The DOI matches its Crossref record; 163 of the 163 references it cites were found in a registry or an index.
Distinct regions of the cerebellum show gray matter decreases in autism, ADHD, and developmental dyslexia
Open accessAbstract
Differences in cerebellar structure have been identified in autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), and developmental dyslexia. However, it is not clear if different cerebellar regions are involved in each disorder, and thus whether cerebellar anatomical differences reflect a generic developmental vulnerability or disorder-specific characteristics. To clarify this, we conducted an anatomic likelihood estimate (ALE) meta-analysis on voxel-based morphometry (VBM) studies which compared ASD (17 studies), ADHD (10 studies), and dyslexic (10 studies) participants with age-matched typically-developing (TD) controls. A second ALE analysis included studies in which the cerebellum was a region of interest (ROI). There were no regions of significantly increased gray matter (GM) in the cerebellum in ASD, ADHD, or dyslexia. Data from ASD studies revealed reduced GM in the inferior cerebellar vermis (lobule IX), left lobule VIIIB, and right Crus I. In ADHD, significantly decreased GM was found bilaterally in lobule IX, whereas participants with developmental dyslexia showed GM decreases in left lobule VI. There was no overlap between the cerebellar clusters identified in each disorder. We evaluated the functional significance of the regions revealed in both whole-brain and cerebellar ROI ALE analyses using Buckner and colleagues' 7-network functional connectivity map available in the SUIT cerebellar atlas. The cerebellar regions identified in ASD showed functional connectivity with frontoparietal, default mode, somatomotor, and limbic networks; in ADHD, the clusters were part of dorsal and ventral attention networks; and in dyslexia, the clusters involved ventral attention, frontoparietal, and default mode networks. The results suggest that different cerebellar regions are affected in ASD, ADHD, and dyslexia, and these cerebellar regions participate in functional networks that are consistent with the characteristic symptoms of each disorder.
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
Williams, J. B. W., & First, M. (2013) · Encyclopedia of Social Work · doi:10.1093/acrefore/9780199975839.013.104 · Cited by 109,519
Control of goal-directed and stimulus-driven attention in the brain
Corbetta, M., & Shulman, G. L. (2002) · Nature Reviews Neuroscience · doi:10.1038/nrn755 · Cited by 12,881
Co-Planar Stereotaxic Atlas of the Human Brain
Talairach, J., & Tournoux, P. (1988) · Medical Entomology and Zoology · Cited by 11,798
The organization of the human cerebellum estimated by intrinsic functional connectivity
Buckner, R. L., Krienen, F. M., Castellanos, A., Diaz, J. C., & Yeo, B. T. T. (2011) · Journal of Neurophysiology · doi:10.1152/jn.00339.2011 · Cited by 7,304
Simonoff, E., Pickles, A., Charman, T., Chandler, S., Loucas, T., & Baird, G. (2008) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1097/chi.0b013e318179964f · Cited by 3,399
Categorizing sounds and learning to read—a causal connection
Bradley, L., & Bryant, P. E. (1983) · Nature · doi:10.1038/301419a0 · Cited by 3,021
Molecular genetics of attention-deficit/hyperactivity disorder
Faraone, S. V., Perlis, R. H., Doyle, A. E., Smoller, J. W., Goralnick, J. J., Holmgren, M. A., & Sklar, P. (2005) · Biological Psychiatry · doi:10.1016/j.biopsych.2004.11.024 · Cited by 2,357
Functional topography in the human cerebellum: A meta-analysis of neuroimaging studies
STOODLEY, C., & SCHMAHMANN, J. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.08.039 · Cited by 2,183
Self-citationEickhoff, S. B., Laird, A. R., Grefkes, C., Wang, L. E., Zilles, K., & Fox, P. T. (2009) · Human Brain Mapping · doi:10.1002/hbm.20718 · Cited by 1,924
Design and construction of a realistic digital brain phantom
Collins, D. L., Zijdenbos, A. P., Kollokian, V., Sled, J. G., Kabani, N. J., Holmes, C. J., & Evans, A. C. (1998) · IEEE Transactions on Medical Imaging · doi:10.1109/42.712135 · Cited by 1,822
Cited by
Cerebro-cerebellar circuits in autism spectrum disorder
D'Mello, A. M., & Stoodley, C. J. (2015) · Frontiers in Neuroscience · doi:10.3389/fnins.2015.00408 · Cited by 411
Self-citationThe Cerebellum and Neurodevelopmental Disorders
Stoodley, C. J. (2016) · The Cerebellum · doi:10.1007/s12311-015-0715-3 · Cited by 409
Self-citationNeuroinflammation as a risk factor for attention deficit hyperactivity disorder
Dunn, G. A., Nigg, J. T., & Sullivan, E. L. (2019) · Pharmacology Biochemistry and Behavior · doi:10.1016/j.pbb.2019.05.005 · Cited by 299
Cerebellar gray matter and lobular volumes correlate with core autism symptoms
D'Mello, A. M., Crocetti, D., Mostofsky, S. H., & Stoodley, C. J. (2015) · NeuroImage: Clinical · doi:10.1016/j.nicl.2015.02.007 · Cited by 281
Self-citationNorton, E. S., Beach, S. D., & Gabrieli, J. D. (2015) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2014.09.007 · Cited by 277
Metadata
- Authors
- Stoodley, C. J.
- Venue
- Frontiers in Systems Neuroscience
- Publisher
- Frontiers Media SA
- Published
- 2014-05-20
- Volume
- 8
- Pages
- 92-92
- ISSN
- 1662-5137 (ISSN-L)
- OpenAlex
- W2038028083
- Cited by
- 276
- References
- 163
- FWCI
- 10.21
- Type
- journal article
- Language
- en
- Open access
- gold
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Distinct regions of the cerebellum show gray matter decreases in autism, ADHD, and developmental dyslexia. https://app.cochat.ai/papers/10.3389/fnsys.2014.00092
- The paper
- Stoodley, C. J. (2014). Distinct regions of the cerebellum show gray matter decreases in autism, ADHD, and developmental dyslexia. Frontiers in Systems Neuroscience. https://doi.org/10.3389/fnsys.2014.00092
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.