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During development, the healthy human brain constructs a host of large-scale, distributed, function-critical neural networks. Neurodegenerative diseases have been thought to target these systems, but this hypothesis has not been systematically tested in living humans. We used network-sensitive neuroimaging methods to show that five different(More)
Resting-state or intrinsic connectivity network functional magnetic resonance imaging provides a new tool for mapping large-scale neural network function and dysfunction. Recently, we showed that behavioural variant frontotemporal dementia and Alzheimer's disease cause atrophy within two major networks, an anterior 'Salience Network' (atrophied in(More)
We propose a novel method to automatically segment subcortical structures of human brain in magnetic resonance images by using fuzzy templates. A set of fuzzy templates of the structures based on features such as intensity, spatial location, and relative spatial relationship among structures are first created from a set of training images by defining the(More)
Structural and functional connectivity methods are changing how researchers conceptualize and explore neuropsychiatric disease. Here, we summarize emerging evidence of large-scale network dysfunction in Alzheimer's disease and behavioral variant frontotemporal dementia, focusing on the divergent impact these disorders have on the default mode network and(More)
Intrinsic or resting state functional connectivity MRI and structural covariance MRI have begun to reveal the adult human brain's multiple network architectures. How and when these networks emerge during development remains unclear, but understanding ontogeny could shed light on network function and dysfunction. In this study, we applied structural(More)
"Resting-state" or task-free fMRI can assess intrinsic connectivity network (ICN) integrity in health and disease, suggesting a potential for use of these methods as disease-monitoring biomarkers. Numerous analytical options are available, including model-driven ROI-based correlation analysis and model-free, independent component analysis (ICA). High(More)
We propose to use dynamic Bayesian networks (DBN) to learn the structure of effective brain connectivity from functional MRI data in an exploratory manner. In our previous work, we used Bayesian networks (BN) to learn the functional structure of the brain (Zheng, X., Rajapakse, J.C., 2006. Learning functional structure from fMR images. NeuroImage 31 (4),(More)
  • Juan Zhou, Efstathios D. Gennatas, Joel H. Kramer, Bruce L. Miller, William W. Seeley
  • 2012
Neurodegenerative diseases target large-scale neural networks. Four competing mechanistic hypotheses have been proposed to explain network-based disease patterning: nodal stress, transneuronal spread, trophic failure, and shared vulnerability. Here, we used task-free fMRI to derive the healthy intrinsic connectivity patterns seeded by brain regions(More)
MicroRNAs (miRNAs) are small regulatory RNAs that modulate the expression of approximately half of all human genes. Small changes in miRNA expression have been associated with several psychiatric and neurological disorders, but whether the polymorphisms in genes involved in the processing of miRNAs into maturity influence the susceptibility of a person to(More)
MicroRNAs (miRNAs) play an important role in the pathogenesis of neoplasm. Single nucleotide polymorphisms (SNPs) within miRNAs can change their phenotype and function. We attempted to analyze the relationship between two SNP loci in miRNAs and colorectal cancer (CRC) in Chinese Han population. We genotyped the polymorphism of two common miRNA SNPs,(More)