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Vince Daniel Calhoun
University of New Mexico
985Publications
87H-index
33.5kCitations
Publications 985
Newest
Published on Jun 1, 2019in NeuroImage 5.81
Dongdong Lin9
Estimated H-index: 9
(The Mind Research Network),
Kent E. Hutchison46
Estimated H-index: 46
(CU: University of Colorado Boulder)
+ 6 AuthorsVince Daniel Calhoun87
Estimated H-index: 87
(UNM: University of New Mexico)
Abstract Recent studies have shown a critical role of the gastrointestinal microbiome in brain and behavior via the complex gut–microbiome–brain axis. However, the influence of the oral microbiome in neurological processes is much less studied, especially in response to the stimuli, such as smoking, within the oral microenvironment. Additionally, given the complex structural and functional networks in brain, our knowledge about the relationship between microbiome and brain function through speci...
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Published on Jul 18, 2019in bioRxiv
Ashkan Faghiri1
Estimated H-index: 1
,
Armin Iraji6
Estimated H-index: 6
+ 2 AuthorsVince Daniel Calhoun87
Estimated H-index: 87
Studying functional network connectivity using different imaging modalities has been the focus of many studies in recent years. One category of methods assumes that the connectivity is constant throughout the whole scanning period (e.g. using Pearson correlation to estimate linear correlation between two time series each belonging to a specific region in brain) while others relax this assumption by estimating connectivity at different time scales. The most common way to estimate dynamic function...
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Published on Jul 16, 2019in Human Brain Mapping 4.55
Bhim Mani Adhikari12
Estimated H-index: 12
(UMB: University of Maryland, Baltimore),
L. Elliot Hong32
Estimated H-index: 32
(UMB: University of Maryland, Baltimore)
+ 8 AuthorsShuo Chen10
Estimated H-index: 10
(UMB: University of Maryland, Baltimore)
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Published on Jul 10, 2019 in ISNN (International Symposium on Neural Networks)
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Published on Jan 1, 2018in IEEE Journal of Biomedical and Health Informatics 4.22
Aiying Zhang (Tulane University), Jian Fang5
Estimated H-index: 5
(Tulane University)
+ 2 AuthorsYu-Ping Wang20
Estimated H-index: 20
(Tulane University)
Schizophrenia (SZ) is a chronic and severe mental disorder that affects how a person thinks, feels, and behaves. It has been proposed that this disorder is related to disrupted brain connectivity. With the development of functional magnetic resonance imaging (fMRI), further exploration of brain connectivity was made possible and this hypothesis has been verified. Region-based networks are commonly used for mapping brain connectivity. However, they fail to illustrate the connectivity within regio...
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Katharina M. Kubera9
Estimated H-index: 9
(Heidelberg University),
Mahmoud Rashidi (Heidelberg University)+ 5 AuthorsRobert Christian Wolf31
Estimated H-index: 31
(Heidelberg University)
Abstract There is accumulating neuroimaging evidence for both structural and functional abnormalities in schizophrenia patients with persistent auditory verbal hallucinations (AVH). So far, the direct interrelationships between altered structural and functional changes underlying AVH are unknown. Recently, it has become possible to reveal hidden patterns of neural dysfunction not sufficiently captured by separate analysis of these two modalities. A data-driven fusion method called parallel indep...
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Published on Apr 1, 2019in Journal of Neuroscience Methods 2.79
Mohammad R. Arbabshirani2
Estimated H-index: 2
(The Mind Research Network),
Adrian Preda3
Estimated H-index: 3
(UCI: University of California, Irvine)
+ 9 AuthorsKent A. Kiehl55
Estimated H-index: 55
(The Mind Research Network)
Abstract Background Autocorrelation (AC) in fMRI time-series is a well-known phenomenon, typically attributed to colored noise and therefore removed from the data. We hypothesize that AC reflects systematic and meaningful signal fluctuations that may be tied to neural activity and provide evidence to support this hypothesis. New Method Each fMRI time-series is modeled as an autoregressive process from which the autocorrelation is quantified. Then, autocorrelation during resting-state fMRI and au...
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Published on Jul 1, 2019in NeuroImage: Clinical 3.94
Zening Fu6
Estimated H-index: 6
(The Mind Research Network),
Armin Iraji6
Estimated H-index: 6
(The Mind Research Network)
+ 4 AuthorsVince Daniel Calhoun87
Estimated H-index: 87
(UNM: University of New Mexico)
Abstract Structural and functional brain abnormalities have been widely identified in dementia, but with variable replicability and significant overlap. Alzheimer's disease (AD) and Binswanger's disease (BD) share similar symptoms and common brain changes that can confound diagnosis. In this study, we aimed to investigate correlated structural and functional brain changes in AD and BD by combining resting-state functional magnetic resonance imaging (fMRI) and diffusion MRI. A group independent c...
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Published on Jan 1, 2019in IEEE Transactions on Medical Imaging 7.82
Suchita Bhinge2
Estimated H-index: 2
(UMBC: University of Maryland, Baltimore County),
Rami Mowakeaa1
Estimated H-index: 1
(UMBC: University of Maryland, Baltimore County)
+ 1 AuthorsTülay Adali52
Estimated H-index: 52
(UMBC: University of Maryland, Baltimore County)
Dynamic functional connectivity analysis is an effective way to capture the networks that are functionally associated and continuously changing over the scanning period. However, these methods mostly analyze the dynamic associations across the activation patterns of the spatial networks while assuming that the spatial networks are stationary. Hence, a model that allows for the variability in both domains and reduces the assumptions imposed on the data provides an effective way for extracting spa...
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