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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Spike Timing Dependent Plasticity: A Consequence of More Fundamental Learning Rules
|
|---|---|
| Published in |
Frontiers in Computational Neuroscience, July 2010
|
| DOI | 10.3389/fncom.2010.00019 |
| Pubmed ID | |
| Authors |
Harel Z. Shouval, Samuel S.-H. Wang, Gayle M. Wittenberg |
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 % |
|---|---|---|
| United Kingdom | 1 | 25% |
| Switzerland | 1 | 25% |
| United States | 1 | 25% |
| Unknown | 1 | 25% |
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 406 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 12 | 3% |
| Germany | 11 | 3% |
| United Kingdom | 6 | 1% |
| Switzerland | 5 | 1% |
| France | 2 | <1% |
| Turkey | 1 | <1% |
| India | 1 | <1% |
| Estonia | 1 | <1% |
| Australia | 1 | <1% |
| Other | 4 | <1% |
| Unknown | 362 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 118 | 29% |
| Researcher | 74 | 18% |
| Student > Master | 49 | 12% |
| Student > Bachelor | 29 | 7% |
| Professor > Associate Professor | 21 | 5% |
| Other | 44 | 11% |
| Unknown | 71 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 81 | 20% |
| Neuroscience | 67 | 17% |
| Computer Science | 49 | 12% |
| Engineering | 44 | 11% |
| Physics and Astronomy | 26 | 6% |
| Other | 64 | 16% |
| Unknown | 75 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 18. 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 03 January 2023.
All research outputs
#2,009,970
of 25,373,627 outputs
Outputs from Frontiers in Computational Neuroscience
#73
of 1,463 outputs
Outputs of similar age
#6,982
of 103,850 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#1
of 1 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,463 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. This one has done particularly well, scoring higher than 94% 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 103,850 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them