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Longitudinal changes in cortical thickness in autism and typical development
Open accessAbstract
The natural history of brain growth in autism spectrum disorders remains unclear. Cross-sectional studies have identified regional abnormalities in brain volume and cortical thickness in autism, although substantial discrepancies have been reported. Preliminary longitudinal studies using two time points and small samples have identified specific regional differences in cortical thickness in the disorder. To clarify age-related trajectories of cortical development, we examined longitudinal changes in cortical thickness within a large mixed cross-sectional and longitudinal sample of autistic subjects and age- and gender-matched typically developing controls. Three hundred and forty-five magnetic resonance imaging scans were examined from 97 males with autism (mean age = 16.8 years; range 3-36 years) and 60 males with typical development (mean age = 18 years; range 4-39 years), with an average interscan interval of 2.6 years. FreeSurfer image analysis software was used to parcellate the cortex into 34 regions of interest per hemisphere and to calculate mean cortical thickness for each region. Longitudinal linear mixed effects models were used to further characterize these findings and identify regions with between-group differences in longitudinal age-related trajectories. Using mean age at time of first scan as a reference (15 years), differences were observed in bilateral inferior frontal gyrus, pars opercularis and pars triangularis, right caudal middle frontal and left rostral middle frontal regions, and left frontal pole. However, group differences in cortical thickness varied by developmental stage, and were influenced by IQ. Differences in age-related trajectories emerged in bilateral parietal and occipital regions (postcentral gyrus, cuneus, lingual gyrus, pericalcarine cortex), left frontal regions (pars opercularis, rostral middle frontal and frontal pole), left supramarginal gyrus, and right transverse temporal gyrus, superior parietal lobule, and paracentral, lateral orbitofrontal, and lateral occipital regions. We suggest that abnormal cortical development in autism spectrum disorders undergoes three distinct phases: accelerated expansion in early childhood, accelerated thinning in later childhood and adolescence, and decelerated thinning in early adulthood. Moreover, cortical thickness abnormalities in autism spectrum disorders are region-specific, vary with age, and may remain dynamic well into adulthood.
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“Here, we used microelectrode arrays that were implanted in the animal’s mPFC (Extended Data Fig. 1b), an area suggested to be involved in social behavior 1,7,12,26,34 and disorders such as ASD 14,21,35,36.”
From Reduced sociability and social agency encoding in adult Shank3-mutant mice are restored through gene re-expression in real time (2021) · cites this paper as [35]
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“various neurophysiological features such as cortical volume 35,47 and connectivity 27 are also altered in ASD.”
From Reduced sociability and social agency encoding in adult Shank3-mutant mice are restored through gene re-expression in real time (2021) · cites this paper as [35]
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Cites
R: A Language and Environment for Statistical Computing
R Core Team (2000) · doi:10.32614/r.manuals · Cited by 355,893
Diagnostic and Statistical Manual of Mental Disorders
