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Systemic Low-Frequency Oscillations in BOLD Signal Vary with Tissue Type

Overview of attention for article published in Frontiers in Neuroscience, June 2016
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Title
Systemic Low-Frequency Oscillations in BOLD Signal Vary with Tissue Type
Published in
Frontiers in Neuroscience, June 2016
DOI 10.3389/fnins.2016.00313
Pubmed ID
Authors

Yunjie Tong, Lia M. Hocke, Kimberly P. Lindsey, Sinem B. Erdoğan, Gordana Vitaliano, Carolyn E. Caine, Blaise deB. Frederick

Abstract

Blood-oxygen-level dependent (BOLD) signals are widely used in functional magnetic resonance imaging (fMRI) as a proxy measure of brain activation. However, because these signals are blood-related, they are also influenced by other physiological processes. This is especially true in resting state fMRI, during which no experimental stimulation occurs. Previous studies have found that the amplitude of resting state BOLD is closely related to regional vascular density. In this study, we investigated how some of the temporal fluctuations of the BOLD signal also possibly relate to regional vascular density. We began by identifying the blood-bound systemic low-frequency oscillation (sLFO). We then assessed the distribution of all voxels based on their correlations with this sLFO. We found that sLFO signals are widely present in resting state BOLD signals and that the proportion of these sLFOs in each voxel correlates with different tissue types, which vary significantly in underlying vascular density. These results deepen our understanding of the BOLD signal and suggest new imaging biomarkers based on fMRI data, such as amplitude of low-frequency fluctuation (ALFF) and sLFO, a combination of both, for assessing vascular density.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Chile 1 2%
United States 1 2%
Australia 1 2%
Unknown 47 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 22%
Student > Ph. D. Student 10 20%
Student > Master 7 14%
Professor > Associate Professor 4 8%
Professor 3 6%
Other 6 12%
Unknown 9 18%
Readers by discipline Count As %
Neuroscience 8 16%
Engineering 7 14%
Medicine and Dentistry 7 14%
Psychology 4 8%
Nursing and Health Professions 2 4%
Other 2 4%
Unknown 20 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 December 2016.
All research outputs
#7,896,698
of 25,374,647 outputs
Outputs from Frontiers in Neuroscience
#5,007
of 11,538 outputs
Outputs of similar age
#121,175
of 366,926 outputs
Outputs of similar age from Frontiers in Neuroscience
#78
of 156 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 11,538 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. This one has gotten more attention than average, scoring higher than 56% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 366,926 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 156 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.