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Recording Neural Activity Based on Surface Plasmon Resonance by Optical Fibers-A Computational Analysis

Overview of attention for article published in Frontiers in Computational Neuroscience, August 2018
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  • Above-average Attention Score compared to outputs of the same age (60th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

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Title
Recording Neural Activity Based on Surface Plasmon Resonance by Optical Fibers-A Computational Analysis
Published in
Frontiers in Computational Neuroscience, August 2018
DOI 10.3389/fncom.2018.00061
Pubmed ID
Authors

Mitra Abedini, Tahereh Tekieh, Pezhman Sasanpour

Abstract

An all optical, non-destructive method for monitoring neural activity has been proposed and its performance in detection has been analyzed computationally. The proposed method is based on excitation of Surface Plasmon Resonance (SPR) through the structure of optical fibers. The sensor structure consists of a multimode optical fiber where, the cladding of fiber has been removed and thin film of gold structure has been deposited on the surface. Impinging the laser light with appropriate wavelength inside the fiber and based on the total internal reflection, the evanescent wave will excite surface plasmons in the gold thin film. The absorption of light by surface plasmons in the gold structure is severely dependent on the dielectric properties at its vicinity. The electrical activity of neural cells (action potential) can modulate the dielectric properties at its vicinity and hence can modify the absorption of light inside the optical fiber. We have computationally analyzed the performance of the proposed sensor with different available geometries using Finite Element Method (FEM). In this regard, we have shown that the optical response of proposed sensor will track the action potential of the neuron at its vicinity. Based on different geometrical structure, the sensor has absorption in different regions of visible spectrum.

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X Demographics

The data shown below were collected from the profiles of 7 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 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 20%
Student > Master 5 17%
Student > Bachelor 4 13%
Student > Ph. D. Student 4 13%
Student > Doctoral Student 1 3%
Other 1 3%
Unknown 9 30%
Readers by discipline Count As %
Engineering 9 30%
Neuroscience 3 10%
Physics and Astronomy 3 10%
Arts and Humanities 2 7%
Agricultural and Biological Sciences 2 7%
Other 3 10%
Unknown 8 27%
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 23 August 2022.
All research outputs
#7,537,178
of 23,153,849 outputs
Outputs from Frontiers in Computational Neuroscience
#409
of 1,360 outputs
Outputs of similar age
#128,721
of 331,175 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#12
of 29 outputs
Altmetric has tracked 23,153,849 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 1,360 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one has gotten more attention than average, scoring higher than 69% 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 331,175 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 60% of its contemporaries.
We're also able to compare this research output to 29 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 58% of its contemporaries.