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Understanding Epileptiform After-Discharges as Rhythmic Oscillatory Transients

Overview of attention for article published in Frontiers in Computational Neuroscience, April 2017
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Title
Understanding Epileptiform After-Discharges as Rhythmic Oscillatory Transients
Published in
Frontiers in Computational Neuroscience, April 2017
DOI 10.3389/fncom.2017.00025
Pubmed ID
Authors

Gerold Baier, Peter N. Taylor, Yujiang Wang

Abstract

Electro-cortical activity in patients with epilepsy may show abnormal rhythmic transients in response to stimulation. Even when using the same stimulation parameters in the same patient, wide variability in the duration of transient response has been reported. These transients have long been considered important for the mapping of the excitability levels in the epileptic brain but their dynamic mechanism is still not well understood. To investigate the occurrence of abnormal transients dynamically, we use a thalamo-cortical neural population model of epileptic spike-wave activity and study the interaction between slow and fast subsystems. In a reduced version of the thalamo-cortical model, slow wave oscillations arise from a fold of cycles (FoC) bifurcation. This marks the onset of a region of bistability between a high amplitude oscillatory rhythm and the background state. In vicinity of the bistability in parameter space, the model has excitable dynamics, showing prolonged rhythmic transients in response to suprathreshold pulse stimulation. We analyse the state space geometry of the bistable and excitable states, and find that the rhythmic transient arises when the impending FoC bifurcation deforms the state space and creates an area of locally reduced attraction to the fixed point. This area essentially allows trajectories to dwell there before escaping to the stable steady state, thus creating rhythmic transients. In the full thalamo-cortical model, we find a similar FoC bifurcation structure. Based on the analysis, we propose an explanation of why stimulation induced epileptiform activity may vary between trials, and predict how the variability could be related to ongoing oscillatory background activity. We compare our dynamic mechanism with other mechanisms (such as a slow parameter change) to generate excitable transients, and we discuss the proposed excitability mechanism in the context of stimulation responses in the epileptic cortex.

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The data shown below were collected from the profiles of 11 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 4%
Unknown 22 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 30%
Student > Ph. D. Student 4 17%
Student > Doctoral Student 3 13%
Student > Master 2 9%
Lecturer 1 4%
Other 3 13%
Unknown 3 13%
Readers by discipline Count As %
Neuroscience 9 39%
Computer Science 3 13%
Engineering 3 13%
Agricultural and Biological Sciences 2 9%
Physics and Astronomy 1 4%
Other 0 0%
Unknown 5 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 10 November 2021.
All research outputs
#5,523,982
of 22,890,496 outputs
Outputs from Frontiers in Computational Neuroscience
#242
of 1,347 outputs
Outputs of similar age
#87,417
of 309,843 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#7
of 35 outputs
Altmetric has tracked 22,890,496 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,347 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one has done well, scoring higher than 81% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 309,843 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.