title: Fetal MEG evoked response latency from beamformer with random field theory.
abstract: 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.affiliation: Department of Obstetrics and Gynecology, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA. mccubbin@telus.net
authors.forename: J
authors.initials: J
authors.lastname: McCubbin
authors.forename: J
authors.initials: J
authors.lastname: Vrba
authors.forename: P
authors.initials: P
authors.lastname: Murphy
authors.forename: J
authors.initials: J
authors.lastname: Temple
authors.forename: H
authors.initials: H
authors.lastname: Eswaran
authors.forename: C L
authors.initials: CL
authors.lastname: Lowery
authors.forename: H
authors.initials: H
authors.lastname: Preissl
mesh_terms: D000328:Adult; D000465:Algorithms; D003198:Computer Simulation; D005260:Female; D005333:Fetus / Q000033:anatomy & histology*; D005865:Gestational Age; D006321:Heart / Q000033:anatomy & histology; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D007231:Infant, Newborn; D015225:Magnetoencephalography / Q000379:methods*; D015233:Models, Statistical; D009010:Monte Carlo Method; D016011:Normal Distribution; D011247:Pregnancy
references.citation: Exp Neurol. 2004 Nov;190 Suppl 1:S22-7
references.pmid: 15498538
references.citation: IEEE Trans Biomed Eng. 1997 Sep;44(9):867-80
references.pmid: 9282479
references.citation: Semin Fetal Neonatal Med. 2006 Dec;11(6):430-6
references.pmid: 17067862
references.citation: Neuroimage. 1996 Dec;4(3 Pt 1):223-35
references.pmid: 9345513
references.citation: Hum Brain Mapp. 2003 Jan;18(1):1-12
references.pmid: 12454907
references.citation: Stat Med. 2005 Aug 15;24(15):2267-80
references.pmid: 15977294
references.citation: Neuroimage. 2008 Feb 15;39(4):1788-802
references.pmid: 18155612
references.citation: Lancet. 2002 Sep 7;360(9335):779-80
references.pmid: 12241838
references.citation: Hum Brain Mapp. 1996;4(1):58-73
references.pmid: 20408186
references.citation: Neuroimage. 2004 Jul;22(3):1203-13
references.pmid: 15219592
references.citation: Electroencephalogr Clin Neurophysiol. 1995 Jul;96(4):291-9
references.pmid: 7635074
references.citation: Science. 2007 Feb 16;315(5814):972-6
references.pmid: 17218491
references.citation: Brain Res. 2006 Jul 26;1101(1):51-8
references.pmid: 16784726
references.citation: IEEE Trans Biomed Eng. 2004 Oct;51(10):1726-34
references.pmid: 15490820
references.citation: Hum Brain Mapp. 1999;8(2-3):98-101
references.pmid: 10524599
references.citation: Neuroimage. 2004 May;22(1):268-76
references.pmid: 15110017
references.citation: Clin Neurophysiol. 2001 May;112(5):785-92
references.pmid: 11336893
references.citation: Exp Neurol. 2004 Nov;190 Suppl 1:S59-64
references.pmid: 15498543
references.citation: Biometrics. 2008 Dec;64(4):1215-22
references.pmid: 18261164
references.citation: Phys Med Biol. 2007 Oct 7;52(19):5803-13
references.pmid: 17881801
references.citation: Hum Brain Mapp. 2009 Aug;30(8):2477-86
references.pmid: 19184994
references.citation: Physiol Meas. 2009 Jan;30(1):N1-10
references.pmid: 19104135
references.citation: Neuroimage. 2009 Jan 1;44(1):71-82
references.pmid: 18547821
references.citation: Clin Neurophysiol. 2008 Apr;119(4):796-804
references.pmid: 18226946
references.citation: Doc Ophthalmol. 1999;99(1):21-39
references.pmid: 10947007
references.citation: Am J Obstet Gynecol. 2008 Nov;199(5):503.e1-7
references.pmid: 18533116
references.citation: Phys Med Biol. 2007 Feb 7;52(3):757-76
references.pmid: 17228119
references.citation: IEEE Trans Biomed Eng. 2006 Aug;53(8):1720-4
references.pmid: 16916111
references.citation: Neuroimage. 2008 Nov 15;43(3):521-7
references.pmid: 18760370
references.citation: Neuroimage. 2009 Jan 1;44(1):62-70
references.pmid: 18603449
references.citation: Early Hum Dev. 2007 Mar;83(3):199-207
references.pmid: 16863685