Document Detail


Fetal MEG evoked response latency from beamformer with random field theory.
MedLine Citation:
PMID:  19686855     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Analysis of fetal magnetoencephalographic brain recordings is restricted by low signal to noise ratio (SNR) and non-stationarity of the sources. Beamformer techniques have been applied to improve SNR of fetal evoked responses. However, until now the effect of non-stationarity was not taken into account in detail, because the detection of evoked responses is in most cases determined by averaging a large number of trials. We applied a windowing technique to improve the stationarity of the data by using short time segments recorded during a flash-evoked study. In addition, we implemented a random field theory approach for more stringent control of false-positives in the statistical parametric map of the search volume for the beamformer. The search volume was based on detailed individual fetal/maternal biometrics from ultrasound scans and fetal heart localization. Average power over a sliding window within the averaged evoked response against a randomized average background power was used as the test z-statistic. The significance threshold was set at 10% over all members of a contiguous cluster of voxels. There was at least one significant response for 62% of fetal and 95% of newborn recordings with gestational age (GA) between 28 and 45 weeks from 29 subjects. We found that the latency was either substantially unchanged or decreased with increasing GA for most subjects, with a nominal rate of about -11 ms/week. These findings support the anticipated neurophysiological development, provide validation for the beamformer model search as a methodology, and may lead to a clinical test for fetal cognitive development.
Authors:
J McCubbin; J Vrba; P Murphy; J Temple; H Eswaran; C L Lowery; H Preissl
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural     Date:  2009-08-15
Journal Detail:
Title:  NeuroImage     Volume:  49     ISSN:  1095-9572     ISO Abbreviation:  Neuroimage     Publication Date:  2010 Jan 
Date Detail:
Created Date:  2009-10-20     Completed Date:  2010-01-04     Revised Date:  2013-05-31    
Medline Journal Info:
Nlm Unique ID:  9215515     Medline TA:  Neuroimage     Country:  United States    
Other Details:
Languages:  eng     Pagination:  282-92     Citation Subset:  IM    
Affiliation:
Department of Obstetrics and Gynecology, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA. mccubbin@telus.net
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MeSH Terms
Descriptor/Qualifier:
Adult
Algorithms
Computer Simulation
Female
Fetus / anatomy & histology*
Gestational Age
Heart / anatomy & histology
Humans
Image Processing, Computer-Assisted / methods
Infant, Newborn
Magnetoencephalography / methods*
Models, Statistical
Monte Carlo Method
Normal Distribution
Pregnancy
Grant Support
ID/Acronym/Agency:
R01 NS 036277/NS/NINDS NIH HHS; R01 NS036277-10/NS/NINDS NIH HHS
Comments/Corrections

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