Evidence map›Paper›PMID 26021622›Full record

ArticleAJNR. American journal of neuroradiology2015

Influence of Resting-State Network on Lateralization of Functional Connectivity in Mesial Temporal Lobe Epilepsy.

L Su, J An, Q Ma, S Qiu, D Hu

Abstract read
In one paragraph

Article in AJNR. American journal of neuroradiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

16 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Dynamic functional connectivity in temporal lobe epilepsy: a graph theoretical and machine learning approach.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2021
    Article
  9. Dynamical Mechanisms of Interictal Resting-State Functional Connectivity in Epilepsy.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2020
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. 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

5 authors.

L SuFrom the College of Mechatronics and Automation (L.S., Q.M., D.H.), National University of Defense Technology, Changsha, Hunan, People's Republic of China Department of Information Engineering (L.S.), Officers College of Chinese Armed Police Force, Chengdu, Sichuan, China.
J AnDepartment of Medical Imaging (J.A., S.Q.), First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, People's Republic of China.
Q MaFrom the College of Mechatronics and Automation (L.S., Q.M., D.H.), National University of Defense Technology, Changsha, Hunan, People's Republic of China.
S QiuDepartment of Medical Imaging (J.A., S.Q.), First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, People's Republic of China dwhu@nudt.edu.cn qiu-sj@163.com.
D HuFrom the College of Mechatronics and Automation (L.S., Q.M., D.H.), National University of Defense Technology, Changsha, Hunan, People's Republic of China dwhu@nudt.edu.cn qiu-sj@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

background and purposeAlthough most studies on epilepsy have focused on the epileptogenic zone, epilepsy is a system-level disease characterized by aberrant neuronal synchronization among groups of neurons. Increasingly, studies have indicated that mesial temporal lobe epilepsy may be a network-level disease; however, few investigations have examined resting-state functional connectivity of the entire brain, particularly in patients with mesial temporal lobe epilepsy and hippocampal sclerosis. This study primarily investigated whole-brain resting-state functional connectivity abnormality in patients with mesial temporal lobe epilepsy and right hippocampal sclerosis during the interictal period. MATERIALS AND

methodsWe investigated resting-state functional connectivity of 21 patients with mesial temporal lobe epilepsy with right hippocampal sclerosis and 21 neurologically healthy controls. A multivariate pattern analysis was used to identify the functional connections that most clearly differentiated patients with mesial temporal lobe epilepsy with right hippocampal sclerosis from controls.

resultsDiscriminative analysis of functional connections indicated that the patients with mesial temporal lobe epilepsy with right hippocampal sclerosis exhibited decreased resting-state functional connectivity within the right hemisphere and increased resting-state functional connectivity within the left hemisphere. Resting-state network analysis suggested that the internetwork connections typically obey the hemispheric lateralization trend and most of the functional connections that disturb the lateralization trend are the intranetwork ones.

conclusionsThe current findings suggest that weakening of the resting-state functional connectivity associated with the right hemisphere appears to strengthen resting-state functional connectivity on the contralateral side, which may be related to the seizure-induced damage and underlying compensatory mechanisms. Resting-state network-based analysis indicated that the compensatory mechanism among different resting-state networks may disturb the hemispheric lateralization.

Indexed as

AdultBrainBrain MappingEpilepsy, Temporal LobeFemaleFunctional LateralityHumansMagnetic Resonance ImagingMaleMiddle AgedMultivariate AnalysisNerve Net

Identifiers

PMID26021622
PMCPMC7964696

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.