Author
Jing Sui
Other affiliations: Georgia State University, Lovelace Respiratory Research Institute, The Mind Research Network ...read more
Bio: Jing Sui is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Medicine & Resting state fMRI. The author has an hindex of 44, co-authored 200 publications receiving 6158 citations. Previous affiliations of Jing Sui include Georgia State University & Lovelace Respiratory Research Institute.
Papers published on a yearly basis
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TL;DR: There is extensive evidence showing the great potential of neuroimaging data for single subject prediction of various disorders, however, the main bottleneck of this exciting field is still the limited sample size, which could be potentially addressed by modern data sharing models such as the ones discussed in this paper.
699 citations
TL;DR: A number of multivariate methods appearing in previous multimodal fusion reports, mostly fMRI with other modality, which were performed with or without prior information are surveyed.
345 citations
TL;DR: The basic reasons why multimodal data fusion is important and what it can do, and importantly how it can help us avoid wrong conclusions and help compensate for imperfect brain imaging studies are introduced.
330 citations
TL;DR: Although the two patient groups showed several distinct brain patterns from each other and healthy controls, they also shared common abnormalities in prefrontal thalamic WM integrity and in frontal brain mechanisms, suggesting that brain dysfunction and WM disruptions occurred in identified regions for both disorders.
238 citations
TL;DR: A comprehensive analysis of INs reveals a key role for the default mode in both schizophrenia and bipolar disorder.
Abstract: Intrinsic functional brain networks (INs) are regions showing temporal coherence with one another. These INs are present in the context of a task (as opposed to an undirected task such as rest), albeit modulated to a degree both spatially and temporally. Prominent networks include the default mode, attentional fronto-parietal, executive control, bilateral temporal lobe, and motor networks. The characterization of INs has recently gained considerable momentum, however; most previous studies evaluate only a small subset of the INs (e.g., default mode). In this paper we use independent component analysis to study INs decomposed from functional magnetic resonance imaging data collected in a large group of schizophrenia patients, healthy controls, and individuals with bipolar disorder, while performing an auditory oddball task. Schizophrenia and bipolar disorder share significant overlap in clinical symptoms, brain characteristics, and risk genes which motivates our goal of identifying whether functional imaging data can differentiate the two disorders. We tested for group differences in properties of all identified INs including spatial maps, spectra, and functional network connectivity. A small set of default mode, temporal lobe, and frontal networks with default mode regions appearing to play a key role in all comparisons. Bipolar subjects showed more prominent changes in ventromedial and prefrontal default mode regions whereas schizophrenia patients showed changes in posterior default mode regions. Anti-correlations between left parietal areas and dorsolateral prefrontal cortical areas were different in bipolar and schizophrenia patients and amplitude was significantly different from healthy controls in both patient groups. Patients exhibited similar frequency behavior across multiple networks with decreased low frequency power. In summary, a comprehensive analysis of INs reveals a key role for the default mode in both schizophrenia and bipolar disorder.
216 citations
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TL;DR: Hollow micro-/nanostructures are of great interest in many current and emerging areas of technology as discussed by the authors, and a comprehensive overview of synthetic strategies for hollow structures is presented.
Abstract: Hollow micro-/nanostructures are of great interest in many current and emerging areas of technology. Perhaps the best-known example of the former is the use of fly-ash hollow particles generated from coal power plants as partial replacement for Portland cement, to produce concrete with enhanced strength and durability. This review is devoted to the progress made in the last decade in synthesis and applications of hollow micro-/nanostructures. We present a comprehensive overview of synthetic strategies for hollow structures. These strategies are broadly categorized into four themes, which include well-established approaches, such as conventional hard-templating and soft-templating methods, as well as newly emerging methods based on sacrificial templating and template-free synthesis. Success in each has inspired multiple variations that continue to drive the rapid evolution of the field. The Review therefore focuses on the fundamentals of each process, pointing out advantages and disadvantages where appropriate. Strategies for generating more complex hollow structures, such as rattle-type and nonspherical hollow structures, are also discussed. Applications of hollow structures in lithium batteries, catalysis and sensing, and biomedical applications are reviewed.
2,767 citations
TL;DR: Combining data from numerous empirical and computational studies, network approaches strongly suggest that brain hubs play important roles in information integration underpinning numerous aspects of complex cognitive function.
1,760 citations
01 Jan 2016
TL;DR: As you may know, people have search numerous times for their chosen novels like this statistical parametric mapping the analysis of functional brain images, but end up in malicious downloads.
Abstract: Thank you very much for reading statistical parametric mapping the analysis of functional brain images. As you may know, people have search numerous times for their chosen novels like this statistical parametric mapping the analysis of functional brain images, but end up in malicious downloads. Rather than enjoying a good book with a cup of coffee in the afternoon, instead they cope with some infectious bugs inside their desktop computer.
1,719 citations
TL;DR: UK Biobank brain imaging is described and results derived from the first 5,000 participants' data release are presented, which have already yielded a rich range of associations between brain imaging and other measures collected by UK Biobanks.
Abstract: Medical imaging has enormous potential for early disease prediction, but is impeded by the difficulty and expense of acquiring data sets before symptom onset. UK Biobank aims to address this problem directly by acquiring high-quality, consistently acquired imaging data from 100,000 predominantly healthy participants, with health outcomes being tracked over the coming decades. The brain imaging includes structural, diffusion and functional modalities. Along with body and cardiac imaging, genetics, lifestyle measures, biological phenotyping and health records, this imaging is expected to enable discovery of imaging markers of a broad range of diseases at their earliest stages, as well as provide unique insight into disease mechanisms. We describe UK Biobank brain imaging and present results derived from the first 5,000 participants' data release. Although this covers just 5% of the ultimate cohort, it has already yielded a rich range of associations between brain imaging and other measures collected by UK Biobank.
1,343 citations