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Mendeley readers
Attention Score in Context
| Title |
A Phase-Locking Analysis of Neuronal Firing Rhythms with Transcranial Magneto-Acoustical Stimulation Based on the Hodgkin-Huxley Neuron Model
|
|---|---|
| Published in |
Frontiers in Computational Neuroscience, January 2017
|
| DOI | 10.3389/fncom.2017.00001 |
| Pubmed ID | |
| Authors |
Yi Yuan, Na Pang, Yudong Chen, Yi Wang, Xiaoli Li |
| Abstract |
Transcranial magneto-acoustical stimulation (TMAS) uses ultrasonic waves and a static magnetic field to generate electric current in nerve tissues for the purpose of modulating neuronal activities. It has the advantage of high spatial resolution and penetration depth. Neuronal firing rhythms carry and transmit nerve information in neural systems. In this study, we investigated the phase-locking characteristics of neuronal firing rhythms with TMAS based on the Hodgkin-Huxley neuron model. The simulation results indicate that the modulation frequency of ultrasound can affect the phase-locking behaviors. The results of this study may help us to explain the potential firing mechanism of TMAS. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 25% |
| United States | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 32 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 22% |
| Student > Master | 6 | 19% |
| Researcher | 4 | 13% |
| Student > Doctoral Student | 4 | 13% |
| Student > Bachelor | 3 | 9% |
| Other | 4 | 13% |
| Unknown | 4 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 11 | 34% |
| Neuroscience | 5 | 16% |
| Medicine and Dentistry | 3 | 9% |
| Agricultural and Biological Sciences | 2 | 6% |
| Physics and Astronomy | 2 | 6% |
| Other | 5 | 16% |
| Unknown | 4 | 13% |
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 05 September 2020.
All research outputs
#16,114,739
of 25,470,300 outputs
Outputs from Frontiers in Computational Neuroscience
#746
of 1,466 outputs
Outputs of similar age
#241,466
of 421,344 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#12
of 32 outputs
Altmetric has tracked 25,470,300 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,466 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. This one is in the 45th percentile – i.e., 45% of its peers scored the same or lower than it.
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 421,344 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 32 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 65% of its contemporaries.