| Title |
A phenomenological model of seizure initiation suggests network structure may explain seizure frequency in idiopathic generalised epilepsy
|
|---|---|
| Published in |
The Journal of Mathematical Neuroscience, January 2012
|
| DOI | 10.1186/2190-8567-2-1 |
| Pubmed ID | |
| Authors |
Oscar Benjamin, Thomas HB Fitzgerald, Peter Ashwin, Krasimira Tsaneva-Atanasova, Fahmida Chowdhury, Mark P Richardson, John R Terry |
| Abstract |
We describe a phenomenological model of seizure initiation, consisting of a bistable switch between stable fixed point and stable limit-cycle attractors. We determine a quasi-analytic formula for the exit time problem for our model in the presence of noise. This formula--which we equate to seizure frequency--is then validated numerically, before we extend our study to explore the combined effects of noise and network structure on escape times. Here, we observe that weakly connected networks of 2, 3 and 4 nodes with equivalent first transitive components all have the same asymptotic escape times. We finally extend this work to larger networks, inferred from electroencephalographic recordings from 35 patients with idiopathic generalised epilepsies and 40 controls. Here, we find that network structure in patients correlates with smaller escape times relative to network structures from controls. These initial findings are suggestive that network structure may play an important role in seizure initiation and seizure frequency. |
Mendeley readers
The data shown below were compiled from readership statistics for 114 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 4 | 4% |
| Germany | 2 | 2% |
| Switzerland | 1 | <1% |
| Korea, Republic of | 1 | <1% |
| Netherlands | 1 | <1% |
| Unknown | 105 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 27 | 24% |
| Researcher | 19 | 17% |
| Professor | 13 | 11% |
| Student > Master | 12 | 11% |
| Student > Bachelor | 5 | 4% |
| Other | 21 | 18% |
| Unknown | 17 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Mathematics | 17 | 15% |
| Agricultural and Biological Sciences | 16 | 14% |
| Medicine and Dentistry | 15 | 13% |
| Neuroscience | 14 | 12% |
| Engineering | 9 | 8% |
| Other | 15 | 13% |
| Unknown | 28 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 04 January 2024.
All research outputs
#7,413,731
of 22,665,794 outputs
Outputs from The Journal of Mathematical Neuroscience
#15
of 80 outputs
Outputs of similar age
#70,045
of 241,642 outputs
Outputs of similar age from The Journal of Mathematical Neuroscience
#2
of 4 outputs
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So far Altmetric has tracked 80 research outputs from this source. They receive a mean Attention Score of 2.6. This one has done well, scoring higher than 80% of its peers.
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