| Title |
Managing heterogeneity in the study of neural oscillator dynamics
|
|---|---|
| Published in |
The Journal of Mathematical Neuroscience, March 2012
|
| DOI | 10.1186/2190-8567-2-5 |
| Pubmed ID | |
| Authors |
Carlo R Laing, Yu Zou, Ben Smith, Ioannis G Kevrekidis |
| Abstract |
We consider a coupled, heterogeneous population of relaxation oscillators used to model rhythmic oscillations in the pre-Bötzinger complex. By choosing specific values of the parameter used to describe the heterogeneity, sampled from the probability distribution of the values of that parameter, we show how the effects of heterogeneity can be studied in a computationally efficient manner. When more than one parameter is heterogeneous, full or sparse tensor product grids are used to select appropriate parameter values. The method allows us to effectively reduce the dimensionality of the model, and it provides a means for systematically investigating the effects of heterogeneity in coupled systems, linking ideas from uncertainty quantification to those for the study of network dynamics. |
Mendeley readers
The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 5% |
| Unknown | 19 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 30% |
| Student > Ph. D. Student | 5 | 25% |
| Student > Bachelor | 2 | 10% |
| Student > Postgraduate | 2 | 10% |
| Professor > Associate Professor | 2 | 10% |
| Other | 3 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 5 | 25% |
| Mathematics | 4 | 20% |
| Physics and Astronomy | 3 | 15% |
| Agricultural and Biological Sciences | 1 | 5% |
| Psychology | 1 | 5% |
| Other | 2 | 10% |
| Unknown | 4 | 20% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 14 March 2012.
All research outputs
#22,758,309
of 25,373,627 outputs
Outputs from The Journal of Mathematical Neuroscience
#71
of 79 outputs
Outputs of similar age
#153,475
of 168,992 outputs
Outputs of similar age from The Journal of Mathematical Neuroscience
#2
of 2 outputs
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So far Altmetric has tracked 79 research outputs from this source. They receive a mean Attention Score of 2.7. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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