Williams, J. B. W., & First, M. B. (2013) · Oxford University Press eBooks · doi:10.1093/acrefore/9780199975839.013.104 · Cited by 109,845
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
A new look at the statistical model identification
Akaike, H. (1974) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1974.1100705 · Cited by 51,879
The assessment and analysis of handedness: The Edinburgh inventory
Oldfield, R. C. (1971) · Neuropsychologia · doi:10.1016/0028-3932(71)90067-4 · Cited by 35,900
Diagnostic and Statistical Manual of Mental Disorders
(2012) · Springer eBooks · doi:10.1007/springerreference_121117 · Cited by 20,772
Desikan, R. S., Ségonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., Buckner, R. L., Dale, A. M., Maguire, R. P., Hyman, B. T., et al. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.01.021 · Cited by 13,324
Lord, C., Rutter, M., & Le Couteur, A. (1994) · Journal of Autism and Developmental Disorders · doi:10.1007/bf02172145 · Cited by 9,065
Fischl, B., Salat, D. H., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., van der Kouwe, A., Killiany, R., Kennedy, D., Klaveness, S., et al. (2002) · Neuron · doi:10.1016/s0896-6273(02)00569-x · Cited by 8,610
Lord, C., Risi, S., Lambrecht, L., Cook, E. H., Leventhal, B. L., DiLavore, P. C., Pickles, A., & Rutter, M. (2000) · Journal of Autism and Developmental Disorders · doi:10.1023/a:1005592401947 · Cited by 7,520
Flagged first, then by citations
Research works printed but not linked: 2
- Elliott, 1990, Differntial Ability Scales-II (DAS-II)
- Wechsler, Wechsler Intelligence Scales for Children
Cited by
Sorted by citations
Items 201–300 of 375
Ventral temporal and posteromedial sulcal morphology in autism spectrum disorder
Benitez, J. A. R., Kannan, S., Hastings, W. L., Parker, B. J., Willbrand, E. H., & Weiner, K. S. (2024) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2024.108786 · Cited by 20
Sex differences in trajectories of cortical development in autistic children from 2–13 years of age
Andrews, D. S., Diers, K., Lee, J. K., Harvey, D. J., Heath, B. E., Cordero, D., Rogers, S. J., Reuter, M., Solomon, M., Amaral, D. G., et al. (2024) · Molecular Psychiatry · doi:10.1038/s41380-024-02592-8 · Cited by 18
Quantitative brain morphological analysis in CHARGE syndrome
Shiohama, T., McDavid, J., Levman, J. E. D., & Takahashi, E. (2019) · NeuroImage Clinical · doi:10.1016/j.nicl.2019.101866 · Cited by 16
Measuring robustness of brain networks in autism spectrum disorder with Ricci curvature
Simhal, A. K., Carpenter, K. L. H., Nadeem, S., Kurtzberg, J., Song, A. W., Tannenbaum, A., Sapiro, G., & Dawson, G. (2020) · Scientific Reports · doi:10.1038/s41598-020-67474-9 · Cited by 17
Grey and white matter volumes in early childhood: A comparison of voxel-based morphometry pipelines
Haynes, L., Ip, A., Cho, I. Y. K., Dimond, D., Rohr, C. S., Bagshawe, M., Dewey, D., Lebel, C. A., & Bray, S. (2020) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2020.100875 · Cited by 17
Smith, S. D. W., Smith, A. B., Richardson, M. P., & Pal, D. K. (2021) · Epilepsia Open · doi:10.1002/epi4.12468 · Cited by 14
Lan, J., Hu, Y., Wang, X., Zheng, W., Liao, A., Wang, S., Li, Y., Wang, Y., Yang, F., & Chen, D. (2021) · Neuropharmacology · doi:10.1016/j.neuropharm.2021.108689 · Cited by 15
Functional and Neuropathological Evidence for a Role of the Brainstem in Autism
Baizer, J. S. (2021) · Frontiers in Integrative Neuroscience · doi:10.3389/fnint.2021.748977 · Cited by 15
Walsh, E. C., Lee, J. M., Terzakis, K., Zhou, D. W., Burns, S. M., Buie, T. M., Firth, P. G., Shank, E. S., Houle, T. T., Brown, E. N., et al. (2018) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2018.00023 · Cited by 15
