Evidence map›Paper›PMID 24831083›Full record

ReviewClinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology2014

Graph theory findings in the pathophysiology of temporal lobe epilepsy.

Sharon Chiang, Zulfi Haneef

Abstract readReview
In one paragraph

Review in Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
65citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. A complex network perspective on brain disease.Biological reviews of the Cambridge Philosophical Society · 2026
    Review
  5. Article
  6. Article
  7. Review
  8. Stronger pre-surgical functional connectivity networks are associated with improved surgical outcome in temporal lobe epilepsy.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2025
    Article
  9. Article
  10. Individualized morphological covariation network aberrance associated with seizure relapse after antiseizure medication withdrawal.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025
    Article
  11. Article
  12. Article
  13. Article
  14. Article
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  16. Article
  17. Article
  18. Review
  19. Review
  20. Article

5 more citing papers are in PubMed but not listed here.

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

2 authors.

Sharon ChiangDepartment of Statistics, Rice University, Houston, TX, USA.
Zulfi HaneefDepartment of Neurology, Baylor College of Medicine, Houston, TX, USA; Neurology Care Line, VA Medical Center, Houston, TX, USA. Electronic address: zulfi.haneef@bcm.edu.

Funding

TRAINING PROGRAM IN COMPUTATIONAL BIOLOGY AND MEDICINET15LM007093 · NLM · RICE UNIVERSITY · PI Lydia E. Kavraki · 1992 to 2026
$20.8M
Training Program in Biostatistics for Cancer ResearchT32CA096520 · NCI · RICE UNIVERSITY · PI KIMMEL, MAREK, YUAN, YING · 2003 to 2023
$4.5M
NCI NIH HHS 5T32CA096520-07NCI NIH HHS T32 CA096520NLM NIH HHS 2T15LM007093-21NLM NIH HHS T15 LM007093
6 · The paper itself

Abstract

Temporal lobe epilepsy (TLE) is the most common form of adult epilepsy. Accumulating evidence has shown that TLE is a disorder of abnormal epileptogenic networks, rather than focal sources. Graph theory allows for a network-based representation of TLE brain networks, and has potential to illuminate characteristics of brain topology conducive to TLE pathophysiology, including seizure initiation and spread. We review basic concepts which we believe will prove helpful in interpreting results rapidly emerging from graph theory research in TLE. In addition, we summarize the current state of graph theory findings in TLE as they pertain its pathophysiology. Several common findings have emerged from the many modalities which have been used to study TLE using graph theory, including structural MRI, diffusion tensor imaging, surface EEG, intracranial EEG, magnetoencephalography, functional MRI, cell cultures, simulated models, and mouse models, involving increased regularity of the interictal network configuration, altered local segregation and global integration of the TLE network, and network reorganization of temporal lobe and limbic structures. As different modalities provide different views of the same phenomenon, future studies integrating data from multiple modalities are needed to clarify findings and contribute to the formation of a coherent theory on the pathophysiology of TLE.

Indexed as

Neural Networks, ComputerBrain MappingCells, CulturedDiffusion Tensor ImagingElectroencephalographyEpilepsy, Temporal LobeHumansMagnetic Resonance ImagingMagnetoencephalographyNerve NetTemporal LobeDiffusion tensor imagingFunctional connectivityGraph theoryPathophysiologySmall-world networksTemporal lobe epilepsy

Identifiers

PMID24831083
PMCPMC4281254

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.