The data shown below were collected from the profiles of 11 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
A Theoretical Framework to Derive Simple, Firing-Rate-Dependent Mathematical Models of Synaptic Plasticity
|
|---|---|
| Published in |
Frontiers in Computational Neuroscience, May 2019
|
| DOI | 10.3389/fncom.2019.00026 |
| Pubmed ID | |
| Authors |
Janne Lappalainen, Juliane Herpich, Christian Tetzlaff |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 27% |
| Serbia | 1 | 9% |
| Germany | 1 | 9% |
| United Kingdom | 1 | 9% |
| Unknown | 5 | 45% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 64% |
| Scientists | 4 | 36% |
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 % |
|---|---|---|
| Student > Ph. D. Student | 7 | 23% |
| Student > Master | 5 | 17% |
| Researcher | 4 | 13% |
| Other | 2 | 7% |
| Student > Bachelor | 2 | 7% |
| Other | 3 | 10% |
| Unknown | 7 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 7 | 23% |
| Computer Science | 4 | 13% |
| Engineering | 3 | 10% |
| Unspecified | 1 | 3% |
| Agricultural and Biological Sciences | 1 | 3% |
| Other | 6 | 20% |
| Unknown | 8 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 08 February 2023.
All research outputs
#6,343,044
of 25,339,932 outputs
Outputs from Frontiers in Computational Neuroscience
#267
of 1,455 outputs
Outputs of similar age
#106,280
of 357,893 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#8
of 23 outputs
Altmetric has tracked 25,339,932 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 1,455 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.8. This one has done well, scoring higher than 81% 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 357,893 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 70% of its contemporaries.
We're also able to compare this research output to 23 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 69% of its contemporaries.