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Attention Score in Context
| Title |
Noise Reduction in Arterial Spin Labeling Based Functional Connectivity Using Nuisance Variables
|
|---|---|
| Published in |
Frontiers in Neuroscience, August 2016
|
| DOI | 10.3389/fnins.2016.00371 |
| Pubmed ID | |
| Authors |
Kay Jann, Robert X. Smith, Edgar A. Rios Piedra, Mirella Dapretto, Danny J. J. Wang |
| Abstract |
Arterial Spin Labeling (ASL) perfusion image series have recently been utilized for functional connectivity (FC) analysis in healthy volunteers and children with autism spectrum disorders (ASD). Noise reduction by using nuisance variables has been shown to be necessary to minimize potential confounding effects of head motion and physiological signals on BOLD based FC analysis. The purpose of the present study is to systematically evaluate the effectiveness of different noise reduction strategies (NRS) using nuisance variables to improve perfusion based FC analysis in two cohorts of healthy adults using state of the art 3D background-suppressed (BS) GRASE pseudo-continuous ASL (pCASL) and dual-echo 2D-EPI pCASL sequences. Five different NRS were performed in healthy volunteers to compare their performance. We then compared seed-based FC analysis using 3D BS GRASE pCASL in a cohort of 12 children with ASD (3f/9m, age 12.8 ± 1.3 years) and 13 typically developing (TD) children (1f/12m; age 13.9 ± 3 years) in conjunction with NRS. Regression of different combinations of nuisance variables affected FC analysis from a seed in the posterior cingulate cortex (PCC) to other areas of the default mode network (DMN) in both BOLD and pCASL data sets. Consistent with existing literature on BOLD-FC, we observed improved spatial specificity after physiological noise reduction and improved long-range connectivity using head movement related regressors. Furthermore, 3D BS GRASE pCASL shows much higher temporal SNR compared to dual-echo 2D-EPI pCASL and similar effects of noise reduction as those observed for BOLD. Seed-based FC analysis using 3D BS GRASE pCASL in children with ASD and TD children showed that noise reduction including physiological and motion related signals as nuisance variables is crucial for identifying altered long-range connectivity from PCC to frontal brain areas associated with ASD. This is the first study that systematically evaluated the effects of different NRS on ASL based FC analysis. 3D BS GRASE pCASL is the preferred ASL sequence for FC analysis due to its superior temporal SNR. Removing physiological noise and motion parameters is critical for detecting altered FC in neurodevelopmental disorders such as ASD. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 49 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 20% |
| Student > Master | 9 | 18% |
| Student > Ph. D. Student | 9 | 18% |
| Student > Doctoral Student | 3 | 6% |
| Student > Postgraduate | 3 | 6% |
| Other | 7 | 14% |
| Unknown | 8 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 13 | 27% |
| Engineering | 6 | 12% |
| Medicine and Dentistry | 5 | 10% |
| Psychology | 3 | 6% |
| Agricultural and Biological Sciences | 3 | 6% |
| Other | 9 | 18% |
| Unknown | 10 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 August 2016.
All research outputs
#17,236,404
of 25,374,917 outputs
Outputs from Frontiers in Neuroscience
#7,937
of 11,541 outputs
Outputs of similar age
#231,286
of 354,259 outputs
Outputs of similar age from Frontiers in Neuroscience
#89
of 136 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 31st percentile – i.e., 31% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,541 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. This one is in the 30th percentile – i.e., 30% of its peers scored the same or lower than it.
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We're also able to compare this research output to 136 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.