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Neural inhibition can explain negative BOLD responses: A mechanistic modelling and fMRI study

Overview of attention for article published in NeuroImage, July 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

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Title
Neural inhibition can explain negative BOLD responses: A mechanistic modelling and fMRI study
Published in
NeuroImage, July 2017
DOI 10.1016/j.neuroimage.2017.07.002
Pubmed ID
Authors

S. Sten, K. Lundengård, S.T. Witt, G. Cedersund, F. Elinder, M. Engström

Abstract

Functional magnetic resonance imaging (fMRI) of hemodynamic changes captured in the blood oxygen level-dependent (BOLD) response contains information of brain activity. The BOLD response is the result of a complex neurovascular coupling and comes in at least two fundamentally different forms: a positive and a negative deflection. Because of the complexity of the signalling, mathematical modelling can provide vital help in the data analysis. For the positive BOLD response, there are plenty of mathematical models, both physiological and phenomenological. However, for the negative BOLD response, no physiologically based model exists. Here, we expand our previously developed physiological model with the most prominent mechanistic hypothesis for the negative BOLD response: the neural inhibition hypothesis. The model was trained and tested on experimental data containing both negative and positive BOLD responses from two studies: 1) a visual-motor task and 2) a working-memory task in conjunction with administration of the tranquilizer diazepam. Our model was able to predict independent validation data not used for training and provides a mechanistic underpinning for previously observed effects of diazepam. The new model moves our understanding of the negative BOLD response from qualitative reasoning to a quantitative systems-biology level, which can be useful both in basic research and in clinical use.

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The data shown below were collected from the profiles of 40 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 149 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 149 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 33 22%
Researcher 27 18%
Student > Master 21 14%
Student > Doctoral Student 12 8%
Student > Postgraduate 9 6%
Other 27 18%
Unknown 20 13%
Readers by discipline Count As %
Neuroscience 45 30%
Psychology 19 13%
Medicine and Dentistry 14 9%
Agricultural and Biological Sciences 13 9%
Engineering 7 5%
Other 21 14%
Unknown 30 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 22. 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 13 July 2017.
All research outputs
#1,683,282
of 25,382,440 outputs
Outputs from NeuroImage
#1,181
of 12,206 outputs
Outputs of similar age
#32,241
of 326,085 outputs
Outputs of similar age from NeuroImage
#36
of 221 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,206 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.6. This one has done particularly well, scoring higher than 90% 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 326,085 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 221 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.