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fMRI at High Spatial Resolution: Implications for BOLD-Models

Overview of attention for article published in Frontiers in Computational Neuroscience, June 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

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Title
fMRI at High Spatial Resolution: Implications for BOLD-Models
Published in
Frontiers in Computational Neuroscience, June 2016
DOI 10.3389/fncom.2016.00066
Pubmed ID
Authors

Jozien Goense, Yvette Bohraus, Nikos K. Logothetis

Abstract

As high-resolution functional magnetic resonance imaging (fMRI) and fMRI of cortical layers become more widely used, the question how well high-resolution fMRI signals reflect the underlying neural processing, and how to interpret laminar fMRI data becomes more and more relevant. High-resolution fMRI has shown laminar differences in cerebral blood flow (CBF), volume (CBV), and neurovascular coupling. Features and processes that were previously lumped into a single voxel become spatially distinct at high resolution. These features can be vascular compartments such as veins, arteries, and capillaries, or cortical layers and columns, which can have differences in metabolism. Mesoscopic models of the blood oxygenation level dependent (BOLD) response therefore need to be expanded, for instance, to incorporate laminar differences in the coupling between neural activity, metabolism and the hemodynamic response. Here we discuss biological and methodological factors that affect the modeling and interpretation of high-resolution fMRI data. We also illustrate with examples from neuropharmacology and the negative BOLD response how combining BOLD with CBF- and CBV-based fMRI methods can provide additional information about neurovascular coupling, and can aid modeling and interpretation of high-resolution fMRI.

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X Demographics

The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 286 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 3 1%
United States 2 <1%
Chile 1 <1%
Japan 1 <1%
Cuba 1 <1%
Unknown 278 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 69 24%
Researcher 45 16%
Student > Master 32 11%
Student > Bachelor 30 10%
Student > Doctoral Student 16 6%
Other 42 15%
Unknown 52 18%
Readers by discipline Count As %
Neuroscience 79 28%
Engineering 31 11%
Psychology 28 10%
Agricultural and Biological Sciences 20 7%
Medicine and Dentistry 15 5%
Other 49 17%
Unknown 64 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 30 October 2017.
All research outputs
#4,991,224
of 24,240,330 outputs
Outputs from Frontiers in Computational Neuroscience
#227
of 1,405 outputs
Outputs of similar age
#84,674
of 358,044 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#8
of 37 outputs
Altmetric has tracked 24,240,330 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,405 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.9. This one has done well, scoring higher than 83% 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 358,044 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
We're also able to compare this research output to 37 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.