ArticleHuman brain mapping2023
Altered default mode network causal connectivity patterns in autism spectrum disorder revealed by Liang information flow analysis.
Article in Human brain mapping, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Atypical Social Behavior is Predicted by Overconnectivity Between Salience and Default Mode Networks in Autism Spectrum Disorder.Journal of autism and developmental disorders · 2026Article
- Autism spectrum disorder across the lifespan: Dynamic symptom trajectories and multidimensional support framework.Molecular psychiatry · 2026Review
- Contribution of attentional mechanisms to verbal and nonverbal communication in boys with ASD.European child & adolescent psychiatry · 2026Article
- <p>Harnessing MSC‑derived exosomes to modulate the pathophysiology of ASD: Recent advances and therapeutic implications (Review)</p>.International journal of molecular medicine · 2026Review
- Structural brain alterations associated with brain age may link to social dysfunction in male adults with autism spectrum disorder.Frontiers in neuroscience · 2026Article
- Quo Vadis translational neuroscience?Translational neuroscience · 2026Review
- Estimation of Information Flow-Based Causality with Coarsely Sampled Time Series.Entropy (Basel, Switzerland) · 2025Article
- Diffusion trajectory of atypical morphological development in autism spectrum disorder.Communications biology · 2025Article
- Causal pathways underlying global soil moisture-precipitation coupling.Nature communications · 2025Article
- rTMS-induced neuroimaging changes measured with structural and functional MRI in autism.Frontiers in neuroscience · 2025Article
- Applying Target Trial Emulation to Evaluate Acupuncture Combined with Rehabilitation for Autism Spectrum Disorder in Children: A Retrospective Single-Center Real-World Protocol.Neuropsychiatric disease and treatment · 2025Article
- Precision neurodiversity: personalized brain network architecture as a window into cognitive variability.Frontiers in human neuroscience · 2025Review
- Identification of autism spectrum disorder using multiple functional connectivity-based graph convolutional network.Medical & biological engineering & computing · 2024Article
- Identifying Diagnostic Biomarkers for Autism Spectrum Disorder From Higher-order Interactions Using the PED Algorithm.Neuroinformatics · 2024Article
- Prefrontal Cortex Responses to Social Video Stimuli in Young Children with and without Autism Spectrum Disorder.Brain sciences · 2024Article
- Altered default mode network causal connectivity patterns in autism spectrum disorder revealed by Liang information flow analysis.Human brain mapping · 2023Article
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Autism spectrum disorder (ASD) is a pervasive developmental disorder with severe cognitive impairment in social communication and interaction. Previous studies have reported that abnormal functional connectivity patterns within the default mode network (DMN) were associated with social dysfunction in ASD. However, how the altered causal connectivity pattern within the DMN affects the social functioning in ASD remains largely unclear. Here, we introduced the Liang information flow method, widely applied to climate science and quantum mechanics, to uncover the brain causal network patterns in ASD. Compared with the healthy controls (HC), we observed that the interactions among the dorsal medial prefrontal cortex (dMPFC), ventral medial prefrontal cortex (vMPFC), hippocampal formation, and temporo-parietal junction showed more inter-regional causal connectivity differences in ASD. For the topological property analysis, we also found the clustering coefficient of DMN and the In-Out degree of anterior medial prefrontal cortex were significantly decreased in ASD. Furthermore, we found that the causal connectivity from dMPFC to vMPFC was correlated with the clinical symptoms of ASD. These altered causal connectivity patterns indicated that the DMN inter-regions information processing was perturbed in ASD. In particular, we found that the dMPFC acts as a causal source in the DMN in HC, whereas it plays a causal target in ASD. Overall, our findings indicated that the Liang information flow method could serve as an important way to explore the DMN causal connectivity patterns, and it also can provide novel insights into the nueromechanisms underlying DMN dysfunction in ASD.
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