Lucibello, S., Verdolotti, T., Giordano, F. M., Lapenta, L., Infante, A., Piludu, F., Tartaglione, T., Chieffo, D. P. R., Colosimo, C., Mercuri, E. M., et al. (2018) · Clinical Anatomy · doi:10.1002/ca.23252 · Cited by 15
Bletsch, A., Schäfer, T., Mann, C., Andrews, D. S., Daly, E., Gudbrandsen, M., Ruigrok, A. N. V., Dallyn, R. A., Romero-García, R., Lai, M., et al. (2020) · Human Brain Mapping · doi:10.1002/hbm.25237 · Cited by 16
Neuron-Specific Enolase (NSE) as a Biomarker for Autistic Spectrum Disease (ASD)
Stancioiu, F., Bogdan, R. D., & Dumitrescu, R. (2023) · Life · doi:10.3390/life13081736 · Cited by 14
Yamagata, B., Itahashi, T., Fujino, J., Ohta, H., Takashio, O., Nakamura, M., Kato, N., Mimura, M., Hashimoto, R., & Aoki, Y. Y. (2019) · Psychiatry and Clinical Neurosciences · doi:10.1111/pcn.12854 · Cited by 15
Brain structural alterations in autism and criminal psychopathy
Noppari, T., Sun, L., Lukkarinen, L., Putkinen, V., Tani, P., Lindberg, N., Saure, E., Lauerma, H., Tiihonen, J., Venetjoki, N., et al. (2022) · NeuroImage Clinical · doi:10.1016/j.nicl.2022.103116 · Cited by 14
Adolescent-Specific Motivation Deficits in Autism Versus Typical Development
Bos, D. J., Silver, B., Barnes, E. D., Ajodan, E. L., Silverman, M. R., Clark-Whitney, E., Tarpey, T., & Jones, R. M. (2019) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-019-04258-9 · Cited by 15
James, D. M., Lam, V. T., Jo, B., & Fung, L. K. (2022) · Autism Research · doi:10.1002/aur.2703 · Cited by 16
Kojima, M., Yassin, W., Owada, K., Aoki, Y. Y., Kuwabara, H., Natsubori, T., Iwashiro, N., Gonoi, W., Takao, H., Kasai, K., et al. (2018) · Cerebral Cortex · doi:10.1093/cercor/bhy122 · Cited by 15
Xu, L., Guo, Y., Li, J., Yu, J., & Xu, H. (2020) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2020.101958 · Cited by 13
Khundrakpam, B. S., Bhutani, N., Vainik, U., Gong, J., Al‐Sharif, N., Dagher, A., White, T. J. H., & Evans, A. C. (2022) · Molecular Psychiatry · doi:10.1038/s41380-022-01916-w · Cited by 22
Maturational trajectories of pericortical contrast in typical brain development
Drakulich, S., Thiffault, A.-C., Olafson, E. R., Parent, O., Labbe, A., Albaugh, M. D., Khundrakpam, B. S., Ducharme, S., Evans, A. C., Chakravarty, M. M., et al. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.117974 · Cited by 12
DiPiero, M. A., Surgent, O. J., Travers, B. G., Alexander, A. L., Lainhart, J. E., & Dean, D. (2022) · NeuroImage Clinical · doi:10.1016/j.nicl.2022.103306 · Cited by 13
Self-citationLundwall, R. A., Stephenson, K. G., Tass, E. S., Cox, J. C., South, M., Bigler, E. D., Anderberg, E., Prigge, M. B. D., Hansen, B. D., Lainhart, J. E., et al. (2016) · Research in Autism · doi:10.1016/j.rasd.2016.12.001 · Cited by 13
Self-citationNi, H., Lin, H., Chen, Y., Tseng, W. I., & Gau, S. S. (2019) · Brain Imaging and Behavior · doi:10.1007/s11682-019-00199-0 · Cited by 13
Reduced lateralization of multiple functional brain networks in autistic males
Peterson, M., Prigge, M. B. D., Floris, D. L., Bigler, E. D., Zielinski, B. A., King, J. B., LANGE, N. D., Alexander, A. L., Lainhart, J. E., & Nielsen, J. A. (2024) · Journal of Neurodevelopmental Disorders · doi:10.1186/s11689-024-09529-w · Cited by 14
Self-citationLi, M., Izumoto, M., Wang, Y., Kato, Y., Iwatani, Y., Hirata, I., Mizuno, Y., Tachibana, M., Mohri, I., & Kagitani‐Shimono, K. (2024) · NeuroImage · doi:10.1016/j.neuroimage.2024.120731 · Cited by 13
Feng, Y.-X., Collignon, O., Maurer, D. M., Yao, K., & Gao, X. (2021) · Frontiers in Medicine · doi:10.3389/fmed.2021.752021 · Cited by 11
