Literature DB >> 16538095

Seizure anticipation: from algorithms to clinical practice.

Florian Mormann1, Christian E Elger, Klaus Lehnertz.   

Abstract

PURPOSE OF REVIEW: Our understanding of the mechanisms that lead to the occurrence of epileptic seizures is rather incomplete. If it were possible to identify preictal precursors from the EEG of epilepsy patients, therapeutic possibilities could improve dramatically. Studies on seizure prediction have advanced from preliminary descriptions of preictal phenomena via proof of principle studies and controlled studies to studies on continuous multi-day recordings. RECENT
FINDINGS: Following mostly promising early reports, recent years have witnessed a debate over the reproducibility of results and suitability of approaches. The current literature is inconclusive as to whether seizures are predictable by prospective algorithms. Prospective out-of-sample studies including a statistical validation are missing. Nevertheless, there are indications of a superior performance for approaches characterizing relations between different brain regions.
SUMMARY: Prediction algorithms must be proven to perform better than a random predictor before prospective clinical trials involving seizure intervention techniques in patients can be justified.

Entities:  

Mesh:

Year:  2006        PMID: 16538095     DOI: 10.1097/01.wco.0000218237.52593.bc

Source DB:  PubMed          Journal:  Curr Opin Neurol        ISSN: 1350-7540            Impact factor:   5.710


  15 in total

1.  Synchrony in normal and focal epileptic brain: the seizure onset zone is functionally disconnected.

Authors:  Christopher P Warren; Sanqing Hu; Matt Stead; Benjamin H Brinkmann; Mark R Bower; Gregory A Worrell
Journal:  J Neurophysiol       Date:  2010-10-06       Impact factor: 2.714

2.  Seizure prediction: methods.

Authors:  Paul R Carney; Stephen Myers; James D Geyer
Journal:  Epilepsy Behav       Date:  2011-12       Impact factor: 2.937

Review 3.  Seizure prediction and its applications.

Authors:  Leon D Iasemidis
Journal:  Neurosurg Clin N Am       Date:  2011-10       Impact factor: 2.509

4.  Predicting state transitions in brain dynamics through spectral difference of phase-space graphs.

Authors:  Patrick Luckett; Elena Pavelescu; Todd McDonald; Lee Hively; Juan Ochoa
Journal:  J Comput Neurosci       Date:  2018-10-12       Impact factor: 1.621

5.  A rule-based seizure prediction method for focal neocortical epilepsy.

Authors:  Ardalan Aarabi; Bin He
Journal:  Clin Neurophysiol       Date:  2012-02-22       Impact factor: 3.708

6.  Epilepsy and nonlinear dynamics.

Authors:  Klaus Lehnertz
Journal:  J Biol Phys       Date:  2008-07-09       Impact factor: 1.365

7.  Seizure prediction in patients with focal hippocampal epilepsy.

Authors:  Ardalan Aarabi; Bin He
Journal:  Clin Neurophysiol       Date:  2017-05-12       Impact factor: 3.708

8.  Patient-specific early seizure detection from scalp electroencephalogram.

Authors:  Georgiy R Minasyan; John B Chatten; Martha J Chatten; Richard N Harner
Journal:  J Clin Neurophysiol       Date:  2010-06       Impact factor: 2.177

9.  A chronic generalized bi-directional brain-machine interface.

Authors:  A G Rouse; S R Stanslaski; P Cong; R M Jensen; P Afshar; D Ullestad; R Gupta; G F Molnar; D W Moran; T J Denison
Journal:  J Neural Eng       Date:  2011-05-05       Impact factor: 5.379

10.  Transition to seizures in the isolated immature mouse hippocampus: a switch from dominant phasic inhibition to dominant phasic excitation.

Authors:  M Derchansky; S S Jahromi; M Mamani; D S Shin; A Sik; P L Carlen
Journal:  J Physiol       Date:  2007-11-08       Impact factor: 5.182

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