Atypical hierarchical brain connectivity in autism: Insights from stepwise causal analysis using Liang information flow
Autism spectrum disorder (ASD) is associated with atypical brain connectivity, yet its hierarchical organization remains underexplored. In this study, we applied the Liang information flow method to analyze stepwise causal functional connectivity in ASD, offering a novel approach to understanding ho...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-04-01
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| Series: | NeuroImage |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1053811925001090 |
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| author | Shan Sun Fei Wang Fen Xu Yufeng Deng Jiwang Ma Kai Chen Sheng Guo X. San Liang Tao Zhang |
| author_facet | Shan Sun Fei Wang Fen Xu Yufeng Deng Jiwang Ma Kai Chen Sheng Guo X. San Liang Tao Zhang |
| author_sort | Shan Sun |
| collection | DOAJ |
| description | Autism spectrum disorder (ASD) is associated with atypical brain connectivity, yet its hierarchical organization remains underexplored. In this study, we applied the Liang information flow method to analyze stepwise causal functional connectivity in ASD, offering a novel approach to understanding how different brain networks interact. Using resting-state fMRI data from ASD individuals and healthy controls, we observed significant alterations in both positive and negative causal connections across the ventral attention network, limbic network, frontal-parietal network, and default mode network. These disruptions were detected at multiple hierarchical levels, indicating changes in communication patterns across brain regions. By leveraging features of hierarchical causal connectivity, we achieved high classification accuracy between ASD and healthy individuals. Additionally, changes in network node degrees were found to correlate with ASD clinical symptoms, particularly social and communication behaviors. Our findings provide new insights into disrupted hierarchical brain connectivity in ASD and demonstrate the potential of this approach for distinguishing ASD from typical development. |
| format | Article |
| id | doaj-art-78867e779fa94e2880b12da720ace8f7 |
| institution | OA Journals |
| issn | 1095-9572 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage |
| spelling | doaj-art-78867e779fa94e2880b12da720ace8f72025-08-20T01:54:18ZengElsevierNeuroImage1095-95722025-04-0131012110710.1016/j.neuroimage.2025.121107Atypical hierarchical brain connectivity in autism: Insights from stepwise causal analysis using Liang information flowShan Sun0Fei Wang1Fen Xu2Yufeng Deng3Jiwang Ma4Kai Chen5Sheng Guo6X. San Liang7Tao Zhang8The Artificial Inteligence Department, Division of Frontier Research, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China; Mental Health Education Center, and School of Science, Xihua University, Chengdu ChinaThe Artificial Inteligence Department, Division of Frontier Research, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China; School of Computer and Software, Chengdu Jincheng College, Chengdu, ChinaThe Artificial Inteligence Department, Division of Frontier Research, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, ChinaMental Health Education Center, and School of Science, Xihua University, Chengdu ChinaThe Artificial Inteligence Department, Division of Frontier Research, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, ChinaMental Health Education Center, and School of Science, Xihua University, Chengdu ChinaMental Health Education Center, and School of Science, Xihua University, Chengdu ChinaThe Artificial Inteligence Department, Division of Frontier Research, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China; Department of Atmospheric and Oceanic Sciences, Fudan University, Shanghai, China; Corresponding authors at: The Artificial Inteligence Department, Division of Frontier Research, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China.The Artificial Inteligence Department, Division of Frontier Research, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China; Mental Health Education Center, and School of Science, Xihua University, Chengdu China; Corresponding authors at: The Artificial Inteligence Department, Division of Frontier Research, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China.Autism spectrum disorder (ASD) is associated with atypical brain connectivity, yet its hierarchical organization remains underexplored. In this study, we applied the Liang information flow method to analyze stepwise causal functional connectivity in ASD, offering a novel approach to understanding how different brain networks interact. Using resting-state fMRI data from ASD individuals and healthy controls, we observed significant alterations in both positive and negative causal connections across the ventral attention network, limbic network, frontal-parietal network, and default mode network. These disruptions were detected at multiple hierarchical levels, indicating changes in communication patterns across brain regions. By leveraging features of hierarchical causal connectivity, we achieved high classification accuracy between ASD and healthy individuals. Additionally, changes in network node degrees were found to correlate with ASD clinical symptoms, particularly social and communication behaviors. Our findings provide new insights into disrupted hierarchical brain connectivity in ASD and demonstrate the potential of this approach for distinguishing ASD from typical development.http://www.sciencedirect.com/science/article/pii/S1053811925001090Stepwise causal connectivityASDfMRILiang information flow |
| spellingShingle | Shan Sun Fei Wang Fen Xu Yufeng Deng Jiwang Ma Kai Chen Sheng Guo X. San Liang Tao Zhang Atypical hierarchical brain connectivity in autism: Insights from stepwise causal analysis using Liang information flow NeuroImage Stepwise causal connectivity ASD fMRI Liang information flow |
| title | Atypical hierarchical brain connectivity in autism: Insights from stepwise causal analysis using Liang information flow |
| title_full | Atypical hierarchical brain connectivity in autism: Insights from stepwise causal analysis using Liang information flow |
| title_fullStr | Atypical hierarchical brain connectivity in autism: Insights from stepwise causal analysis using Liang information flow |
| title_full_unstemmed | Atypical hierarchical brain connectivity in autism: Insights from stepwise causal analysis using Liang information flow |
| title_short | Atypical hierarchical brain connectivity in autism: Insights from stepwise causal analysis using Liang information flow |
| title_sort | atypical hierarchical brain connectivity in autism insights from stepwise causal analysis using liang information flow |
| topic | Stepwise causal connectivity ASD fMRI Liang information flow |
| url | http://www.sciencedirect.com/science/article/pii/S1053811925001090 |
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