Evidence map›Paper›PMID 17414973›Full record

ArticleJournal of clinical neurophysiology : official publication of the American Electroencephalographic Society2007

Tonic-clonic transitions in computer simulation.

William W Lytton, Ahmet Omurtag

Open access · greenAbstract read
In one paragraph

Article in Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society, 2007. 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
2.7field-weighted citation impact, top 9% 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, 36 citations in OpenAlex.

  1. Ephaptic conduction in tonic-clonic seizures.Frontiers in neurology · 2024
    Article
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  16. Computer modelling of epilepsy.Nature reviews. Neuroscience · 2008
    Review
  17. The virtual slice setup.Journal of neuroscience methods · 2008
    Article
  18. Review
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 at 2 institutions in 1 country.

William W LyttonDepartment of Physiology, SUNY Downstate, Brooklyn, NY, USA. billl@neurosim.downstate.edu.
Ahmet Omurtag
Houston Methodist · USSUNY Downstate Health Sciences University · US

Funding

Reverse Engineering Cortical CircuitryR01NS045612 · NINDS · SUNY DOWNSTATE MEDICAL CENTER · PI LYTTON, WILLIAM W · 2004 to 2007
$926k
NINDS NIH HHS R01 NS045612
6 · The paper itself

Abstract

summaryNetwork simulations can help identify underlying mechanisms of epileptic activity that are hard to isolate in biologic preparations. To be useful, simulations must be sufficiently realistic to make possible biologic and clinical prediction. This requirement for large networks of sufficiently detailed neurons raises challenges both with regard to computational load and the difficulty of obtaining insights with large numbers of free parameters and the large amounts of generated data. The authors have addressed these problems by simulating computationally manageable networks of moderate size consisting of 1,000 to 3,000 neurons with multiple intrinsic and synaptic properties. Experiments on these simulations demonstrated the presence of epileptiform behavior in the form of repetitive high-intensity population events (clonic behavior) or latch-up with near maximal activity (tonic behavior). Intrinsic neuronal excitability is not always a predictor of network epileptiform activity but may paradoxically produce antiepileptic effects, depending on the settings of other parameters. Several simulations revealed the importance of random coincident inputs to shift a network from a low-activation to a high-activation epileptiform state. Finally, a simulated anticonvulsant acting on excitability tended to preferentially decrease tonic activity.

Indexed as

Computer SimulationModels, NeurologicalNeural Networks, ComputerAction PotentialsAnimalsAnticonvulsantsNerve NetNeuronsSeizuresSynapsesAnticonvulsants

Identifiers

PMID17414973
PMCPMC2633473
OpenAlexW2032194349

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.