Myers, S. M., & Challman, T. D. (2018) · American Academy of PediatricsItasca, IL eBooks · doi:10.1542/9781610021357-19 · Cited by 12
Radoeva, P. D., Bansal, R., Antshel, K. M., Fremont, W. P., Peterson, B. S., & Kates, W. R. (2016) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12657 · Cited by 13
Beyond volume: A surface-based approach to bilingualism-induced grey matter changes
Hämäläinen, S., Joutsa, J., Sihvonen, A. J., Leminen, A., & Lehtonen, M. (2018) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2018.04.038 · Cited by 13
Chien, H.-Y. S., Gau, S. S., Hsu, Y., Chen, Y., Lo, Y., Shih, Y., & Tseng, W. I. (2015) · Autism Research · doi:10.1002/aur.1484 · Cited by 16
Boedhoe, P. S. W., van Rooij, D., Hoogman, M., Twisk, J. W. R., Schmaal, L., Abe, Y., Alonso, P., Ameis, S. H., Владимирович, А. А., Anticevic, A., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/673012 · Cited by 12
The Cost of Untracked Diversity in Brain-Imaging PredictionPreprint
Benkarim, O. M., Paquola, C., Park, B., Kebets, V., Hong, S., de Wael, R. V., Zhang, S., Yeo, B. T. T., Eickenberg, M., Ge, T., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.06.16.448764 · Cited by 12
Rabelo, L. N., Queiroz, J. P. G., Castro, C. C. M., da Silva, S. P., Campos, L. D., Silva, L. C., do Nascimento, E. B., Martínez‐Cerdeño, V., & Fiuza, F. P. (2022) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-022-05626-8 · Cited by 11
Abdelrahim, M., Khudri, M., Elnakib, A. A., Shehata, M., Weafer, K., Khalil, A., Saleh, G. A., Batouty, N. M., Ghazal, M. A., Contractor, S. G., et al. (2025) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2025.103074 · Cited by 12
Morphometric Analysis of Brain in Newborn with Congenital Diaphragmatic Hernia
Lucignani, M., Longo, D., Fontana, E., Rossi‐Espagnet, M. C., Lucignani, G., Savelli, S., Bascetta, S., Sgrò, S., Morini, F., Giliberti, P., et al. (2021) · Brain Sciences · doi:10.3390/brainsci11040455 · Cited by 11
Pre-autism: What a paediatrician should know about early diagnosis of autism
Al‐Beltagi, M. (2023) · World Journal of Clinical Pediatrics · doi:10.5409/wjcp.v12.i5.273 · Cited by 13
Association between cortical thickness and cognitive ability in very preterm school-age children
Choi, U.-S., Shim, S., Cho, H. J., & Jeong, H.-J. (2024) · Scientific Reports · doi:10.1038/s41598-024-52576-5 · Cited by 12
Li, S., Zhou, Z., Meng, J., Zhu, X., Wang, K., Wei, D., & Qiu, J. (2020) · Psychophysiology · doi:10.1111/psyp.13728 · Cited by 12
Kunda, M., Zhou, S., Gong, G., & Lu, H. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.02.01.930073 · Cited by 10
Accelerating progress in autism through developmental research
Wolff, J. J., & Piven, J. (2014) · Nature Reviews Neurology · doi:10.1038/nrneurol.2014.126 · Cited by 10
Chinen, Y., Nakamura, S., Ganaha, A., Hayashi, S., Inazawa, J., Yanagi, K., Nakanishi, K., Kaname, T., & Naritomi, K. (2017) · Clinical Case Reports · doi:10.1002/ccr3.1361 · Cited by 10
MGN-Net: a multi-view graph normalizer for integrating heterogeneous biological network populationsPreprint
Rekik, I., & Gürbüz, M. B. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2104.03895 · Cited by 10
Autism-associated brain differences can be observed in utero using MRI
Ortuğ, A., Guo, Y., Feldman, H. A., Ou, Y., Warren, J. L. A., Dieuveuil, H., Baumer, N., Faja, S., & Takahashi, E. (2024) · Cerebral Cortex · doi:10.1093/cercor/bhae117 · Cited by 10
Transcallosal white matter and cortical gray matter variations in autistic adults aged 30–73 years
