What is he best known for?
The fields of study he is best known for:
- Neuroscience
- Statistics
- Cognition
Xi-Nian Zuo mostly deals with Neuroscience, Resting state fMRI, Brain mapping, Functional magnetic resonance imaging and Human brain.
The study incorporates disciplines such as Connectome, Neuroimaging, Voxel, Artificial intelligence and Precuneus in addition to Resting state fMRI.
Xi-Nian Zuo works mostly in the field of Neuroimaging, limiting it down to topics relating to Bioinformatics and, in certain cases, Discovery science, Functional neuroimaging and Computational biology.
The Artificial intelligence study combines topics in areas such as Machine learning and Pattern recognition.
Xi-Nian Zuo interconnects Amplitude of low frequency fluctuations, Nerve net and Functional connectivity in the investigation of issues within Brain mapping.
His study in the fields of Posterior cingulate and Functional Connectivity MRI under the domain of Functional magnetic resonance imaging overlaps with other disciplines such as Systems neuroscience.
His most cited work include:
- Toward discovery science of human brain function (2229 citations)
- REST: A Toolkit for Resting-State Functional Magnetic Resonance Imaging Data Processing (1406 citations)
- DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging. (963 citations)
What are the main themes of his work throughout his whole career to date?
Neuroscience, Resting state fMRI, Default mode network, Functional magnetic resonance imaging and Brain mapping are his primary areas of study.
The Human brain, Connectome, Prefrontal cortex and Cognition research he does as part of his general Neuroscience study is frequently linked to other disciplines of science, such as Systems neuroscience, therefore creating a link between diverse domains of science.
Within one scientific family, Xi-Nian Zuo focuses on topics pertaining to Neuroimaging under Connectome, and may sometimes address concerns connected to Cognitive psychology.
In his study, which falls under the umbrella issue of Resting state fMRI, Machine learning, Smoothing and Bioinformatics is strongly linked to Artificial intelligence.
His research in Functional magnetic resonance imaging intersects with topics in Artificial neural network, Dorsolateral prefrontal cortex, Personality, Brain activity and meditation and Pattern recognition.
His Brain mapping research includes elements of Amplitude of low frequency fluctuations and Nerve net.
He most often published in these fields:
- Neuroscience (63.02%)
- Resting state fMRI (47.40%)
- Default mode network (33.33%)
What were the highlights of his more recent work (between 2018-2021)?
- Artificial intelligence (23.96%)
- Default mode network (33.33%)
- Functional connectivity (21.35%)
In recent papers he was focusing on the following fields of study:
Xi-Nian Zuo mainly investigates Artificial intelligence, Default mode network, Functional connectivity, Neuroscience and Pattern recognition.
His Artificial intelligence research incorporates themes from Machine learning, Sample size determination and Big data.
His research integrates issues of Major depressive disorder, Precuneus, Cortex and Salience in his study of Default mode network.
His studies in Major depressive disorder integrate themes in fields like Resting state fMRI, Internal medicine and Oncology.
His work carried out in the field of Resting state fMRI brings together such families of science as Neuroimaging and Audiology.
His study in Pattern recognition is interdisciplinary in nature, drawing from both Functional magnetic resonance imaging, Generalizability theory and Human Connectome Project.
Between 2018 and 2021, his most popular works were:
- Spatial Topography of Individual-Specific Cortical Networks Predicts Human Cognition, Personality, and Emotion. (197 citations)
- Harnessing reliability for neuroscience research. (102 citations)
- Reduced default mode network functional connectivity in patients with recurrent major depressive disorder. (91 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Neuroscience
- Cognition
His main research concerns Neuroimaging, Default mode network, Cognitive decline, Reliability and Neuroscience.
His Neuroimaging research is multidisciplinary, incorporating elements of Growth chart, Brain network and School age child.
His Reliability study integrates concerns from other disciplines, such as Big data, Neuroscience research, Connectomics and Reproducibility.
He performs integrative study on Neuroscience and Signal variability.
His work deals with themes such as Resting state fMRI and Schizophrenia, which intersect with Temporal cortex.
His study looks at the relationship between Resting state fMRI and topics such as Balance, which overlap with Audiology and Major depressive disorder.
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