Linking Connectivity Dynamics to Symptom Severity and Cognitive Abilities in Children with Autism Spectrum Disorder: An FNIRS Study
Year: 2025
Type: article
Study design: Observational Study
Abstract: Functional near-infrared spectroscopy (fNIRS) has emerged as a valuable tool for investigating neurobiological markers in children with autism spectrum disorder (ASD). While previous studies have identified abnormal functional connectivity in ASD children compared with typically developing (TD) peers, brain connectivity dynamics and their associations with autism symptoms and cognitive abilities remain underexplored. We analyzed fNIRS data from 44 children (30 boys, 21 ASD/23 TD) aged 2.08–6.67 years while they viewed a silent cartoon. Using sliding window correlation and k -means clustering, we assessed group differences in dynamic connectivity and the correlations with symptom severity and cognitive performance. Our results revealed that children with ASD showed reduced dwell time in a specific brain state and fewer state transitions compared with TD children. These atypical brain state patterns were negatively correlated with autism symptom severity and positively correlated with adaptive behavior and cognitive performance across participants. Mediation analysis revealed that adaptive behavior fully mediated the relationship between brain dynamics and cognitive performance. Furthermore, dynamic connectivity features achieved 74.4% accuracy in distinguishing ASD from TD children. Importantly, the link between brain dynamics and cognitive performance was replicated in an independent TD sample, underscoring the robustness of this finding. Together, these findings highlight altered brain dynamics in young children with ASD and underscore the critical role of adaptive behavior in bridging neural activity and cognitive performance. These insights advance our understanding of neural mechanisms underlying ASD and point to potential pathways for early interventions and clinical applications.
Source: Journal of Neuroscience
Authors: Conghui Su, Yubin Hu, Yifan Liu, Ningxuan Zhang, Liming Tan, Shuiqun Zhang, Aiwen Yi, Yaqiong Xiao
Institutions: Shenzhen University of Advanced Technology, Chinese University of Hong Kong, Chinese University of Hong Kong, Shenzhen, Chinese Academy of Sciences, Shenzhen Institutes of Advanced Technology, Shenzhen-Hong Kong Institute of Brain Science, Third Affiliated Hospital of Guangzhou Medical University
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: hybrid
Awards: G4656437091, G4668810654, G6871943133
OpenAlex ID: W4414538231
