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rdf:type |
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lifeskim:mentions |
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pubmed:issue |
4
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pubmed:dateCreated |
2005-8-22
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pubmed:abstractText |
Wavelet-crosscorrelation analysis is a new application of wavelet analysis used to show the propagation of epileptiform discharges and to localize the corresponding lesions. We have shown previously that this analysis can help predict brain conditions statistically (Mizuno-Matsumoto et al. 2002). Our objective was to assess whether wavelet-crosscorrelation analysis reveals the initiation and propagation of epileptiform activity in human patients.
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pubmed:language |
eng
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pubmed:journal |
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pubmed:citationSubset |
IM
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pubmed:status |
MEDLINE
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pubmed:issn |
0896-0267
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pubmed:author |
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|
pubmed:issnType |
Print
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pubmed:volume |
17
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pubmed:owner |
NLM
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pubmed:authorsComplete |
Y
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pubmed:pagination |
237-52
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pubmed:dateRevised |
2007-11-15
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pubmed:meshHeading |
pubmed-meshheading:16110773-Adult,
pubmed-meshheading:16110773-Algorithms,
pubmed-meshheading:16110773-Brain Mapping,
pubmed-meshheading:16110773-Cerebral Cortex,
pubmed-meshheading:16110773-Epilepsy,
pubmed-meshheading:16110773-Evoked Potentials,
pubmed-meshheading:16110773-Female,
pubmed-meshheading:16110773-Humans,
pubmed-meshheading:16110773-Magnetoencephalography,
pubmed-meshheading:16110773-Male,
pubmed-meshheading:16110773-Predictive Value of Tests,
pubmed-meshheading:16110773-Reproducibility of Results,
pubmed-meshheading:16110773-Signal Processing, Computer-Assisted,
pubmed-meshheading:16110773-Statistics as Topic,
pubmed-meshheading:16110773-User-Computer Interface
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pubmed:year |
2005
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pubmed:articleTitle |
Wavelet-crosscorrelation analysis: Non-stationary analysis of neurophysiological signals.
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pubmed:affiliation |
Graduate School of Applied Informatics, University of Hyogo, Kobe, Japan. yuko@ai.u-hyogo.ac.jp
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pubmed:publicationType |
Journal Article,
Research Support, Non-U.S. Gov't
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