Shin, Y. S., Christensen, D., Wang, J., Shirley, D. J., Orlando, A., Romero, R. A. A., Vaillancourt, D. E., Wilkes, B. J., Coombes, S. A., & Wang, Z. (2025) · Molecular Autism · doi:10.1186/s13229-025-00652-6 · Cited by 10
Schizophrenia Polygenic Risk During Typical Development Reflects Multiscale Cortical Organization
Kirschner, M., Paquola, C., Khundrakpam, B. S., Vainik, U., Bhutani, N., Hodzic-Santor, B. H., Georgiadis, F., Al‐Sharif, N., Mišić, B., Bernhardt, B. C., et al. (2022) · Biological Psychiatry Global Open Science · doi:10.1016/j.bpsgos.2022.08.003 · Cited by 15
DiPiero, M. A., Cordash, H., Prigge, M. B. D., King, C. K., Morgan, J., Guerrero-Gonzalez, J. M., Adluru, N., King, J. B., LANGE, N. D., Bigler, E. D., et al. (2023) · Frontiers in Neuroscience · doi:10.3389/fnins.2023.1231719 · Cited by 9
Self-citationKhundrakpam, B. S., Choudhury, S., Vainik, U., Al‐Sharif, N., Bhutani, N., Evans, A. C., & the Pediatric Imaging, N. A. G. S. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/575993 · Cited by 10
Crutcher, J., Martin, A. D., & Wallace, G. L. (2018) · Autism Research · doi:10.1002/aur.1969 · Cited by 8
Sader, M., Harris, H. A., Waiter, G. D., Jansen, P. W., Williams, J. H. G., & White, T. J. H. (2024) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.14086 · Cited by 8
Borsani, E., Bonomini, F., Bonini, S. A., Premoli, M., Maccarinelli, G., Giugno, L., Mastinu, A., Aria, F., Memo, M., & Rezzani, R. (2022) · Journal of Neuroscience Research · doi:10.1002/jnr.24997 · Cited by 12
Lan, Z., Xu, S., Yu, X., Yu, Z., Li, M., Chen, F., Liu, Y., Wang, T., Wu, Y., Gan, Y., et al. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.844821 · Cited by 8
Mali, I., Payne, M. M., King, C., Maze, T., Davison, T., Challans, B., Bossmann, S. H., & Plakke, B. (2022) · Brain Research · doi:10.1016/j.brainres.2022.148199 · Cited by 9
Weiss, E. M., Walter, C., Fink, A., Schulter, G., Mittenecker, E., & Papousek, I. (2018) · European Archives of Psychiatry and Clinical Neuroscience · doi:10.1007/s00406-018-0915-1 · Cited by 8
Chien, Y., Chen, Y., Chiu, Y., Tsai, W., & Gau, S. S. (2021) · Journal of Psychiatry and Neuroscience · doi:10.1503/jpn.210022 · Cited by 7
Kaiser, M. (2020) · The MIT Press eBooks · doi:10.7551/mitpress/11980.001.0001 · Cited by 25
Simhal, A. K., Carpenter, K. L. H., Kurtzberg, J., Song, A. W., Tannenbaum, A., Zhang, L., Sapiro, G., & Dawson, G. (2022) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.1026279 · Cited by 8
Garcia, M., & Kelly, C. A. M. (2024) · PLoS ONE · doi:10.1371/journal.pone.0276832 · Cited by 9
Hanson, K. L., Avino, T. A., Taylor, S. L., Murray, K. D., & Schumann, C. M. (2025) · Molecular Autism · doi:10.1186/s13229-025-00684-y · Cited by 9
Prenatal Adversities and Risk of Persistent Youth Psychopathology and Altered Cortical Thinning
Zhi, D., Perdomo, S. Á., Arteaga, L. R., Hughes, D., Dunn, E. C., Lee, P. H., Evins, A. E., Reeder, H. T., Hadland, S. E., Doyle, A. E., et al. (2026) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2025.4080 · Cited by 8
Rochat, M. J., & Gallese, V. (2022) · Psychoanalytic Inquiry · doi:10.1080/07351690.2022.2007022 · Cited by 8
Kollndorfer, K., Novak, A., Nenning, K., Fischmeister, F. P. S., Seidl, R., Langs, G., Kasprian, G. J., Prayer, D., & Bartha, L. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1196707 · Cited by 7
Yao, Y., Guo, L.-L., Gao, J.-Q., Jin, X.-J., Wang, K., Chen, J.-H., Zhang, Y.-H., Che, C., Cai, Z., Gao, J., et al. (2025) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-025-06914-9 · Cited by 6
Morphological and Functional Changes of Cerebral Cortex in Autism Spectrum Disorder.
