Neuroscience, Connectome, Functional magnetic resonance imaging, Human brain and Resting state fMRI are his primary areas of study. His work in Functional magnetic resonance imaging tackles topics such as Brain activity and meditation which are related to areas like Posterior cingulate, Prefrontal cortex and Default mode network. In his study, Cognitive neuroscience, Human Connectome, Human Connectomes and Blood-oxygen-level dependent is inextricably linked to Bioinformatics, which falls within the broad field of Human brain.
His research integrates issues of Clustering coefficient, Nerve net, Neuroimaging and Brain mapping in his study of Resting state fMRI. His Brain mapping research integrates issues from DICOM, Visualization, Data pre-processing, Artificial intelligence and Pattern recognition. His biological study spans a wide range of topics, including Amplitude of low frequency fluctuations, Magnetic resonance imaging and Positron emission tomography.
His primary scientific interests are in Neuroscience, Resting state fMRI, Default mode network, Functional magnetic resonance imaging and Functional connectivity. His Resting state fMRI research incorporates themes from Audiology, Posterior cingulate, Artificial intelligence, Reliability and Precuneus. His Artificial intelligence research includes elements of Machine learning, Magnetic resonance imaging, Data mining and Pattern recognition.
In his work, Functional brain, Internal medicine, Oncology, Neuroimaging and Clinical psychology is strongly intertwined with Major depressive disorder, which is a subfield of Default mode network. His study in Functional magnetic resonance imaging is interdisciplinary in nature, drawing from both Functional neuroimaging, Connectome, Addiction and Bioinformatics. His work carried out in the field of Bioinformatics brings together such families of science as Human Connectomes and Cognitive neuroscience.
Chao-Gan Yan mainly focuses on Neuroimaging, Default mode network, Major depressive disorder, Resting state fMRI and Artificial intelligence. His Major depressive disorder research is within the category of Neuroscience. His research on Neuroscience often connects related areas such as Chronic schizophrenia.
His work on Dynamic functional connectivity as part of general Resting state fMRI study is frequently linked to Network dynamics, bridging the gap between disciplines. The study incorporates disciplines such as Magnetic resonance imaging and Pattern recognition in addition to Artificial intelligence. His Functional magnetic resonance imaging research is multidisciplinary, incorporating elements of Neuropathology, Connectome, Functional brain and Cortex.
His main research concerns Default mode network, Major depressive disorder, Neuroscience, Resting state fMRI and Prefrontal cortex. While working in this field, he studies both Default mode network and Association. Chao-Gan Yan integrates several fields in his works, including Association, Pattern recognition, Visual cortex, Voxel, Artificial intelligence and Property.
His work on Dynamic functional connectivity is typically connected to Dynamic network analysis as part of general Resting state fMRI study, connecting several disciplines of science. His Dynamic functional connectivity study results in a more complete grasp of Functional magnetic resonance imaging. His work investigates the relationship between Prefrontal cortex and topics such as Neuroimaging that intersect with problems in Neural correlates of consciousness.
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REST: A Toolkit for Resting-State Functional Magnetic Resonance Imaging Data Processing
Xiao-Wei Song;Zhang-Ye Dong;Xiang-Yu Long;Su-Fang Li.
PLOS ONE (2011)
DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging.
Chao-Gan Yan;Xin-Di Wang;Xi-Nian Zuo;Yu-Feng Zang.
A Comprehensive Assessment of Regional Variation in the Impact of Head Micromovements on Functional Connectomics
Chao-Gan Yan;Brian Cheung;Clare Kelly;Stanley J. Colcombe.
The NKI-Rockland Sample: A Model for Accelerating the Pace of Discovery Science in Psychiatry.
Kate Brody Nooner;Kate Brody Nooner;Stanley J. Colcombe;Russell H. Tobe;Maarten Mennes;Maarten Mennes.
Frontiers in Neuroscience (2012)
Uncovering Intrinsic Modular Organization of Spontaneous Brain Activity in Humans
Yong-yong He;Jinhui Wang;Liang Wang;Zhang J. Chen.
PLOS ONE (2009)
Imaging human connectomes at the macroscale
R Cameron Craddock;Saad Jbabdi;Chao-Gan Yan;Chao-Gan Yan;Chao-Gan Yan;Joshua T Vogelstein.
Nature Methods (2013)
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.
Spontaneous brain activity in the default mode network is sensitive to different resting-state conditions with limited cognitive load.
Chaogan Yan;Dongqiang Liu;Yong-yong He;Qihong Zou.
PLOS ONE (2009)
Hemisphere- and gender-related differences in small-world brain networks: a resting-state functional MRI study.
Lixia Tian;Jinhui Wang;Chaogan Yan;Yong He.
Discriminative analysis of early Alzheimer's disease using multi-modal imaging and multi-level characterization with multi-classifier (M3).
Zhengjia Dai;Chaogan Yan;Zhiqun Wang;Jinhui Wang.
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