| Title |
The Dynamics of Networks of Identical Theta Neurons
|
|---|---|
| Published in |
The Journal of Mathematical Neuroscience, February 2018
|
| DOI | 10.1186/s13408-018-0059-7 |
| Pubmed ID | |
| Authors |
Carlo R. Laing |
| Abstract |
We consider finite and infinite all-to-all coupled networks of identical theta neurons. Two types of synaptic interactions are investigated: instantaneous and delayed (via first-order synaptic processing). Extensive use is made of the Watanabe/Strogatz (WS) ansatz for reducing the dimension of networks of identical sinusoidally-coupled oscillators. As well as the degeneracy associated with the constants of motion of the WS ansatz, we also find continuous families of solutions for instantaneously coupled neurons, resulting from the reversibility of the reduced model and the form of the synaptic input. We also investigate a number of similar related models. We conclude that the dynamics of networks of all-to-all coupled identical neurons can be surprisingly complicated. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 3 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 29 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 24% |
| Student > Bachelor | 4 | 14% |
| Student > Master | 4 | 14% |
| Student > Ph. D. Student | 4 | 14% |
| Professor > Associate Professor | 2 | 7% |
| Other | 2 | 7% |
| Unknown | 6 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Physics and Astronomy | 6 | 21% |
| Mathematics | 4 | 14% |
| Engineering | 3 | 10% |
| Agricultural and Biological Sciences | 2 | 7% |
| Computer Science | 2 | 7% |
| Other | 4 | 14% |
| Unknown | 8 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 29 January 2024.
All research outputs
#3,177,195
of 25,303,733 outputs
Outputs from The Journal of Mathematical Neuroscience
#6
of 77 outputs
Outputs of similar age
#68,855
of 449,932 outputs
Outputs of similar age from The Journal of Mathematical Neuroscience
#1
of 3 outputs
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So far Altmetric has tracked 77 research outputs from this source. They receive a mean Attention Score of 2.8. This one has done particularly well, scoring higher than 93% of its peers.
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