Evidence map›Paper›PMID 25270401›Full record

ArticleEpilepsy research2014

An interictal EEG spectral metric for temporal lobe epilepsy lateralization.

Giridhar P Kalamangalam, Lukas Cara, Nitin Tandon, Jeremy D Slater

Open access · greenAbstract read
In one paragraph

Article in Epilepsy research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.6field-weighted citation impact, top 32% 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

1 citing paper in PubMed, 11 citations in OpenAlex.

  1. A unified statistical model for the human electrocorticogram.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2016
    Article
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

4 authors at 1 institution in 1 country.

Giridhar P KalamangalamDepartment of Neurology, University of Texas Health Science Center, Houston, TX, USA. Electronic address: Giridhar.P.Kalamangalam@uth.tmc.edu.
Lukas CaraDepartment of Neurology, University of Texas Health Science Center, Houston, TX, USA.
Nitin TandonDepartment of Neurosurgery, University of Texas Health Science Center, Houston, TX, USA.
Jeremy D SlaterDepartment of Neurology, University of Texas Health Science Center, Houston, TX, USA.
The University of Texas Health Science Center at Houston · US

Funding

Center for Clinical and Translational Sciences (CCTS)UL1TR000371 · NCATS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI MCPHERSON, DAVID D · 2012 to 2016
$13.4M
Advancing Diagnosis and Functional Localization in Focal Epilepsy with Oxygen-Enhanced MRIK23NS079900 · NINDS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI KALAMANGALAM, GIRIDHAR PADMANABHAN · 2012 to 2016
$982k
NCATS NIH HHS UL1 TR000371NINDS NIH HHS 1K23NS079900-01NINDS NIH HHS K23 NS079900
6 · The paper itself

Abstract

objectiveVisually-obvious abnormalities in the resting baseline EEG--slowing, spiking and high-frequency oscillations (HFOs)--are cardinal, though incompletely understood, features of the seizure onset zone in focal epilepsy. We hypothesized that evidence of cortical network dysfunction in temporal lobe epilepsy (TLE) would persist in the absence of visually-classifiable abnormalities in the baseline EEG recorded within the conventional passband, and that metrics of such dysfunction could serve as a lateralizing diagnostic in TLE.

methodsEpochs of resting EEG without significant abnormalities in light sleep over several days were compared between a group of 10 patients with proven TLE and 10 subjects without epilepsy. A novel laterality metric computed from the line length of normalized power spectra from the temporal channels was compared between the two groups.

resultsSignificant group differences in spectral line length laterality metric were found between the TLE and control group. At the individual level, seven of 10 TLE patients had highly significant laterality metrics, all concordant with the known laterality of their disease. SIGNIFICANCE: Detailed spectral analysis offers novel insight into TLE network behavior, independent of the orthodox abnormalities of EEG slowing, spikes or HFOs. The results may be deployed in a practical diagnostic manner, offer insight into the EEG manifestations of disordered cellular network architecture in TLE, and maybe understood through simple analogy with the theory of linear time-invariant physical systems.

Indexed as

Functional LateralityAdultAgedBrainBrain MappingElectroencephalographyEpilepsy, Temporal LobeFemaleHumansMaleMiddle AgedRestSensitivity and SpecificitySignal Processing, Computer-AssistedSleepYoung AdultEpilepsy surgeryPartial epilepsySynchronization

Identifiers

PMID25270401
PMCPMC4252661
OpenAlexW2113809418

What OpenQuestion holds

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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.