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Astroglial Networks and Implications for Therapeutic Neuromodulation of Epilepsy

Overview of attention for article published in Frontiers in Computational Neuroscience, January 2012
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Title
Astroglial Networks and Implications for Therapeutic Neuromodulation of Epilepsy
Published in
Frontiers in Computational Neuroscience, January 2012
DOI 10.3389/fncom.2012.00061
Pubmed ID
Authors

Mark R. Witcher, Thomas L. Ellis

Abstract

Epilepsy is a common chronic neurologic disorder affecting approximately 1% of the world population. More than one-third of all epilepsy patients have incompletely controlled seizures or debilitating medication side effects in spite of optimal medical management. Medically refractory epilepsy is associated with excess injury and mortality, psychosocial dysfunction, and significant cognitive impairment. Effective treatment options for these patients can be limited. The cellular mechanisms underlying seizure activity are incompletely understood, though we here describe multiple lines of evidence supporting the likely contribution of astroglia to epilepsy, with focus on individual astrocytes and their network functions. Of the emerging therapeutic modalities for epilepsy, one of the most intriguing is the field of neuromodulation. Neuromodulatory treatment, which consists of administering electrical pulses to neural tissue to modulate its activity leading to a beneficial effect, may be an option for these patients. Current modalities consist of vagal nerve stimulation, open and closed-loop stimulation, and transcranial magnetic stimulation. Due to their unique properties, we here present astrocytes as likely important targets for the developing field of neuromodulation in the treatment of epilepsy.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
United Kingdom 1 1%
Germany 1 1%
Unknown 63 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 16%
Researcher 10 15%
Student > Master 10 15%
Professor 8 12%
Other 6 9%
Other 11 16%
Unknown 11 16%
Readers by discipline Count As %
Medicine and Dentistry 13 19%
Neuroscience 13 19%
Agricultural and Biological Sciences 9 13%
Engineering 5 7%
Psychology 3 4%
Other 6 9%
Unknown 18 27%
Attention Score in Context

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 29 August 2012.
All research outputs
#20,165,369
of 22,675,759 outputs
Outputs from Frontiers in Computational Neuroscience
#1,156
of 1,336 outputs
Outputs of similar age
#221,176
of 244,088 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#61
of 69 outputs
Altmetric has tracked 22,675,759 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,336 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 69 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.