Evidence map›Paper›PMID 18594562›Full record

ReviewNature reviews. Neuroscience2008

Computer modelling of epilepsy.

William W Lytton

Abstract readReview
In one paragraph

Review in Nature reviews. Neuroscience, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 99 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
99citing 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

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

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39 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

1 author.

William W LyttonDepartment of Physiology, State University of New York, Downstate Medical Center, Brooklyn, New York, USA. billl@neurosim.downstate.edu

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

Epilepsy is a complex set of disorders that can involve many areas of the cortex, as well as underlying deep-brain systems. The myriad manifestations of seizures, which can be as varied as déjà vu and olfactory hallucination, can therefore give researchers insights into regional functions and relations. Epilepsy is also complex genetically and pathophysiologically: it involves microscopic (on the scale of ion channels and synaptic proteins), macroscopic (on the scale of brain trauma and rewiring) and intermediate changes in a complex interplay of causality. It has long been recognized that computer modelling will be required to disentangle causality, to better understand seizure spread and to understand and eventually predict treatment efficacy. Over the past few years, substantial progress has been made in modelling epilepsy at levels ranging from the molecular to the socioeconomic. We review these efforts and connect them to the medical goals of understanding and treating the disorder.

Indexed as

Computer SimulationModels, NeurologicalAnimalsBrainCerebral CortexEpilepsyEpilepsy, Temporal LobeHumansMarkov ChainsPredictive Value of TestsSeizures

Identifiers

PMID18594562
PMCPMC2739976

What OpenQuestion holds

Textmetadata
LicenceTDM
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.