schulte-Rüther M, Fink GR, Nickl-Jockschat T, Herpertz-Dahlmann B, et al. Changes in grey matter development in autism spectrum disorder. Brain Structure and Function. 2013;218(4):929-42.

Uddin LQ, Supekar K, Menon V. Reconceptualizing functional brain connectivity in autism from a developmental perspective. Frontiers in human neuroscience. 2013;7:458.

O'Hearn K, Larsen B, Fedor J, Luna B, Lynn A. Representational similarity analysis reveals atypical age-related changes in brain regions supporting face and car recognition in autism. NeuroImage. 2020;209:116322.

Murphy CM, Deeley Q, Daly E, Ecker C, O'brien F, Hallahan B, et al. Anatomy and aging of the amygdala and hippocampus in autism spectrum disorder: an in vivo magnetic resonance imaging study of Asperger syndrome. Autism Research. 2012;5(1):3-12.

Yang DY-J, Beam D, Pelphrey KA, Abdullahi S, Jou RJ. Cortical morphological markers in children with autism: a structural magnetic resonance imaging study of thickness, area, volume, and gyrification. Molecular autism. 2016;7(1):1-14.

Riddle K, Cascio CJ, Woodward ND. Brain structure in autism: a voxel-based morphometry analysis of the Autism Brain Imaging Database Exchange (ABIDE). Brain imaging and behavior. 2017;11(2):541-51.

Kucharsky Hiess R, Alter R, Sojoudi S, Ardekani B, Kuzniecky R, Pardoe H. Corpus callosum area and brain volume in autism spectrum disorder: quantitative analysis of structural MRI from the ABIDE database. Journal of autism and developmental disorders. 2015;45(10):3107-14.

Katuwal GJ, Baum SA, Michael AM. Early brain imaging can predict autism: Application of machine learning to a clinical imaging archive. BioRxiv. 2018:471169.

Xiao Z, Qiu T, Ke X, Xiao X, Xiao T, Liang F, et al. Autism spectrum disorder as early neurodevelopmental disorder: Evidence from the brain imaging abnormalities in 2–3 years old toddlers. Journal of autism and developmental disorders. 2014;44(7):1633-40.

Katuwal GJ, Baum SA, Cahill ND, Dougherty CC, Evans E, Evans DW, et al. Inter-method discrepancies in brain volume estimation may drive inconsistent findings in autism. Frontiers in neuroscience. 2016;10:439.

D'Mello AM, Crocetti D, Mostofsky SH, Stoodley CJ. Cerebellar gray matter and lobular volumes correlate with core autism symptoms. NeuroImage Clinical. 2015;7:631-9.

Hoffmann E, Brück C, Kreifelts B, Ethofer T, Wildgruber D. Reduced functional connectivity to the frontal cortex during processing of social cues in autism spectrum disorder. Journal of Neural Transmission. 2016;123(8):937-47.

Xu J, Wang C, Xu Z, Li T, Chen F, Chen K, et al. Specific functional connectivity patterns of middle temporal gyrus subregions in children and adults with autism spectrum disorder. Autism Research. 2020;13(3):410-22.

Sato W, Uono S. The atypical social brain network in autism: advances in structural and functional MRI studies. Current Opinion in Neurology. 2019;32(4):617-21.

Cauda F, Geda E, Sacco K, D'Agata F, Duca S, Geminiani G, et al. Grey matter abnormality in autism spectrum disorder: an activation likelihood estimation meta-analysis study. Journal of Neurology, Neurosurgery & Psychiatry. 2011;82(12):1304-13.

Yang X, Si T, Gong Q, Qiu L, Jia Z, Zhou M, et al. Brain gray matter alterations and associated demographic profiles in adults with autism spectrum disorder: A meta-analysis of voxel-based morphometry studies. Australian & New Zealand Journal of Psychiatry. 2016;50(8):741-53.

Wallace GL, Dankner N, Kenworthy L, Giedd JN, Martin A. Age-related temporal and parietal cortical thinning in autism spectrum disorders. Brain. 2010;133(12):3745-54.

Foster NE, Doyle-Thomas KA, Tryfon A, Ouimet T, Anagnostou E, Evans AC, et al. Structural gray matter differences during childhood development in autism spectrum disorder: a multimetric approach. Pediatric neurology. 2015;53(4):350-9.

Wallace GL, Eisenberg IW, Robustelli B, Dankner N, Kenworthy L, Giedd JN, et al. Longitudinal cortical development during adolescence and young adulthood in autism spectrum disorder: increased cortical thinning but comparable surface area changes. Journal of the American Academy of Child & Adolescent Psychiatry. 2015;54(6):464-9.

Iacoboni M. Neurobiology of imitation. Current opinion in neurobiology. 2009;19(6):661-5.

Miller E. Functional Connectivity of the Inferior Frontal Gyrus in Autism Spectrum Disorders. 2021.

