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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Neural Dynamics as Sampling: A Model for Stochastic Computation in Recurrent Networks of Spiking Neurons
|
|---|---|
| Published in |
PLoS Computational Biology, November 2011
|
| DOI | 10.1371/journal.pcbi.1002211 |
| Pubmed ID | |
| Authors |
Lars Buesing, Johannes Bill, Bernhard Nessler, Wolfgang Maass |
X Demographics
The data shown below were collected from the profiles of 15 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 2 | 13% |
| United Kingdom | 1 | 7% |
| Unknown | 12 | 80% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 14 | 93% |
| Science communicators (journalists, bloggers, editors) | 1 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 585 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 18 | 3% |
| Germany | 11 | 2% |
| Switzerland | 8 | 1% |
| France | 8 | 1% |
| United Kingdom | 7 | 1% |
| Australia | 4 | <1% |
| Sweden | 3 | <1% |
| Spain | 2 | <1% |
| Netherlands | 2 | <1% |
| Other | 11 | 2% |
| Unknown | 511 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 184 | 31% |
| Researcher | 121 | 21% |
| Student > Master | 72 | 12% |
| Student > Bachelor | 53 | 9% |
| Professor | 23 | 4% |
| Other | 73 | 12% |
| Unknown | 59 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 122 | 21% |
| Neuroscience | 88 | 15% |
| Engineering | 87 | 15% |
| Agricultural and Biological Sciences | 87 | 15% |
| Physics and Astronomy | 47 | 8% |
| Other | 81 | 14% |
| Unknown | 73 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 33. 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 15 February 2024.
All research outputs
#1,225,052
of 25,738,558 outputs
Outputs from PLoS Computational Biology
#981
of 9,029 outputs
Outputs of similar age
#5,341
of 154,638 outputs
Outputs of similar age from PLoS Computational Biology
#11
of 135 outputs
Altmetric has tracked 25,738,558 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,029 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has done well, scoring higher than 89% 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 154,638 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 96% of its contemporaries.
We're also able to compare this research output to 135 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.