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Updated: Dec 27, 2025
Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging
Published on: September 12, 2011
A Longitudinal MRI Study of Amygdala and Hippocampal Subfields for Infants with Risk of Autism
Guannan Li1,2, Meng-Hsiang Chen3, Gang Li2
1School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.
Insights
Early autism spectrum disorder (ASD) detection is crucial. This study identifies potential infant brain biomarkers, specifically amygdala and hippocampus overgrowth starting at 6 months, aiding early intervention for autism.
Area of Science:
- Neuroimaging
- Developmental Neuroscience
- Biomarkers
Background:
- Current autism spectrum disorder (ASD) diagnosis relies on behavioral observations at 3-4 years, missing critical early intervention windows.
- Early intervention is vital before 2 years old, but effective early biomarkers for infants at risk of ASD are lacking.
- Previous research shows altered amygdala and hippocampus development in older ASD individuals, but early postnatal trajectories are poorly understood.
Purpose of the Study:
- To investigate early developmental trajectories of the amygdala and hippocampal subfields in infants at risk of ASD.
- To identify potential neuroimaging biomarkers for early detection of autism spectrum disorder.
- To establish volume-based analysis of infant brain structures for ASD risk assessment.
Main Methods:
- A novel deep-learning approach, dilated-dense U-Net, was developed for accurate segmentation of infant amygdala and hippocampal subfields.
- Longitudinal brain imaging data from infants at risk of ASD (ages 6, 12, and 24 months) from the National Database for Autism Research (NDAR) were analyzed.
- Volume-based analysis was performed on segmented amygdala and hippocampal subfields to assess developmental changes.
Main Results:
- The study observed potential overgrowth in the amygdala and cornu ammonis (CA) sectors 1-3 starting as early as 6 months of age in infants at risk of ASD.
- Deep learning segmentation successfully addressed challenges of low tissue contrast and small structure size in infant brain imaging.
- These findings suggest early alterations in specific brain regions may precede typical behavioral diagnosis of ASD.
Conclusions:
- Overgrowth in the amygdala and specific hippocampal subfields (CA1-3) from 6 months of age may serve as an early neuroimaging biomarker for autism spectrum disorder risk.
- The developed deep learning segmentation method enables precise analysis of infant brain structures for early ASD detection.
- Identifying these early biomarkers facilitates timely intervention during a critical developmental window, potentially improving outcomes for infants at risk of ASD.
Abstract:
Currently, there are still no early biomarkers to detect infants with risk of autism spectrum disorder (ASD), which is mainly diagnosed based on behavioral observations at three or four years of age. Since intervention efforts may miss a critical developmental window after 2 years old, it is clinically significant to identify imaging-based biomarkers at an early stage for better intervention, before behavioral diagnostic signs of ASD typically arising. Previous studies on older children and young adults with ASD demonstrate altered developmental trajectories of the amygdala and hippocampus. However, our knowledge on their developmental trajectories in early postnatal stages remains very limited. In this paper, for the first time, we propose a volume-based analysis of the amygdala and hippocampal subfields of the infant subjects with risk of ASD at 6, 12, and 24 months of age. To address the challenge of low tissue contrast and small structural size of infant amygdala and hippocampal subfields, we propose a novel deep-learning approach, dilated-dense U-Net, to digitally segment the amygdala and hippocampal subfields in a longitudinal dataset, the National Database for Autism Research (NDAR). A volume-based analysis is then performed based on the segmentation results. Our study shows that the overgrowth of amygdala and cornu ammonis sectors (CA) 1-3 May start from 6 months of age, which may be related to the emergence of autistic spectrum disorder.
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