Evidence map›Paper›PMID 33633670›Full record

ArticleFrontiers in neurology2021

Specific Oscillatory Power Changes and Their Efficacy for Determining Laterality in Mesial Temporal Lobe Epilepsy: A Magnetoencephalographic Study.

Yuta Tanoue, Takehiro Uda, Hideyuki Hoshi, Yoshihito Shigihara, Toshiyuki Kawashima, Kosuke Nakajo, Naohiro Tsuyuguchi, Takeo Goto

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neurology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 29% 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

3 citing papers in PubMed, 9 citations in OpenAlex.

  1. Review
  2. Two Distinct Neural Mechanisms Underlying Acupuncture Analgesia.Frontiers in pain research (Lausanne, Switzerland) · 2022
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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

8 authors at 4 institutions in 1 country.

Yuta TanoueDepartment of Neurosurgery, Graduate School of Medicine, Osaka City University, Osaka, Japan.
Takehiro UdaDepartment of Neurosurgery, Graduate School of Medicine, Osaka City University, Osaka, Japan.
Hideyuki HoshiPrecision Medicine Centre, Hokuto Hospital, Obihiro City, Japan.
Yoshihito ShigiharaPrecision Medicine Centre, Hokuto Hospital, Obihiro City, Japan.
Toshiyuki KawashimaDepartment of Neurosurgery, Graduate School of Medicine, Osaka City University, Osaka, Japan.
Kosuke NakajoDepartment of Neurosurgery, Graduate School of Medicine, Osaka City University, Osaka, Japan.
Naohiro TsuyuguchiDepartment of Neurosurgery, Graduate School of Medicine, Osaka City University, Osaka, Japan.
Takeo GotoDepartment of Neurosurgery, Graduate School of Medicine, Osaka City University, Osaka, Japan.
Osaka City University · JPHokuto Hospital · JPKindai University · JPSaitama Prefectural Kumagaya Girls High School · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Appropriate determination of the epileptic focus and its laterality are important for the diagnosis of mesial temporal lobe epilepsy (MTLE). The aims of this study are to establish a specific oscillatory distribution and laterality of the oscillatory power in unilateral MTLE with frequency analysis of magnetoencephalography (MEG), and to confirm their potential to carry significant information for determining lateralization of the epileptic focus. Thirty-five patients with MTLE [left (LtMTLE), 16; right (RtMTLE), 19] and 102 healthy control volunteers (CTR) were enrolled. Cortical oscillatory powers were compared among the groups by contrasting the source images using a one-way ANOVA model for each frequency band. Further, to compare the lateralization of regional oscillatory powers between LtMTLEs and RtMTLEs, the laterality index (LI) was calculated for four brain regions (frontal, temporal, parietal, and occipital) in each frequency band, which were compared between patient groups (LtMTLE, RtMTLE, and CTR), and used for machine learning prediction of the groups with support vector machine (SVM) with linear kernel function. Significant oscillatory power differences between MTLE and CTR were found in certain areas. In the theta to high-frequency oscillation bands, there were marked increases in the parietal lobe, especially on the left side, in LtMTLE. In the theta, alpha, and high-gamma bands, there were marked increases in the parietal lobe, especially on the right side in RtMTLE. Compared with CTR, LIs were significantly higher in 24/28 regions in LtMTLE, but lower in 4/28 regions and higher in 10/28 regions in RtMTLE. LI at the temporal lobe in the theta band was significantly higher in LtMTLE and significantly lower in RtMTLE. Comparing LtMTLE and RtMTLE, there were significant LI differences in most regions and frequencies (21/28 regions). In all frequency bands, there were significant differences between LtMTLE and RtMTLE in the temporal and parietal lobes. The leave-one-out cross-validation of the linear-SVM showed the classification accuracy to be over 91%, where the model had high specificity over 96% and mild sensitivity ~68-75%. Using MEG frequency analysis, the characteristics of the oscillatory power distribution in the MTLE were demonstrated. Compared with CTR, LIs shifted to the side of the epileptic focus in the temporal lobe in the theta band. The machine learning approach also confirmed that LIs have significant predictive ability in the lateralization of the epileptic focus. These results provide useful additional information for determining the laterality of the focus.

Indexed as

lateralizing signmachine learningmagnetoencephalographymesial temporal lobe epilepsyoscillatory power change

Identifiers

PMID33633670
PMCPMC7900569
OpenAlexW3126532501

What OpenQuestion holds

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Registered trials

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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.