Evidence map›Paper›PMID 19651549›Full record

ArticleIEEE transactions on bio-medical engineering2009

Analysis of intracerebral EEG recordings of epileptic spikes: insights from a neural network model.

Sophie Demont-Guignard, Pascal Benquet, Urs Gerber, Fabrice Wendling

Open access · greenAbstract read
In one paragraph

Article in IEEE transactions on bio-medical engineering, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
2.0field-weighted citation impact, top 15% 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

18 citing papers in PubMed, 65 citations in OpenAlex.

  1. Article
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  6. Sample Entropy Analysis of Noisy Atrial Electrograms during Atrial Fibrillation.Computational and mathematical methods in medicine · 2018
    Article
  7. Article
  8. Future of seizure prediction and intervention: closing the loop.Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society · 2015
    Review
  9. Article
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  17. Time-domain features of epileptic spikes as potential bio-markers of the epileptogenesis process.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2010
    Article
  18. 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 3 institutions in 2 countries.

Sophie Demont-GuignardInstitut National de la Santé et de la Recherche Médicale (INSERM), U642, Rennes F-35000, France.
Pascal Benquet
Urs Gerber
Fabrice Wendling
Laboratoire Traitement du Signal et de l'Image · FRInserm · FRUniversity of Zurich · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The pathophysiological interpretation of EEG signals recorded with depth electrodes [i.e., local field potentials (LFPs)] during interictal (between seizures) or ictal (during seizures) periods is fundamental in the presurgical evaluation of patients with drug-resistant epilepsy. Our objective was to explain specific shape features of interictal spikes in the hippocampus (observed in LFPs) in terms of cell- and network-related parameters of neuronal circuits that generate these events. We developed a neural network model based on "minimal" but biologically relevant neuron models interconnected through GABAergic and glutamatergic synapses that reproduce the main physiological features of the CA1 subfield. Simulated LFPs were obtained by solving the forward problem (dipole theory) from networks including a large number ( approximately 3000) of cells. Insertion of appropriate parameters allowed the model to simulate events that closely resemble actual epileptic spikes. Moreover, the shape of the early fast component ("spike'') and the late slow component ("negative wave'') was linked to the relative contribution of glutamatergic and GABAergic synaptic currents in pyramidal cells. In addition, the model provides insights about the sensitivity of electrode localization with respect to recorded tissue volume and about the relationship between the LFP and the intracellular activity of principal cells and interneurons represented in the network.

Indexed as

Action PotentialsModels, NeurologicalNeuronsBrainComputer SimulationDiagnosis, Computer-AssistedElectroencephalographyEpilepsyHumansNerve Net

Identifiers

PMID19651549
PMCPMC3245744
OpenAlexW2152530067

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.