The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
Characteristics of Brains in Autism Spectrum Disorder: Structure, Function and Connectivity across the Lifespan
Open accessAbstract
Autism spectrum disorder (ASD) is a highly prevalent neurodevelopmental disorder characterized by impaired social communication and restricted and repetitive behaviors (RRBs). Over the past decade, neuroimaging studies have provided considerable insights underlying neurobiological mechanisms of ASD. In this review, we introduce recent findings from brain imaging studies to characterize the brains of ASD across the human lifespan. Results of structural Magnetic Resonance Imaging (MRI) studies dealing with total brain volume, regional brain structure and cortical area are summarized. Using task-based functional MRI (fMRI), many studies have shown dysfunctional activation in critical areas of social communication and RRBs. We also describe several data to show abnormal connectivity in the ASD brains. Finally, we suggest the possible strategies to study ASD brains in the future.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Diagnostic and Statistical Manual of Mental Disorders
American Psychiatric Association (2013) · doi:10.1176/appi.books.9780890425596 · Cited by 116,369
Complex brain networks: graph theoretical analysis of structural and functional systems
Bullmore, E., & Sporns, O. (2009) · Nature Reviews Neuroscience · doi:10.1038/nrn2575 · Cited by 11,820
Functional connectivity in the motor cortex of resting human brain using echo‐planar mri
Biswal, B., Zerrin Yetkin, F., Haughton, V. M., & Hyde, J. S. (1995) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910340409 · Cited by 9,812
Functional connectivity in the resting brain: a network analysis of the default mode hypothesis
Greicius, M. D., Krasnow, B., Reiss, A. L., & Menon, V. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0135058100 · Cited by 6,358
Gaze fixation and the neural circuitry of face processing in autism
Dalton, K. M., Nacewicz, B. M., Johnstone, T., Schaefer, H. S., Gernsbacher, M. A., Goldsmith, H. H., Alexander, A. L., & Davidson, R. J. (2005) · Nature Neuroscience · doi:10.1038/nn1421 · Cited by 1,543
Amaral, D. G., Schumann, C. M., & Nordahl, C. W. (2008) · Trends in Neurosciences · doi:10.1016/j.tins.2007.12.005 · Cited by 1,492
The neurobiology of social cognition
Adolphs, R. (2001) · Current Opinion in Neurobiology · doi:10.1016/s0959-4388(00)00202-6 · Cited by 1,432
Just, M. A., Cherkassky, V. L., Keller, T. A., Kana, R. K., & Minshew, N. J. (2007) · Cerebral Cortex · doi:10.1093/cercor/bhl006 · Cited by 1,081
Courchesne, E., & Pierce, K. (2005) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2005.03.001 · Cited by 968 · cited 1×
“Other investigators also demonstrated that local-range hyperconnectivity [70, 71], however, these results are controversial and the agreement on terminology, local- and long-range, is still lacking.”
ResultBrain growth across the life span in autism: Age-specific changes in anatomical pathology
Courchesne, E., Campbell, K., & Solso, S. (2011) · Brain Research · doi:10.1016/j.brainres.2010.09.101 · Cited by 711
Autism as a neural systems disorder: A theory of frontal-posterior underconnectivity
Just, M. A., Keller, T. A., Malave, V. L., Kana, R. K., & Varma, S. (2012) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2012.02.007 · Cited by 578
Cerebral Lobes in Autism: Early Hyperplasia and Abnormal Age Effects
Carper, R. (2002) · NeuroImage · doi:10.1006/nimg.2002.1099 · Cited by 566
Schumann, C. M., Bloss, C. S., Barnes, C. C., Wideman, G. M., Carper, R. A., Akshoomoff, N., Pierce, K., Hagler, D., Schork, N., Lord, C., et al. (2010) · The Journal of Neuroscience · doi:10.1523/jneurosci.5714-09.2010 · Cited by 554
Abnormal functional connectivity in autism spectrum disorders during face processing
Kleinhans, N. M., Richards, T., Sterling, L., Stegbauer, K. C., Mahurin, R., Johnson, L. C., Greenson, J., Dawson, G., & Aylward, E. (2008) · Brain · doi:10.1093/brain/awm334 · Cited by 498
Aberrant Striatal Functional Connectivity in Children with Autism
Di Martino, A., Kelly, C., Grzadzinski, R., Zuo, X.-N., Mennes, M., Mairena, M. A., Lord, C., Castellanos, F. X., & Milham, M. P. (2011) · Biological Psychiatry · doi:10.1016/j.biopsych.2010.10.029 · Cited by 483
Neural basis of irony comprehension in children with autism: the role of prosody and context
Wang, A. T., Lee, S. S., Sigman, M., & Dapretto, M. (2006) · Brain · doi:10.1093/brain/awl032 · Cited by 447
Longitudinal changes in cortical thickness in autism and typical development
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., et al. (2014) · Brain · doi:10.1093/brain/awu083 · Cited by 378
A pilot study of amygdala volumes in pediatric generalized anxiety disorder
De Bellis, M. D., Casey, B. J., Dahl, R. E., Birmaher, B., Williamson, D. E., Thomas, K. M., Axelson, D. A., Frustaci, K., Boring, A. M., Hall, J., et al. (2000) · Biological Psychiatry · doi:10.1016/s0006-3223(00)00835-0 · Cited by 322 · cited 1×
“and seem to be common in other disorders such as obsessivecompulsive disorder, general anxiety disorders, and schizophrenia [22-24].”
