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Xi-Nian Zuo
Researcher at Chinese Academy of Sciences
Publications - 210
Citations - 30340
Xi-Nian Zuo is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Resting state fMRI & Default mode network. The author has an hindex of 62, co-authored 194 publications receiving 23229 citations. Previous affiliations of Xi-Nian Zuo include Max Planck Society & Allen Institute for Brain Science.
Papers
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Journal ArticleDOI
Amplitude of low-frequency oscillations in schizophrenia: a resting state fMRI study.
Matthew J. Hoptman,Matthew J. Hoptman,Xi-Nian Zuo,Pamela D. Butler,Pamela D. Butler,Daniel C. Javitt,Daniel C. Javitt,Debra D'Angelo,Cristina J. Mauro,Michael P. Milham +9 more
TL;DR: Amplitude of low-frequency fluctuations (ALFF) and fractional ALFF (fALFF; the relative amplitude that resides in the low frequencies) are used to examine the amplitude of LFO in schizophrenia to suggest LFO abnormalities in schizophrenia.
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Spatial Topography of Individual-Specific Cortical Networks Predicts Human Cognition, Personality, and Emotion.
Ru Kong,Jingwei Li,Csaba Orban,Mert R. Sabuncu,Hesheng Liu,Alexander Schaefer,Nanbo Sun,Xi-Nian Zuo,Avram J. Holmes,Simon B. Eickhoff,B.T. Thomas Yeo +10 more
TL;DR: Network topography estimated by MS-HBM was more effective for behavioral prediction than network size, as well as network topography Estimated by other parcellation approaches, similar to connectivity strength, which might also serve as a fingerprint of human behavior.
Journal ArticleDOI
Toward reliable characterization of functional homogeneity in the human brain: Preprocessing, scan duration, imaging resolution and computational space
Xi-Nian Zuo,Ting Xu,Lili Jiang,Zhi Yang,Xiao-Yan Cao,Yong He,Yu-Feng Zang,F. Xavier Castellanos,F. Xavier Castellanos,Michael P. Milham,Michael P. Milham +10 more
TL;DR: Inspired by these findings and seeking a highly reliable approach to exploratory analysis of the human functional connectome, an R-fMRI pipeline is established to conduct ReHo computations in both 3-dimensions (volume) and 2-Dimensions (surface).
Journal ArticleDOI
An open science resource for establishing reliability and reproducibility in functional connectomics
Xi-Nian Zuo,Jeffrey S. Anderson,Pierre Bellec,Rasmus M. Birn,Bharat B. Biswal,Janusch Blautzik,John C.S. Breitner,Randy L. Buckner,Vince D. Calhoun,F. Xavier Castellanos,F. Xavier Castellanos,Antao Chen,Bing Chen,Jiangtao Chen,Xu Chen,Stanley J. Colcombe,William Courtney,R. Cameron Craddock,Adriana Di Martino,Hao Ming Dong,Xiaolan Fu,Qiyong Gong,Krzysztof J. Gorgolewski,Ying Han,Ye He,Yong He,Erica J. Ho,Avram J. Holmes,Xiao Hui Hou,Jeremy F. Huckins,Tianzi Jiang,Yi Jiang,William M. Kelley,Clare Kelly,Margaret D. King,Stephen M. LaConte,Janet E. Lainhart,Xu Lei,Huijie Li,Kaiming Li,Kuncheng Li,Qixiang Lin,Dong-Qiang Liu,Jia Liu,Xun Liu,Yijun Liu,Guangming Lu,Jie Lu,Beatriz Luna,Jing Luo,Daniel J. Lurie,Ying Mao,Daniel S. Margulies,Andrew R. Mayer,Thomas Meindl,Mary E. Meyerand,Weizhi Nan,Jared A. Nielsen,David H. O’Connor,David J. Paulsen,Vivek Prabhakaran,Zhigang Qi,Jiang Qiu,Chunhong Shao,Zarrar Shehzad,Weijun Tang,Arno Villringer,Huiling Wang,Kai Wang,Dongtao Wei,Gao-Xia Wei,Xu Chu Weng,Xuehai Wu,Ting Xu,Ning Yang,Zhi Yang,Yu-Feng Zang,Lei Zhang,Qinglin Zhang,Zhe Zhang,Zhiqiang Zhang,Ke Zhao,Zonglei Zhen,Yuan Zhou,Xing Ting Zhu,Michael P. Milham +85 more
TL;DR: The Consortium for Reliability and Reproducibility (CoRR) has aggregated 1,629 typical individuals’ resting state fMRI data from 18 international sites, and is openly sharing them via the International Data-sharing Neuroimaging Initiative (INDI).
Journal ArticleDOI
Standardizing the intrinsic brain: Towards robust measurement of inter-individual variation in 1000 functional connectomes
Chao-Gan Yan,R. Cameron Craddock,R. Cameron Craddock,Xi-Nian Zuo,Yu-Feng Zang,Michael P. Milham,Michael P. Milham +6 more
TL;DR: The present work draws upon standardization approaches commonly used in the microarray gene expression literature, and to a lesser extent recent imaging studies, and compares them with respect to their impact on relationships between common fMRI measures and nuisance variables, as well as phenotypic variables of interest.