Document Detail


Active paradigms of seizure anticipation: computer model evidence for necessity of stimulation.
MedLine Citation:
PMID:  19113165     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
It has been shown that the analysis of electroencephalographic (EEG) signals submitted to an appropriate external stimulation (active paradigm) is efficient with respect to anticipating epileptic seizures [S. Kalitzin, Clin. Neurophysiol. 116, 718 (2005)]. To better understand how an active paradigm is able to detect properties of EEG signals by means of which proictal states can be identified, we performed a simulation study using a computational model of seizure generation of a hippocampal network. Applying the active stimulation methodology, we investigated (i) how changes in model parameters that lead to a transition from the normal ongoing EEG to an ictal pattern are reflected in the properties of the simulated EEG output signals and (ii) how the evolution of neuronal excitability towards seizures can be reconstructed from EEG data using an active paradigm, rather than passively, using only ongoing EEG signals. The simulations indicate that a stimulation paradigm combined with appropriate analytical tools, as proposed here, may yield information about the change in excitability that precedes the transition to a seizure. Such information is apparently not fully reflected in the ongoing EEG activity. These findings give strong support to the development and application of active paradigms with the aim of predicting the occurrence of a transition to an epileptic seizure.
Authors:
Piotr Suffczynski; Stiliyan Kalitzin; Fernando Lopes da Silva; Jaime Parra; Demetrios Velis; Fabrice Wendling
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2008-11-19
Journal Detail:
Title:  Physical review. E, Statistical, nonlinear, and soft matter physics     Volume:  78     ISSN:  1539-3755     ISO Abbreviation:  Phys Rev E Stat Nonlin Soft Matter Phys     Publication Date:  2008 Nov 
Date Detail:
Created Date:  2008-12-30     Completed Date:  2009-04-27     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101136452     Medline TA:  Phys Rev E Stat Nonlin Soft Matter Phys     Country:  United States    
Other Details:
Languages:  eng     Pagination:  051917     Citation Subset:  IM    
Affiliation:
Department of Biomedical Physics, Faculty of Physics, University of Warsaw, 00-681 Warsaw, Poland.
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MeSH Terms
Descriptor/Qualifier:
Awareness*
Computer Simulation
Electroencephalography*
Forecasting*
Hippocampus / physiopathology*
Humans
Interneurons / physiology
Models, Neurological*
Pyramidal Cells / physiology
Seizures / physiopathology*,  psychology
Synaptic Potentials / physiology*

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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