Changchun He, Jesus M. Cortes, Yi Ding, Xiaolong Shan, Maoyang Zou, Heng Chen, Huafu Chen, Xianmin Wang, Xujun Duan. Brain Imaging and Behavior, 2025. [pdf]
Abstract
Accumulating neuroimaging evidence suggests that abnormal functional and structural brain connectivity plays a cardinal
role in the pathophysiology of autism spectrum disorder (ASD). Here, we constructed brain networks of functional, structural,
and morphological connectivity using data from functional magnetic resonance imaging (fMRI), diffusion tensor
imaging (DTI), and structural magnetic resonance imaging (sMRI), respectively. The neuroimaging data from a cohort of
50 individuals with ASD and 47 age-, gender- and handedness-matched TDC (age range: 5–18 years) were selected from
the Autism Brain Image Data Exchange database. The combination of the fMRI, sMRI and DTI modalities connectivity
features resulted in a classification accuracy of 82.69% for differentiating individuals with ASD from TDC. This accuracy
surpassed that of any single modality or combination of fMRI and DTI modalities previously examined. Among the fMRI,
sMRI and DTI modalities, the most distinguishing connectivity features were observed in the temporal, parietal, and
occipital lobes from the DTI modality, the prefrontal and parietal lobes from the fMRI modality, and the temporal lobe
from the sMRI modality. In addition, we also found that these distinguishing connectivity features can predict abnormal
social interaction behaviours in ASD. These results highlight the complementary information provided by multimodal
approaches, further emphasizing the pivotal role of multimodal connectivity patterns in unravelling the intricate mechanisms
involved in the pathophysiology of ASD.
