Altered functional and structural brain network organization in autism
Open accessAbstract
Structural and functional underconnectivity have been reported for multiple brain regions, functional systems, and white matter tracts in individuals with autism spectrum disorders (ASD). Although recent developments in complex network analysis have established that the brain is a modular network exhibiting small-world properties, network level organization has not been carefully examined in ASD. Here we used resting-state functional MRI (n = 42 ASD, n = 37 typically developing; TD) to show that children and adolescents with ASD display reduced short and long-range connectivity within functional systems (i.e., reduced functional integration) and stronger connectivity between functional systems (i.e., reduced functional segregation), particularly in default and higher-order visual regions. Using graph theoretical methods, we show that pairwise group differences in functional connectivity are reflected in network level reductions in modularity and clustering (local efficiency), but shorter characteristic path lengths (higher global efficiency). Structural networks, generated from diffusion tensor MRI derived fiber tracts (n = 51 ASD, n = 43 TD), displayed lower levels of white matter integrity yet higher numbers of fibers. TD and ASD individuals exhibited similar levels of correlation between raw measures of structural and functional connectivity (n = 35 ASD, n = 35 TD). However, a principal component analysis combining structural and functional network properties revealed that the balance of local and global efficiency between structural and functional networks was reduced in ASD, positively correlated with age, and inversely correlated with ASD symptom severity. Overall, our findings suggest that modeling the brain as a complex network will be highly informative in unraveling the biological basis of ASD and other neuropsychiatric disorders.
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Such hyper-correlation has been noted in patients with neurologic disorders.
“Such hyper-correlation has been noted in patients with neurologic disorders (Kesler et al., 2017; Rudie et al., 2012; Wirsich et al., 2016).”
From Functional and structural connectome properties in the 5XFAD transgenic mouse model of Alzheimer’s disease (2018) · cites this paper as Rudie et al., 2012
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“Such hyper-correlation has been noted in patients with neurologic disorders (Kesler et al., 2017; Rudie et al., 2012; Wirsich et al., 2016).”
BackgroundHilger, K., & Fiebach, C. J. (2019) · Network Neuroscience · doi:10.1162/netn_a_00083 · Cited by 31 · see citing works
- Authors
- Rudie, J. D., Brown, J. A., Beck-Pancer, D., Hernandez, L. M., Dennis, E. L., Thompson, P. M., Bookheimer, S. Y., & Dapretto, M.
- Affiliations
- University of California, Los Angeles (US)
- Corresponding author
- Rudie, J.D.
- Venue
- NeuroImage: Clinical
- Publisher
- Elsevier BV
- Published
- 2013
- Volume
- 2
- Pages
- 79-94
- ISSN
- 2213-1582 (ISSN-L)
- PMC
- PMC3777708
- OpenAlex
- W2039448553
- Cited by
- 411
- References
- 17
- Citations by year
- 2026: 19 · 2025: 24 · 2024: 22 · 2023: 23 · 2022: 34 · 2021: 41 · 2020: 29 · 2019: 58 · 2018: 28 · 2017: 36 · 2016: 33 · 2015: 33 · 2014: 19 · 2013: 12
- FWCI
- 10.49
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- NeuroImage Clinical (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- Funders
- NICHD (P50 HD055784)
- NIMH (R01 HD06528001)
- UCLA Training Program in Neurobehavioral Genetics (T32 MH073526-05)
- UCLA Medical Scientist Training Program (T32 GM008044)
- NIH (R01 AG040060, EB008432, EB007813, HD050735, RR12169, RR13642, RR00865)
- Autism Speaks
- Brain Mapping Medical Research Organization
- Brain Mapping Support Foundation
- Pierson-Lovelace Foundation
- Ahmanson Foundation
- William M. and Linda R. Dietel Philanthropic Fund at the Northern Piedmont Community Foundation
- Tamkin Foundation
- Jennifer Jones-Simon Foundation
- Capital Group Companies Charitable Foundation
- Robson Family
- North-star Fund
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- autism spectrum disorder, brain network organization, small-world networks, functional connectivity, structural connectivity, white matter integrity, modularity, local efficiency, global efficiency, functional integration, functional segregation, default mode network, visual cortex, diffusion tensor imaging, resting-state fMRI
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 ›
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