Cermak CA, Arshinoff S, Ribeiro de Oliveira L, Tendera A, Beal DS, Brian J, et al. Brain and Language Associations in Autism Spectrum Disorder: A Scoping Review. Journal of Autism and Developmental Disorders. 2021:1-13.

Yamasaki S, Yamasue H, Abe O, Suga M, Yamada H, Inoue H, et al. Reduced gray matter volume of pars opercularis is associated with impaired social communication in high-functioning autism spectrum disorders. Biol Psychiatry. 2010;68(12):1141-7.

McAlonan GM, Cheung V, Cheung C, Suckling J, Lam GY, Tai K, et al. Mapping the brain in autism. A voxel-based MRI study of volumetric differences and intercorrelations in autism. Brain. 2005;128(2):268-76.

Apps MA, Rushworth MF, Chang SW. The anterior cingulate gyrus and social cognition: tracking the motivation of others. Neuron. 2016;90(4):692-707.

Bzdok D, Hartwigsen G, Reid A, Laird AR, Fox PT, Eickhoff SB. Left inferior parietal lobe engagement in social cognition and language. Neuroscience & Biobehavioral Reviews. 2016;68:319-34.

Focquaert F, Vanneste S. Autism spectrum traits in normal individuals: a preliminary VBM analysis. Frontiers in Human Neuroscience. 2015;9:264.

Jung M, Tu Y, Lang CA, Ortiz A, Park J, Jorgenson K, et al. Decreased structural connectivity and resting-state brain activity in the lateral occipital cortex is associated with social communication deficits in boys with autism spectrum disorder. NeuroImage. 2019;190:205-12.

Oades RD. Frontal, temporal and lateralized brain function in children with attention-deficit hyperactivity disorder: a psychophysiological and neuropsychological viewpoint on development. Behavioural brain research. 1998;94(1):83-95.

Sato W, Toichi M, Uono S, Kochiyama T. Impaired social brain network for processing dynamic facial expressions in autism spectrum disorders. BMC neuroscience. 2012;13(1):1-17.

Scheel C, Rotarska-Jagiela A, Schilbach L, Lehnhardt FG, Krug B, Vogeley K, et al. Imaging derived cortical thickness reduction in high-functioning autism: key regions and temporal slope. NeuroImage. 2011;58(2):391-400.

Ecker C, Ginestet C, Feng Y, Johnston P, Lombardo MV, Lai M-C, et al. Brain surface anatomy in adults with autism: the relationship between surface area, cortical thickness, and autistic symptoms. JAMA psychiatry. 2013;70(1):59-70.

Hardan AY, Libove RA, Keshavan MS, Melhem NM, Minshew NJ. A preliminary longitudinal magnetic resonance imaging study of brain volume and cortical thickness in autism. Biological psychiatry. 2009;66(4):320-6.

Constantino J, Todorov A, Hilton C, Law P, Zhang Y, Molloy E, et al. Autism recurrence in half siblings: strong support for genetic mechanisms of transmission in ASD. Molecular psychiatry. 2013;18(2):137-8.

Smith E, Thurm A, Greenstein D, Farmer C, Swedo S, Giedd J, et al. Cortical thickness change in autism during early childhood. Human brain mapping. 2016;37(7):2616-29.

Parikshak NN, Luo R, Zhang A, Won H, Lowe JK, Chandran V, et al. Integrative functional genomic analyses implicate specific molecular pathways and circuits in autism. Cell. 2013;155(5):1008-21.

Luo W, Zhang C, Jiang Y-h, Brouwer CR. Systematic reconstruction of autism biology from massive genetic mutation profiles. Science advances. 2018;4(4):e1701799.

Sanders SJ, Murtha MT, Gupta AR, Murdoch JD, Raubeson MJ, Willsey AJ, et al. De novo mutations revealed by whole-exome sequencing are strongly associated with autism. Nature. 2012;485(7397):237-41.

Sala C, Vicidomini C, Bigi I, Mossa A, Verpelli C. Shank synaptic scaffold proteins: keys to understanding the pathogenesis of autism and other synaptic disorders. Journal of neurochemistry. 2015;135(5):849-58.

Li D, Karnath H-O, Xu X. Candidate biomarkers in children with autism spectrum disorder: a review of MRI studies. Neuroscience bulletin. 2017;33:219-37.

Kharabian Masouleh S, Eickhoff SB, Zeighami Y, Lewis LB, Dahnke R, Gaser C, et al. Influence of processing pipeline on cortical thickness measurement. Cerebral Cortex. 2020;30(9):5014-27.

Pulli EP, Silver E, Kumpulainen V, Copeland A, Merisaari H, Saunavaara J, et al. Feasibility of FreeSurfer processing for T1-weighted brain images of 5-year-olds: semiautomated protocol of FinnBrain Neuroimaging Lab. Frontiers in Neuroscience. 2022;16:874062.