| Title |
SpineCreator: a Graphical User Interface for the Creation of Layered Neural Models
|
|---|---|
| Published in |
Neuroinformatics, September 2016
|
| DOI | 10.1007/s12021-016-9311-z |
| Pubmed ID | |
| Authors |
A. J. Cope, P. Richmond, S. S. James, K. Gurney, D. J. Allerton |
| Abstract |
There is a growing requirement in computational neuroscience for tools that permit collaborative model building, model sharing, combining existing models into a larger system (multi-scale model integration), and are able to simulate models using a variety of simulation engines and hardware platforms. Layered XML model specification formats solve many of these problems, however they are difficult to write and visualise without tools. Here we describe a new graphical software tool, SpineCreator, which facilitates the creation and visualisation of layered models of point spiking neurons or rate coded neurons without requiring the need for programming. We demonstrate the tool through the reproduction and visualisation of published models and show simulation results using code generation interfaced directly into SpineCreator. As a unique application for the graphical creation of neural networks, SpineCreator represents an important step forward for neuronal modelling. |
X Demographics
The data shown below were collected from the profiles of 2 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 | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 32 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 25% |
| Student > Ph. D. Student | 6 | 19% |
| Student > Master | 4 | 13% |
| Student > Bachelor | 3 | 9% |
| Student > Doctoral Student | 2 | 6% |
| Other | 4 | 13% |
| Unknown | 5 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 10 | 31% |
| Neuroscience | 6 | 19% |
| Computer Science | 5 | 16% |
| Agricultural and Biological Sciences | 3 | 9% |
| Physics and Astronomy | 1 | 3% |
| Other | 2 | 6% |
| Unknown | 5 | 16% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 30 December 2020.
All research outputs
#6,170,774
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Outputs from Neuroinformatics
#119
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Outputs of similar age
#93,384
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Outputs of similar age from Neuroinformatics
#2
of 3 outputs
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So far Altmetric has tracked 405 research outputs from this source. They receive a mean Attention Score of 4.5. This one has gotten more attention than average, scoring higher than 70% of its peers.
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