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Mendeley readers
Attention Score in Context
| Title |
Theoretical models of synaptic short term plasticity
|
|---|---|
| Published in |
Frontiers in Computational Neuroscience, April 2013
|
| DOI | 10.3389/fncom.2013.00045 |
| Pubmed ID | |
| Authors |
Matthias H. Hennig |
| Abstract |
Short term plasticity is a highly abundant form of rapid, activity-dependent modulation of synaptic efficacy. A shared set of mechanisms can cause both depression and enhancement of the postsynaptic response at different synapses, with important consequences for information processing. Mathematical models have been extensively used to study the mechanisms and roles of short term plasticity. This review provides an overview of existing models and their biological basis, and of their main properties. Special attention will be given to slow processes such as calcium channel inactivation and the effect of activation of presynaptic autoreceptors. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Mexico | 1 | 20% |
| Unknown | 4 | 80% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 302 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 4 | 1% |
| United States | 4 | 1% |
| United Kingdom | 2 | <1% |
| Canada | 1 | <1% |
| New Zealand | 1 | <1% |
| Switzerland | 1 | <1% |
| Denmark | 1 | <1% |
| Belgium | 1 | <1% |
| Greece | 1 | <1% |
| Other | 1 | <1% |
| Unknown | 285 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 79 | 26% |
| Researcher | 43 | 14% |
| Student > Master | 41 | 14% |
| Student > Bachelor | 24 | 8% |
| Student > Doctoral Student | 19 | 6% |
| Other | 46 | 15% |
| Unknown | 50 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 74 | 25% |
| Agricultural and Biological Sciences | 60 | 20% |
| Physics and Astronomy | 24 | 8% |
| Engineering | 23 | 8% |
| Computer Science | 15 | 5% |
| Other | 47 | 16% |
| Unknown | 59 | 20% |
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 10 October 2023.
All research outputs
#7,688,890
of 25,374,647 outputs
Outputs from Frontiers in Computational Neuroscience
#375
of 1,463 outputs
Outputs of similar age
#62,477
of 210,035 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#1
of 1 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
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 gotten more attention than average, scoring higher than 74% 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 210,035 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 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