Multimodal investigation of dynamic brain network alterations in autism spectrum disorder: Linking connectivity dynamics to symptoms and developmental trajectories
Lin Wan,
Yuhang Li,
Gang Zhu,
Dalin Yang,
Fali Li,
Wen Wang,
Jian Chen,
Guang Yang,
Rihui Li
Affiliations
Lin Wan
Senior Department of Pediatrics, The Seventh Medical Center of PLA General Hospital, Beijing, China; Department of Pediatrics, The First Medical Center, Chinese PLA General Hospital, Beijing, China
Yuhang Li
Center for Cognitive and Brain Sciences, Institute of Collaborative Innovation, University of Macau, Taipa, Macau S.A.R., China; Department of Psychology, Faculty of Social Sciences, University of Macau, Taipa, Macau S.A.R., China
Gang Zhu
Senior Department of Pediatrics, The Seventh Medical Center of PLA General Hospital, Beijing, China; Department of Pediatrics, The First Medical Center, Chinese PLA General Hospital, Beijing, China
Dalin Yang
Washington University School of Medicine, Mallinckrodt Institute of Radiology, 4515 McKinley Avenue, St. Louis, Missouri 63110, USA
Fali Li
School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, China
Wen Wang
Senior Department of Pediatrics, The Seventh Medical Center of PLA General Hospital, Beijing, China; Department of Pediatrics, The First Medical Center, Chinese PLA General Hospital, Beijing, China
Jian Chen
Senior Department of Pediatrics, The Seventh Medical Center of PLA General Hospital, Beijing, China; Department of Pediatrics, The First Medical Center, Chinese PLA General Hospital, Beijing, China
Guang Yang
Senior Department of Pediatrics, The Seventh Medical Center of PLA General Hospital, Beijing, China; Department of Pediatrics, The First Medical Center, Chinese PLA General Hospital, Beijing, China; The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China; Corresponding authors.
Rihui Li
Center for Cognitive and Brain Sciences, Institute of Collaborative Innovation, University of Macau, Taipa, Macau S.A.R., China; Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Taipa, Macau S.A.R., China; Corresponding authors.
Background: Autism spectrum disorder (ASD) has been associated with disrupted brain connectivity, yet a comprehensive understanding of the dynamic neural underpinnings remains lacking. This study employed concurrent electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) techniques to investigate dynamic functional connectivity (dFC) patterns and neurovascular characteristics in children with ASD. We also explored associations between neurovascular characteristics and the developmental trajectory of adaptive behavior in individuals with ASD. Methods: Resting-state EEG and fNIRS data were simultaneously recorded from 58 ASD and 63 TD children. We implemented a k-means clustering approach to extract the dFC states for each modality. In addition, a multimodal covariance network (MCN) was constructed from the EEG and fNIRS dFC features to capture the neurovascular characteristics linked to ASD. Results: EEG analyses revealed atypical properties of dFC states in the beta and gamma bands in children with ASD compared to TD children. For fNIRS, the ASD group exhibited atypical properties of dFC states such as duration and transitions relative to the TD group. The MCN analysis revealed significantly suppressed functional covariance between right superior temporal and left Broca's areas, alongside enhanced right dorsolateral prefrontal-left Broca covariance in ASD. Notably, we found that early neurovascular characteristics can predict the developmental progress of adaptive functioning in ASD. Conclusion: The multimodal investigation revealed distinct dFC patterns and neurovascular characteristics associated with ASD, elucidating potential neural mechanisms underlying core symptoms and their developmental trajectories. Our study highlights that integrating complementary neuroimaging modalities may aid in unraveling the complex neurobiology of ASD.
