Functional connectivity
How is brain network organization different in autism?
Open access · cc by · source: Europe PMC
Autism is characterized by a less organized brain network with weaker internal connections within functional networks and a failure to develop typical structural efficiency over time.
How this study connects
Role on claims
Each row is a claim on a concept or method page where this paper supports, challenges, or qualifies the statement. Roles are hand-checked — not a model guess.
Adolescents with autism spectrum disorders demonstrate lower white matter tract integrity and a failure to develop typical, age-related improvements in structural network efficiency.
Evidence for the claim as stated.
Autism spectrum disorder is characterized by altered network topology, featuring reduced functional connectivity within core networks like the default mode, visual, and sensorimotor systems, and less distinct boundaries between these networks.
Evidence for the claim as stated.
Atypical structural and functional brain network properties, including altered white matter tract integrity and atypical developmental efficiency trajectories, correlate with the severity of social and communication symptoms in autism.
Evidence for the claim as stated.
Discoveries this paper informs or conflicts with
- Autism network differences appeared in function and structure at once — in a sample chosen to be able to show them
This paper informs this development.
Study at a glance
- Design
- Case-control — Combined functional and structural brain-network graph metrics in ASD vs typically developing youth
- N
- N=70 · 35 ASD and 35 typically developing with both functional and structural data
- Population
- High-functioning children and adolescents with ASD and typically developing peers recruited through UCLA CART
- Outcome
- Functional and structural brain-network organization metrics in ASD versus typical development
Structured fields used in claim comparison tables when every cited study has a complete layer.
Inspect source passages
How is brain network organization different in autism?
These passages occur verbatim in the stored paper text. They support the points listed below; they do not verify every statement in the explanation.
35 ASD and 35 TD subjects had both functional and structural brain data available.
Both structural and functional data were available for 35 ASD and 35 TD subjects.
264 regions of the brain were used to define the network nodes.
Therefore, we chose this set of 264 regions for whole-brain parcellation.
Key findings
They discovered that the ASD group had significantly lower functional connectivity within major networks like the default mode, visual, and sensorimotor systems, alongside less distinct boundaries between these systems. Structurally, participants with ASD exhibited lower white matter tract integrity (evidenced by higher mean diffusivity) but unexpectedly higher fiber counts in several pathways. Furthermore, typical age-related shifts toward more globally efficient structural networks were altered or absent in adolescents with ASD, and these atypical network properties correlated with social and communication symptom severity.
Methodology
The researchers collected resting-state fMRI and diffusion tensor imaging data from children and adolescents with autism spectrum disorder (ASD) and typically developing (TD) controls. Both structural and functional data were available for 35 ASD and 35 TD subjects. The team modeled the brain as a complex network of 264 brain regions, assessing graph theory metrics like clustering, path length, and modularity to determine how local and global network connectivity differs between groups.
Limitations
This study only included high-functioning children and adolescents, so the results may not generalize to lower-functioning individuals or adults with ASD. Additionally, because the study design is cross-sectional rather than longitudinal, it cannot prove that the observed differences in age-related network trajectories represent actual changes within individual participants over time. Finally, the preprocessing used global signal regression, which remains a debated technique that could potentially alter the apparent strength of negative functional connections.
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