Evidence map›Paper›PMID 27221325›Full record

ArticleEpilepsia2016

High-frequency brain networks undergo modular breakdown during epileptic seizures.

Stefan Fuertinger, Kristina Simonyan, Michael R Sperling, Ashwini D Sharan, Farid Hamzei-Sichani

Open access · bronzeAbstract read
In one paragraph

Article in Epilepsia, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.2field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 16 citations in OpenAlex.

  1. Connectome-Wide Phenotypical and Genotypical Associations in Focal Dystonia.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2017
    Trial
  2. Networks through the lens of high-frequency oscillations.Frontiers in network physiology · 2024
    Review
  3. Article
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  9. A Magnetoencephalography Study of Pediatric Interictal Neuromagnetic Activity Changes and Brain Network Alterations Caused by Epilepsy in the High Frequency (80-1000 Hz).IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2019
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Stefan FuertingerDepartment of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, U.S.A.
Kristina SimonyanDepartment of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, U.S.A.
Michael R SperlingDepartment of Neurology, Sidney Kimmel College of Medicine, Thomas Jefferson University, Philadelphia, Pennsylvania, U.S.A.
Ashwini D SharanDepartment of Neurosurgery, Sidney Kimmel College of Medicine, Thomas Jefferson University, Philadelphia, Pennsylvania, U.S.A.
Farid Hamzei-SichaniDepartment of Neurosurgery, Sidney Kimmel College of Medicine, Thomas Jefferson University, Philadelphia, Pennsylvania, U.S.A.ORCID 0000-0002-7688-9489
Thomas Jefferson University · USIcahn School of Medicine at Mount Sinai · US

Funding

Brain Networks in DystoniaR01NS088160 · NINDS · MASSACHUSETTS EYE AND EAR INFIRMARY · PI SIMONYAN, KRISTINA · 2015 to 2019
$2.4M
NINDS NIH HHS R01 NS088160
6 · The paper itself

Abstract

objectiveCortical high-frequency oscillations (HFOs; 100-500 Hz) play a critical role in the pathogenesis of epilepsy; however, whether they represent a true epileptogenic process remains largely unknown. HFOs have been recorded in the human cortex but their network dynamics during the transitional period from interictal to ictal phase remain largely unknown. We sought to determine the high-frequency network dynamics of these oscillations in patients with epilepsy who were undergoing intracranial electroencephalographic recording for seizure localization.

methodsWe applied a graph theoretical analysis framework to high-resolution intracranial electroencephalographic recordings of 24 interictal and 24 seizure periods to identify the spatiotemporal evolution of community structure of high-frequency cortical networks at rest and during multiple seizure episodes in patients with intractable epilepsy.

resultsCortical networks at all examined frequencies showed temporally stable community architecture in all 24 interictal periods. During seizure periods, high-frequency networks showed a significant breakdown of their community structure, which was characterized by the emergence of numerous small nodal communities, not limited to seizure foci and encompassing the entire recorded network. Such network disorganization was observed on average 225 s before the electrographic seizure onset and extended on average 190 s after termination of the seizure. Gamma networks were characterized by stable community dynamics during resting and seizure periods. SIGNIFICANCE: Our findings suggest that the modular breakdown of high-frequency cortical networks represents a distinct functional pathology that underlies epileptogenesis and corresponds to a cortical state of highest propensity to generate seizures.

Indexed as

Brain MappingAdultBrainBrain WavesElectroencephalographyEpilepsyHumansImaging, Three-DimensionalLikelihood FunctionsMagnetic Resonance ImagingMaleNerve NetCortical networkEpileptogenesisFunctional connectomeHigh-frequency oscillations

Identifiers

PMID27221325
PMCPMC12880085
OpenAlexW2399490153

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.