Document Detail


Time-frequency characterization of electrocorticographic recordings of epileptic patients using frequency-entropy similarity: a comparison to other bi-variate measures.
MedLine Citation:
PMID:  20969891     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Expert evaluation of electrocorticographic (ECoG) recordings forms the linchpin of seizure onset zone localization in the evaluation of epileptic patients for surgical resection. Numerous methods have been developed to analyze these complex recordings, including uni-variate (characterizing single channels), bi-variate (comparing channel pairs) and multivariate measures. Developing reliable algorithms may be helpful in clinical tasks such as localization of epileptogenic zones and seizure anticipation, as well as enabling better understanding of neuronal function and dynamics. Recently we have developed the frequency-entropy (F-E) similarity measure, and have tested its capability in mapping the epileptogenic zones. The F-E similarity measure compares time-frequency characterizations of two recordings. In this study, we examine the method's principles and utility and compare it to previously described bi-variate correspondence measures such as correlation, coherence, mean phase coherence and spectral comparison methods. Specially designed synthetic signals were used for illuminating theoretical differences between the measures. Intracranial recordings of four epileptic patients were then used for the measures' comparative analysis by creating a mean inter-electrode matrix for each of the correspondence measures and comparing the structure of these matrices during the inter-ictal and ictal periods. We found that the F-E similarity measure is able to discover spectral and temporal features in data which are hidden for the other measures and are important for foci localization.
Authors:
T Gazit; I Doron; O Sagher; M H Kohrman; V L Towle; M Teicher; E Ben-Jacob
Publication Detail:
Type:  Comparative Study; Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't     Date:  2010-10-20
Journal Detail:
Title:  Journal of neuroscience methods     Volume:  194     ISSN:  1872-678X     ISO Abbreviation:  J. Neurosci. Methods     Publication Date:  2011 Jan 
Date Detail:
Created Date:  2010-12-27     Completed Date:  2011-04-22     Revised Date:  2012-01-17    
Medline Journal Info:
Nlm Unique ID:  7905558     Medline TA:  J Neurosci Methods     Country:  Netherlands    
Other Details:
Languages:  eng     Pagination:  358-73     Citation Subset:  IM    
Copyright Information:
Copyright © 2010 Elsevier B.V. All rights reserved.
Affiliation:
The Leslie and Suzan Gonda (Goldschmied) Multidisciplinary Brain Research Center, Bar Ilan University, Ramat Gan 52900, Israel.
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MeSH Terms
Descriptor/Qualifier:
Adolescent
Algorithms
Brain / physiopathology*
Brain Mapping*
Child
Electroencephalography / methods
Entropy*
Epilepsy / pathology*,  physiopathology*
Female
Humans
Male
Models, Neurological
Nonlinear Dynamics
Signal Processing, Computer-Assisted
Time Factors
Young Adult
Grant Support
ID/Acronym/Agency:
5 R01 NS40514/NS/NINDS NIH HHS; R01 NS040514-01A1/NS/NINDS NIH HHS

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


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