BackgroundCuccaro, M. L., Shao, Y., Grubber, J., Slifer, M., Wolpert, C. M., Donnelly, S. L., Abramson, R. K., Ravan, S. A., Wright, H. H., DeLong, G. R., et al. (2003) · Child Psychiatry and Human Development · doi:10.1023/a:1025321707947 · Cited by 299
Mosconi, M. W., Kay, M., D'Cruz, A.-M., Seidenfeld, A., Guter, S., Stanford, L. D., & Sweeney, J. A. (2009) · Psychological Medicine · doi:10.1017/s0033291708004984 · Cited by 222
Partially enhanced thalamocortical functional connectivity in autism
Mizuno, A., Villalobos, M. E., Davies, M. M., Dahl, B. C., & Müller, R.-A. (2006) · Brain Research · doi:10.1016/j.brainres.2006.05.064 · Cited by 206
Abnormal early brain development in autism
Courchesne, E. (2002) · Molecular Psychiatry · doi:10.1038/sj.mp.4001169 · Cited by 175
Zarei, M., Mataix-Cols, D., Heyman, I., Hough, M., Doherty, J., Burge, L., Winmill, L., Nijhawan, S., Matthews, P. M., & James, A. (2011) · Biological Psychiatry · doi:10.1016/j.biopsych.2011.06.032 · Cited by 160
Underconnectivity of the superior temporal sulcus predicts emotion recognition deficits in autism
Alaerts, K., Woolley, D. G., Steyaert, J., Di Martino, A., Swinnen, S. P., & Wenderoth, N. (2014) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nst156 · Cited by 149
Microstructural abnormalities of short-distance white matter tracts in autism spectrum disorder
Shukla, D. K., Keehn, B., Smylie, D. M., & Müller, R.-A. (2011) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2011.02.022 · Cited by 144
Atypical network connectivity for imitation in autism spectrum disorder
Shih, P., Shen, M., Öttl, B., Keehn, B., Gaffrey, M. S., & Müller, R.-A. (2010) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2010.05.035 · Cited by 120
Humphreys, K., Hasson, U., Avidan, G., Minshew, N., & Behrmann, M. (2008) · Autism Research · doi:10.1002/aur.1 · Cited by 104
Cited by
Emerging Roles for the Gut Microbiome in Autism Spectrum Disorder
Vuong, H. E., & Hsiao, E. Y. (2017) · Biological Psychiatry · doi:10.1016/j.biopsych.2016.08.024 · Cited by 595
A synaptic perspective of fragile X syndrome and autism spectrum Disorders.
Bagni, C., & Zukin, R. S. (2019) · Neuron · doi:10.1016/j.neuron.2019.02.041 · Cited by 326
Yen, C., Lin, C.-L., & Chiang, M.-C. (2023) · Life · doi:10.3390/life13071472 · Cited by 281
Carlisi, C. O., Norman, L. J., Lukito, S. S., Radua, J., Mataix-Cols, D., & Rubia, K. (2017) · Biological Psychiatry · doi:10.1016/j.biopsych.2016.10.006 · Cited by 176
Rapanelli, M., Tan, T., Wang, W., Wang, X., Wang, Z.-J., Zhong, P., Frick, L., Qin, L., Ma, K., Qu, J., et al. (2021) · Molecular Psychiatry · doi:10.1038/s41380-019-0498-x · Cited by 74
Metadata
- Authors
- Ha, S., Sohn, I.-J., Kim, N., Sim, H. J., & Cheon, K.-A.
- Venue
- Experimental Neurobiology
- Published
- 2015-12-30
- Volume
- 24
- Issue
- 4
- Pages
- 273-284
- ISSN
- 1226-2560 (ISSN-L)
- 2093-8144
- OpenAlex
- W2210537348
- Cited by
- 312
- References
- 27
- FWCI
- 7.74
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