Ong, L. T., & Fan, S. W. D. (2023) · PubMed Central · Cited by 7
Morphometry and Development: Changes in Brain Structure from Birth to Adult Age
Tamnes, C., & Østby, Y. (2018) · Neuromethods · doi:10.1007/978-1-4939-7647-8_10 · Cited by 6
Identification of Abnormal Cortical 3-Hinge Folding Patterns on Autism Spectral Brains
Huang, Y., He, Z., Liu, T., Guo, L., & Zhang, T. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-33226-6_7 · Cited by 6
Age-related Brain Morphological Alteration of Medication-naive Boys With High Functioning Autism
Wu, C., Zheng, H. W., Wu, H., Tang, Y., Li, F., & Wang, D. (2020) · Academic Radiology · doi:10.1016/j.acra.2020.10.007 · Cited by 6
Mann, C., Schäfer, T., Bletsch, A., Gudbrandsen, M., Daly, E., John Suckling, A., Bullmore, E. T., Lombardo, M. V., Lai, M., Craig, M., et al. (2020) · Human Brain Mapping · doi:10.1002/hbm.25270 · Cited by 6
Bezgin, G., Lewis, J. D., Fonov, V., Collins, D. L., & Evans, A. C. (2024) · Human Brain Mapping · doi:10.1002/hbm.26584 · Cited by 6
Advances in magnetic resonance imaging of the developing brain and its applications in pediatrics
Chen, R., Li, M., Zhao, Z., Xu, H., Ning, C.-L., Lu, J., Zhu, Q.-F., Huang, Y., Zhao, R., Zhang, L.-X., et al. (2025) · World Journal of Pediatrics · doi:10.1007/s12519-025-00905-7 · Cited by 5
The Long and Winding Road to Understanding Autism
Manzo, J., Hernández‐Aguilar, M. E., Toledo‐Cárdenas, M. R., Herrera‐Covarrubias, D., Coria‐Ávila, G. A., Libreros-Jiménez, H. M., Cañedo, L. F., & Pineda, L. A. O. (2025) · NeuroSci · doi:10.3390/neurosci6030084 · Cited by 6
Yamashita, M., Kagitani‐Shimono, K., Hirano, Y., Hamatani, S., Nishitani, S., Yao, A., Kurata, S., Kosaka, H., Jung, M., Yoshida, T., et al. (2023) · BMJ Open · doi:10.1136/bmjopen-2022-070157 · Cited by 4
Assessing cortical features in early stage ASD children
Napolitano, A., Guerrera, S., Lucignani, M., Parrillo, C., Baldassari, G., Bottino, F., Moltoni, G., Rossi‐Espagnet, M. C., Talamanca, L. F., Valeri, G., et al. (2024) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2023.1098265 · Cited by 4
Sader, M., Halls, D., Kerr‐Gaffney, J., Waiter, G. D., Gillespie‐Smith, K., Duffy, F., & Tchanturia, K. (2025) · Psychological Medicine · doi:10.1017/s0033291725001047 · Cited by 4
Autonomic nervous system in children with autism spectrum disorder
Bujnakova, I., Ondrejka, I., Mestanik, M., & Tonhajzerová, I. (2015) · Cognitive Remediation Journal · doi:10.5507/crj.2015.003 · Cited by 4
Hyde, J., & García‐Rill, E. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-817992-5.00006-4 · Cited by 4
Understanding Typical and Atypical Neurodevelopment in Children and Adults
Riccio, C. A., Sun, L. H., & Gonzalez, A. A. (2021) · Springer eBooks · doi:10.1007/978-3-030-59162-5_4 · Cited by 5
Pretzsch, C. M., & Ecker, C. (2022) · Elsevier eBooks · doi:10.1016/b978-0-12-816393-1.00013-0 · Cited by 4
White and gray matter correlates of theory of mind in autism: a voxel-based morphometry study
Soylu, F., May, K. E., & Kana, R. K. (2023) · Brain Structure and Function · doi:10.1007/s00429-023-02680-5 · Cited by 4
Ge, F., Chen, H., Zhang, T., Wang, X., Lin, Y. P., Hu, X., Guo, L., & Liu, T. (2018) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2018.8363750 · Cited by 4
Sultan, S. (2022) · The Egyptian Journal of Neurology Psychiatry and Neurosurgery · doi:10.1186/s41983-022-00578-3 · Cited by 5
