Evidence map›Paper›PMID 26035672›Full record

ReviewJournal of clinical neurophysiology : official publication of the American Electroencephalographic Society2015

Future of seizure prediction and intervention: closing the loop.

Vivek Nagaraj, Steven T Lee, Esther Krook-Magnuson, Ivan Soltesz, Pascal Benquet, Pedro P Irazoqui, Theoden I Netoff

Open access · greenAbstract readReview
In one paragraph

Review in Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
5.9field-weighted citation impact, top 3% 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

28 citing papers in PubMed, 1 synthesis or guideline pooled it, 80 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. The cerebellum and epilepsy.Epilepsy & behavior : E&B · 2021
    Review
  13. Article
  14. Article
  15. Review
  16. Diverse Applications of Artificial Intelligence in Neuroradiology.Neuroimaging clinics of North America · 2020
    Review
  17. Big data in status epilepticus.Epilepsy & behavior : E&B · 2019
    Review
  18. Article
  19. Article
  20. Ultra Broad Band Neural Activity Portends Seizure Onset in a Rat Model of Epilepsy.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2018
    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

7 authors at 4 institutions in 2 countries.

Vivek Nagaraj*Graduate Program in Neuroscience, University of Minnesota, Minneapolis, MN; †Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN; ‡Department of Anatomy & Neurobiology, University of California, Irvine, CA; §INSERM U1099 LTSI, University of Rennes 1, Rennes, France; and ‖Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN.
Steven T Lee
Esther Krook-Magnuson
Ivan Soltesz
Pascal Benquet
Pedro P Irazoqui
Theoden I Netoff
Purdue University West Lafayette · USUniversity of California, Irvine · USUniversity of Minnesota · USInserm · FR

Funding

PREDOCTORAL TRAINING OF NEUROSCIENTISTST32GM008471 · NIGMS · UNIVERSITY OF MINNESOTA TWIN CITIES · PI EBNER, TIMOTHY J · 1993 to 2017
$4.9M
GABAergic regulation of entorhino-hippocampal excitability in epilepsy.R01NS074432 · NINDS · UNIVERSITY OF CALIFORNIA-IRVINE · PI SOLTESZ, IVAN · 2011 to 2015
$1.6M
On-demand optogenetic cerebellar intervention for temporal lobe epilepsyK99NS087110 · NINDS · UNIVERSITY OF CALIFORNIA-IRVINE · PI KROOK-MAGNUSON, ESTHER · 2014 to 2014
$90k
NIGMS NIH HHS T32 GM008471NINDS NIH HHS K99 NS087110NINDS NIH HHS K99NS087110NINDS NIH HHS NS074432NINDS NIH HHS R01 NS074432
6 · The paper itself

Abstract

The ultimate goal of epilepsy therapies is to provide seizure control for all patients while eliminating side effects. Improved specificity of intervention through on-demand approaches may overcome many of the limitations of current intervention strategies. This article reviews the progress in seizure prediction and detection, potential new therapies to provide improved specificity, and devices to achieve these ends. Specifically, we discuss (1) potential signal modalities and algorithms for seizure detection and prediction, (2) closed-loop intervention approaches, and (3) hardware for implementing these algorithms and interventions. Seizure prediction and therapies maximize efficacy, whereas minimizing side effects through improved specificity may represent the future of epilepsy treatments.

Indexed as

AlgorithmsDeep Brain StimulationElectroencephalographyForecastingHumansNeurophysiological MonitoringOptogeneticsSeizures

Identifiers

PMID26035672
PMCPMC4455045
OpenAlexW2409135931

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.