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The Dynamics of the Epileptic Brain Reveal Long-Memory Processes

Overview of attention for article published in Frontiers in Neurology, October 2014
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Title
The Dynamics of the Epileptic Brain Reveal Long-Memory Processes
Published in
Frontiers in Neurology, October 2014
DOI 10.3389/fneur.2014.00217
Pubmed ID
Authors

Mark J. Cook, Andrea Varsavsky, David Himes, Kent Leyde, Samuel Frank Berkovic, Terence O’Brien, Iven Mareels

Abstract

The pattern of epileptic seizures is often considered unpredictable and the interval between events without correlation. A number of studies have examined the possibility that seizure activity respects a power-law relationship, both in terms of event magnitude and inter-event intervals. Such relationships are found in a variety of natural and man-made systems, such as earthquakes or Internet traffic, and describe the relationship between the magnitude of an event and the number of events. We postulated that human inter-seizure intervals would follow a power-law relationship, and furthermore that evidence for the existence of a long-memory process could be established in this relationship. We performed a post hoc analysis, studying eight patients who had long-term (up to 2 years) ambulatory intracranial EEG data recorded as part of the assessment of a novel seizure prediction device. We demonstrated that a power-law relationship could be established in these patients (β = - 1.5). In five out of the six subjects whose data were sufficiently stationary for analysis, we found evidence of long memory between epileptic events. This memory spans time scales from 30 min to 40 days. The estimated Hurst exponents range from 0.51 to 0.77 ± 0.01. This finding may provide evidence of phase-transitions underlying the dynamics of epilepsy.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Nigeria 1 2%
Unknown 59 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 20%
Researcher 8 13%
Student > Master 7 12%
Other 6 10%
Student > Doctoral Student 5 8%
Other 8 13%
Unknown 14 23%
Readers by discipline Count As %
Medicine and Dentistry 10 17%
Neuroscience 8 13%
Engineering 6 10%
Computer Science 6 10%
Agricultural and Biological Sciences 5 8%
Other 7 12%
Unknown 18 30%
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 24 October 2014.
All research outputs
#20,241,019
of 22,768,097 outputs
Outputs from Frontiers in Neurology
#8,670
of 11,665 outputs
Outputs of similar age
#217,713
of 260,971 outputs
Outputs of similar age from Frontiers in Neurology
#72
of 86 outputs
Altmetric has tracked 22,768,097 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 11,665 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. 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 86 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.