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Xujun Duan
Researcher at University of Electronic Science and Technology of China
Publications - 97
Citations - 4530
Xujun Duan is an academic researcher from University of Electronic Science and Technology of China. The author has contributed to research in topics: Resting state fMRI & Autism spectrum disorder. The author has an hindex of 32, co-authored 86 publications receiving 3400 citations. Previous affiliations of Xujun Duan include Xinxiang Medical University & Stanford University.
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Journal ArticleDOI
Altered Functional Connectivity and Small-World in Mesial Temporal Lobe Epilepsy
Wei-Ting Liao,Zhiqiang Zhang,Zhengyong Pan,Dante Mantini,Dante Mantini,Jurong Ding,Xujun Duan,Cheng Luo,Guangming Lu,Huafu Chen +9 more
TL;DR: The mTLE alterations observed in functional connectivity and topological properties may be used to define tentative disease markers, including altered small-world properties in patients, along with smaller degree of connectivity, increased n-to-1 connectivity, smaller absolute clustering coefficients and shorter absolute path length.
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Default mode network abnormalities in mesial temporal lobe epilepsy: a study combining fMRI and DTI.
Wei Liao,Zhiqiang Zhang,Zhengyong Pan,Dante Mantini,Jurong Ding,Xujun Duan,Cheng Luo,Zhengge Wang,Qifu Tan,Guangming Lu,Huafu Chen +10 more
TL;DR: The results suggest that the decreased functional connectivity within the DMN in mTLE may be a consequence of the decreased connection density underpinning the degeneration of structural connectivity.
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Selective aberrant functional connectivity of resting state networks in social anxiety disorder.
Wei Liao,Huafu Chen,Yuanbo Feng,Dante Mantini,Claudio Gentili,Zhengyong Pan,Jurong Ding,Xujun Duan,Changjian Qiu,Su Lui,Qiyong Gong,Weiwei Zhang +11 more
TL;DR: A relationship between functional connectivity and disease severity was found in specific regions of RSNs, including medial and lateral prefrontal cortex, as well as parietal and occipital regions.
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Amygdala subregional structure and intrinsic functional connectivity predicts individual differences in anxiety during early childhood.
TL;DR: Individual differences in anxiety can be reliably detected with high predictive value in amygdala-centric emotion circuits at a surprisingly young age and has significant implications for the development of predictive biomarkers to identify children at risk for anxiety disorders.
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Multivariate classification of autism spectrum disorder using frequency-specific resting-state functional connectivity--A multi-center study.
TL;DR: These findings provide preliminary evidence for frequency-specific whole brain functional connectivity indices that may eventually be used to aid detection of ASD.