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Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging
Published on: September 12, 2011
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Age-dependent white matter microstructural disintegrity in autism spectrum disorder
Clara F Weber1,2, Evelyn M R Lake1, Stefan P Haider1,3
1Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, United States.
Frontiers in Neuroscience
|September 26, 2022
Summary
Autism Spectrum Disorder (ASD) shows age-dependent white matter (WM) changes. Microstructural integrity and connectome disruptions in ASD emerge in adolescence and young adulthood, not infancy or toddlerhood.
Area of Science:
- Neuroscience
- Developmental Neuroscience
- Autism Spectrum Disorder Research
Background:
- Autism Spectrum Disorder (ASD) is associated with white matter (WM) microstructural abnormalities and disrupted brain connectivity.
- Understanding the developmental trajectory of these changes is crucial for early identification and intervention.
Purpose of the Study:
- To investigate the age-dependent effects of ASD on WM microstructure and connectome integrity.
- To examine Diffusion Tensor Imaging (DTI) metrics and Edge Density (ED) across different age groups in individuals with and without ASD.
- To evaluate the predictive performance of machine learning models for ASD diagnosis based on neuroimaging data.
Main Methods:
- Analysis of Diffusion Tensor Imaging (DTI) metrics (FA, MD, RD, AD) and connectome Edge Density (ED) in 583 subjects across four age cohorts (infants, toddlers, adolescents, young adults).
- Voxel-wise and tract-based analyses were conducted to assess the impact of age, ASD diagnosis, and sex.
- Machine learning classifiers were trained and validated for ASD diagnosis prediction using DTI and ED metrics.
Main Results:
- An age-dependent increase in Fractional Anisotropy (FA) and decrease in Mean Diffusivity (MD) and Radial Diffusivity (RD) were observed across WM tracts in all age groups.
- Autism Spectrum Disorder (ASD)-related decreases in FA and ED were found in adolescents and young adults, but not in infants or toddlers.
- Connectome Edge Density (ED) showed a more widespread ASD-related decrease than DTI metrics, particularly in the corpus callosum.
Conclusions:
- White matter (WM) microstructural disintegrity and connectome disruption in ASD become apparent during adolescence and young adulthood.
- The findings suggest that neuroimaging markers for ASD may differ across developmental stages.
- Machine learning models show potential for ASD diagnosis, with an AUC of 0.70 in validation.
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