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Differential Path-Length Factor's Effect on the Characterization of Brain's Hemodynamic Response Function: A Functional Near-Infrared Study

Overview of attention for article published in Frontiers in Neuroinformatics, June 2018
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  • Above-average Attention Score compared to outputs of the same age (63rd percentile)
  • Average Attention Score compared to outputs of the same age and source

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2 X users
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1 Wikipedia page

Citations

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23 Dimensions

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64 Mendeley
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Title
Differential Path-Length Factor's Effect on the Characterization of Brain's Hemodynamic Response Function: A Functional Near-Infrared Study
Published in
Frontiers in Neuroinformatics, June 2018
DOI 10.3389/fninf.2018.00037
Pubmed ID
Authors

Muhammad A. Kamran, Malik M. N. Mannann, Myung Yung Jeong

Abstract

Functional near-infrared spectroscopy (fNIRS) has evolved as a neuro-imaging modality over the course of the past two decades. The removal of superfluous information accompanying the optical signal, however, remains a challenge. A comprehensive analysis of each step is necessary to ensure the extraction of actual information from measured fNIRS waveforms. A slight change in shape could alter the features required for fNIRS-BCI applications. In the present study, the effect of the differential path-length factor (DPF) values on the characteristics of the hemodynamic response function (HRF) was investigated. Results were compiled for both simulated data sets and healthy human subjects over a range of DPF values from three to eight. Different sets of activation durations and stimuli were used to generate the simulated signals for further analysis. These signals were split into optical densities under a constrained environment utilizing known values of DPF. Later, different values of DPF were used to analyze the variations of actual HRF. The results, as summarized into four categories, suggest that the DPF can change the main and post-stimuli responses in addition to other interferences. Six healthy subjects participated in this study. Their observed optical brain time-series were fed into an iterative optimization problem in order to estimate the best possible fit of HRF and physiological noises present in the measured signals with free parameters. A series of solutions was derived for different values of DPF in order to analyze the variations of HRF. It was observed that DPF change is responsible for HRF creep from actual values as well as changes in HRF characteristics.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 64 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 22%
Researcher 11 17%
Student > Master 9 14%
Student > Bachelor 7 11%
Professor > Associate Professor 3 5%
Other 6 9%
Unknown 14 22%
Readers by discipline Count As %
Engineering 12 19%
Neuroscience 11 17%
Psychology 5 8%
Medicine and Dentistry 4 6%
Physics and Astronomy 3 5%
Other 11 17%
Unknown 18 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 05 July 2019.
All research outputs
#6,890,605
of 23,083,773 outputs
Outputs from Frontiers in Neuroinformatics
#330
of 757 outputs
Outputs of similar age
#117,942
of 328,061 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#12
of 24 outputs
Altmetric has tracked 23,083,773 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 757 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one has gotten more attention than average, scoring higher than 56% 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 328,061 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.