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Functional Connectivity Mapping in the Animal Model: Principles and Applications of Resting-State fMRI

Overview of attention for article published in Frontiers in Neurology, May 2017
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Title
Functional Connectivity Mapping in the Animal Model: Principles and Applications of Resting-State fMRI
Published in
Frontiers in Neurology, May 2017
DOI 10.3389/fneur.2017.00200
Pubmed ID
Authors

Martin Gorges, Francesco Roselli, Hans-Peter Müller, Albert C. Ludolph, Volker Rasche, Jan Kassubek

Abstract

"Resting-state" fMRI has substantially contributed to the understanding of human and non-human functional brain organization by the analysis of correlated patterns in spontaneous activity within dedicated brain systems. Spontaneous neural activity is indirectly measured from the blood oxygenation level-dependent signal as acquired by echo planar imaging, when subjects quietly "resting" in the scanner. Animal models including disease or knockout models allow a broad spectrum of experimental manipulations not applicable in humans. The non-invasive fMRI approach provides a promising tool for cross-species comparative investigations. This review focuses on the principles of "resting-state" functional connectivity analysis and its applications to living animals. The translational aspect from in vivo animal models toward clinical applications in humans is emphasized. We introduce the fMRI-based investigation of the non-human brain's hemodynamics, the methodological issues in the data postprocessing, and the functional data interpretation from different abstraction levels. The longer term goal of integrating fMRI connectivity data with structural connectomes obtained with tracing and optical imaging approaches is presented and will allow the interrogation of fMRI data in terms of directional flow of information and may identify the structural underpinnings of observed functional connectivity patterns.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 139 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
Unknown 138 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 44 32%
Researcher 25 18%
Student > Master 17 12%
Student > Bachelor 10 7%
Student > Doctoral Student 9 6%
Other 17 12%
Unknown 17 12%
Readers by discipline Count As %
Neuroscience 58 42%
Engineering 11 8%
Medicine and Dentistry 11 8%
Psychology 10 7%
Agricultural and Biological Sciences 7 5%
Other 16 12%
Unknown 26 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 26 May 2017.
All research outputs
#18,547,867
of 22,971,207 outputs
Outputs from Frontiers in Neurology
#7,818
of 11,853 outputs
Outputs of similar age
#236,843
of 310,780 outputs
Outputs of similar age from Frontiers in Neurology
#123
of 177 outputs
Altmetric has tracked 22,971,207 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,853 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one is in the 25th percentile – i.e., 25% of its peers scored the same or lower than it.
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We're also able to compare this research output to 177 others from the same source and published within six weeks on either side of this one. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.