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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Intracellular calcium dynamics permit a Purkinje neuron model to perform toggle and gain computations upon its inputs
|
|---|---|
| Published in |
Frontiers in Computational Neuroscience, August 2014
|
| DOI | 10.3389/fncom.2014.00086 |
| Pubmed ID | |
| Authors |
Michael D. Forrest |
| Abstract |
Without synaptic input, Purkinje neurons can spontaneously fire in a repeating trimodal pattern that consists of tonic spiking, bursting and quiescence. Climbing fiber input (CF) switches Purkinje neurons out of the trimodal firing pattern and toggles them between a tonic firing and a quiescent state, while setting the gain of their response to Parallel Fiber (PF) input. The basis to this transition is unclear. We investigate it using a biophysical Purkinje cell model under conditions of CF and PF input. The model can replicate these toggle and gain functions, dependent upon a novel account of intracellular calcium dynamics that we hypothesize to be applicable in real Purkinje cells. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 11% |
| Canada | 2 | 11% |
| United States | 2 | 11% |
| Spain | 1 | 6% |
| Singapore | 1 | 6% |
| France | 1 | 6% |
| Unknown | 9 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 16 | 89% |
| Scientists | 2 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 58 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Portugal | 1 | 2% |
| France | 1 | 2% |
| Taiwan | 1 | 2% |
| United States | 1 | 2% |
| Philippines | 1 | 2% |
| Unknown | 53 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 16 | 28% |
| Researcher | 11 | 19% |
| Student > Master | 10 | 17% |
| Student > Bachelor | 4 | 7% |
| Student > Postgraduate | 4 | 7% |
| Other | 5 | 9% |
| Unknown | 8 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 13 | 22% |
| Agricultural and Biological Sciences | 10 | 17% |
| Engineering | 7 | 12% |
| Physics and Astronomy | 6 | 10% |
| Computer Science | 4 | 7% |
| Other | 10 | 17% |
| Unknown | 8 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 17. 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 22 May 2024.
All research outputs
#2,072,642
of 24,770,025 outputs
Outputs from Frontiers in Computational Neuroscience
#80
of 1,426 outputs
Outputs of similar age
#20,874
of 241,054 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#4
of 24 outputs
Altmetric has tracked 24,770,025 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,426 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.9. 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 241,054 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 91% of its contemporaries.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.