| Title |
Population based models of cortical drug response: insights from anaesthesia
|
|---|---|
| Published in |
Cognitive Neurodynamics, September 2008
|
| DOI | 10.1007/s11571-008-9063-z |
| Pubmed ID | |
| Authors |
Brett L. Foster, Ingo Bojak, David T. J. Liley |
| Abstract |
A great explanatory gap lies between the molecular pharmacology of psychoactive agents and the neurophysiological changes they induce, as recorded by neuroimaging modalities. Causally relating the cellular actions of psychoactive compounds to their influence on population activity is experimentally challenging. Recent developments in the dynamical modelling of neural tissue have attempted to span this explanatory gap between microscopic targets and their macroscopic neurophysiological effects via a range of biologically plausible dynamical models of cortical tissue. Such theoretical models allow exploration of neural dynamics, in particular their modification by drug action. The ability to theoretically bridge scales is due to a biologically plausible averaging of cortical tissue properties. In the resulting macroscopic neural field, individual neurons need not be explicitly represented (as in neural networks). The following paper aims to provide a non-technical introduction to the mean field population modelling of drug action and its recent successes in modelling anaesthesia. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 2% |
| Italy | 1 | 2% |
| Australia | 1 | 2% |
| United Kingdom | 1 | 2% |
| Spain | 1 | 2% |
| Unknown | 56 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 18 | 30% |
| Researcher | 14 | 23% |
| Student > Postgraduate | 5 | 8% |
| Professor | 5 | 8% |
| Student > Master | 5 | 8% |
| Other | 11 | 18% |
| Unknown | 3 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 17 | 28% |
| Neuroscience | 7 | 11% |
| Engineering | 7 | 11% |
| Medicine and Dentistry | 7 | 11% |
| Physics and Astronomy | 6 | 10% |
| Other | 12 | 20% |
| Unknown | 5 | 8% |
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 07 May 2021.
All research outputs
#18,444,553
of 22,852,911 outputs
Outputs from Cognitive Neurodynamics
#194
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Outputs of similar age
#80,880
of 87,938 outputs
Outputs of similar age from Cognitive Neurodynamics
#3
of 4 outputs
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