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Evaluating the Influence of Spatial Resampling for Motion Correction in Resting-State Functional MRI

Overview of attention for article published in Frontiers in Neuroscience, December 2016
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Title
Evaluating the Influence of Spatial Resampling for Motion Correction in Resting-State Functional MRI
Published in
Frontiers in Neuroscience, December 2016
DOI 10.3389/fnins.2016.00591
Pubmed ID
Authors

Lisha Yuan, Hongjian He, Han Zhang, Jianhui Zhong

Abstract

Head motion is one of major concerns in current resting-state functional MRI studies. Image realignment including motion estimation and spatial resampling is often applied to achieve rigid-body motion correction. While the accurate estimation of motion parameters has been addressed in most studies, spatial resampling could also produce spurious variance, and lead to unexpected errors on the amplitude of BOLD signal. In this study, two simulation experiments were designed to characterize these variance related with spatial resampling. The fluctuation amplitude of spurious variance was first investigated using a set of simulated images with estimated motion parameters from a real dataset, and regions more likely to be affected by spatial resampling were found around the peripheral regions of the cortex. The other simulation was designed with three typical types of motion parameters to represent different extents of motion. It was found that areas with significant correlation between spurious variance and head motion scattered all over the brain and varied greatly from one motion type to another. In the last part of this study, four popular motion regression approaches were applied respectively and their performance in reducing spurious variance was compared. Among them, Friston 24 and Voxel-specific 12 model (Friston et al., 1996), were found to have the best outcomes. By separating related effects during fMRI analysis, this study provides a better understanding of the characteristics of spatial resampling and the interpretation of motion-BOLD relationship.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 4%
Unknown 25 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 35%
Researcher 6 23%
Professor > Associate Professor 2 8%
Professor 2 8%
Unknown 7 27%
Readers by discipline Count As %
Engineering 6 23%
Neuroscience 6 23%
Psychology 2 8%
Medicine and Dentistry 2 8%
Social Sciences 1 4%
Other 2 8%
Unknown 7 27%
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 04 January 2017.
All research outputs
#22,759,802
of 25,374,647 outputs
Outputs from Frontiers in Neuroscience
#10,137
of 11,542 outputs
Outputs of similar age
#362,866
of 422,434 outputs
Outputs of similar age from Frontiers in Neuroscience
#138
of 165 outputs
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