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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.
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Journal ArticleDOI
Toward discovery science of human brain function
Bharat B. Biswal,Maarten Mennes,Xi-Nian Zuo,Suril Gohel,Clare Kelly,Steve M. Smith,Christian F. Beckmann,Jonathan S. Adelstein,Randy L. Buckner,Stan Colcombe,Anne Marie Dogonowski,Monique Ernst,Damien A. Fair,Michelle Hampson,Matthew J. Hoptman,James S. Hyde,Vesa Kiviniemi,Rolf Kötter,Shi-Jiang Li,Ching Po Lin,Mark J. Lowe,Clare E. Mackay,David J. Madden,Kristoffer Hougaard Madsen,Daniel S. Margulies,Helen S. Mayberg,Katie L. McMahon,Christopher S. Monk,Stewart H. Mostofsky,Bonnie J. Nagel,James J. Pekar,Scott Peltier,Steven E. Petersen,Valentin Riedl,Serge A.R.B. Rombouts,Bart Rypma,Bradley L. Schlaggar,Sein Schmidt,Rachael D. Seidler,Greg J. Siegle,Christian Sorg,Gao Jun Teng,Juha Veijola,Arno Villringer,Martin Walter,Lihong Wang,Xu Chu Weng,Susan Whitfield-Gabrieli,Peter C. Williamson,Christian Windischberger,Yu-Feng Zang,Hong Ying Zhang,F. Xavier Castellanos,F. Xavier Castellanos,Michael P. Milham +54 more
TL;DR: The 1000 Functional Connectomes Project (Fcon_1000) as discussed by the authors is a large-scale collection of functional connectome data from 1,414 volunteers collected independently at 35 international centers.
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DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging.
TL;DR: The newly developed toolbox, DPABI, which was evolved from REST and DPARSF is introduced, designed to make data analysis require fewer manual operations, be less time-consuming, have a lower skill requirement, a smaller risk of inadvertent mistakes, and be more comparable across studies.
Journal ArticleDOI
REST: A Toolkit for Resting-State Functional Magnetic Resonance Imaging Data Processing
Xiaowei Song,Zhang-Ye Dong,Xiangyu Long,Su-Fang Li,Xi-Nian Zuo,Chaozhe Zhu,Yong He,Chao-Gan Yan,Yu-Feng Zang,Yu-Feng Zang +9 more
TL;DR: A toolkit for the analysis of RS-fMRI data, namely the RESting-state fMRI data analysis Toolkit (REST), which was developed in MATLAB with graphical user interface (GUI).
Journal ArticleDOI
Local-Global Parcellation of the Human Cerebral Cortex from Intrinsic Functional Connectivity MRI
Alexander Schaefer,Ru Kong,Evan M. Gordon,Timothy O. Laumann,Xi-Nian Zuo,Avram J. Holmes,Simon B. Eickhoff,B.T. Thomas Yeo,B.T. Thomas Yeo +8 more
TL;DR: The results suggest that gwMRF parcellations reveal neurobiologically meaningful features of brain organization and are potentially useful for future applications requiring dimensionality reduction of voxel-wise fMRI data.
Journal ArticleDOI
An improved approach to detection of amplitude of low-frequency fluctuation (ALFF) for resting-state fMRI: fractional ALFF.
Qihong Zou,Chaozhe Zhu,Yihong Yang,Xi-Nian Zuo,Xiangyu Long,Xiangyu Long,Qingjiu Cao,Yufeng Wang,Yu-Feng Zang,Yu-Feng Zang +9 more
TL;DR: The proposed fractional ALFF (fALFF) approach improved the sensitivity and specificity in detecting spontaneous brain activities and the brain areas within the default mode network including posterior cingulate cortex, precuneus, medial prefrontal cortex and bilateral inferior parietal lobule had significantly higher fALFF than the other brain areas.