| Title |
Analysis of a Scenario for Chaotic Quantal Slowing Down of Inspiration
|
|---|---|
| Published in |
The Journal of Mathematical Neuroscience, September 2013
|
| DOI | 10.1186/2190-8567-3-18 |
| Pubmed ID | |
| Authors |
C Baesens, RS MacKay |
| Abstract |
On exposure to opiates, preparations from rat brain stems have been observed to continue to produce regular expiratory signals, but to fail to produce some inspiratory signals. The numbers of expirations between two successive inspirations form an apparently random sequence. Here, we propose an explanation based on the qualitative theory of dynamical systems. A relatively simple scenario for the dynamics of interaction between the generators of expiratory and inspiratory signals produces pseudo-random behaviour of the type observed. |
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 % |
|---|---|---|
| Italy | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Science communicators (journalists, bloggers, editors) | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Iran, Islamic Republic of | 1 | 10% |
| United Kingdom | 1 | 10% |
| Unknown | 8 | 80% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 1 | 10% |
| Student > Ph. D. Student | 1 | 10% |
| Researcher | 1 | 10% |
| Professor > Associate Professor | 1 | 10% |
| Student > Postgraduate | 1 | 10% |
| Other | 0 | 0% |
| Unknown | 5 | 50% |
| Readers by discipline | Count | As % |
|---|---|---|
| Mathematics | 2 | 20% |
| Agricultural and Biological Sciences | 1 | 10% |
| Neuroscience | 1 | 10% |
| Engineering | 1 | 10% |
| Unknown | 5 | 50% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 21 October 2013.
All research outputs
#16,578,616
of 25,371,288 outputs
Outputs from The Journal of Mathematical Neuroscience
#35
of 79 outputs
Outputs of similar age
#118,655
of 199,085 outputs
Outputs of similar age from The Journal of Mathematical Neuroscience
#2
of 3 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 79 research outputs from this source. They receive a mean Attention Score of 2.7. This one has gotten more attention than average, scoring higher than 55% of its peers.
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We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.