Chen, B. (2020) · International Journal of Neuroscience · doi:10.1080/00207454.2020.1806837 · Cited by 5
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Levman, J. E. D. (2025) · Biology · doi:10.3390/biology14121651 · Cited by 3
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Yu, K., Xu, S., Fu, S., Hua, K., Yin, Y., Lei, Q., Liu, J., Wu, Y., & Jiang, G. (2025) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2025.1513200 · Cited by 3
Yu, M., Liu, J., & Ji, J. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.111877 · Cited by 3
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Gao, L., An, H., Yin, L., Ma, L., Niu, X., & Guo, X. (2026) · Chaos Solitons & Fractals · doi:10.1016/j.chaos.2026.118167 · Cited by 2
Tarchi, L., Doose, A., Hennig, J., Bernardoni, F., King, J. A., Pisano, T., Castellini, G., Ricca, V., Kamp‐Becker, I., & Ehrlich, S. (2026) · Autism Research · doi:10.1002/aur.70243 · Cited by 2
Palande, S., Jose, V., Zielinski, B. A., Anderson, J. S., Fletcher, P. T., & Wang, B. (2018) · Brain Connectivity · doi:10.1089/brain.2018.0604 · Cited by 2
Self-citationGros, G., Miranda, R., Latrille, A., Saitovitch, A., Gollier-Briant, F., Fossati, P., Schmidt, L., Banaschewski, T., Barker, G. J., Bokde, A. L. W., et al. (2023) · Brain Structure and Function · doi:10.1007/s00429-023-02710-2 · Cited by 3
Sivayokan, B., King, C., Mali, I., Payne, M. M., Strating, H., Warnes, E., Bossmann, S. H., & Plakke, B. (2024) · Behavioural Brain Research · doi:10.1016/j.bbr.2024.115136 · Cited by 2
Metadata
- Authors
- Zielinski, B. A., Prigge, M. B. D., Nielsen, J. A., Froehlich, A. L., Abildskov, T. J., Anderson, J. S., Fletcher, P. T., Zygmunt, K. M., Travers, B. G., Lange, N., Alexander, A. L., Bigler, E. D., & Lainhart, J. E.
- Affiliations
- Primary Children's Hospital (US)
- University of Utah (US)
- Brigham Young University (US)
- University of Wisconsin–Madison (US)
- Harvard University (US)
- University of Wisconsin System (US)
- ORCID
- Venue
- Brain
- Publisher
- Oxford University Press (OUP)
- Published
- 2014-04-22
- Volume
- 137
- Issue
- 6
- Pages
- 1799-1812
- ISSN
- 0006-8950 (ISSN-L)
- 1460-2156
- PMC
- PMC4032101
- OpenAlex
- W2115716215
- Cited by
- 378
- References
- 63
- Citations by year
- 2026: 21 · 2025: 22 · 2024: 27 · 2023: 20 · 2022: 37 · 2021: 35 · 2020: 32 · 2019: 36 · 2018: 45 · 2017: 24 · 2016: 37 · 2015: 35 · 2014: 7
- FWCI
- 19.15
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Brain (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institute of Mental Health (K08MH100609, R01MH097464, K08MH092697, R01MH084795)
- National Institute of Neurological Disorders and Stroke (T32NS076067)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (K12HD001410, T32 HD 07489, P30HD003352, T32HD007489)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
- Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
- Keywords
- autism spectrum disorder, cortical thickness, cortical development, brain growth, typically developing controls, inferior frontal gyrus, frontal pole, frontal lobe, parietal cortex, occipital cortex, IQ
- MeSH terms
- Adolescent, Adult, Autistic Disorder, Brain Mapping, Cerebral Cortex, Child, Child, Preschool, Humans, Intelligence Tests, Functional Laterality, Longitudinal Studies, Magnetic Resonance Imaging, Male, Young Adult
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