Magnetoencephalography in healthy neonates

Haddad, Naim; Shihabuddin, Bashir; Preißl, Hubert; Holst, Manuela; Lowery, Curtis L.; Eswaran, Hari

doi:10.1016/j.clinph.2005.10.013

Cited by 16 publications

(17 citation statements)

References 13 publications

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“…Recently, the MEG patterns of healthy neonates were studied, and the classical neonatal EEG patterns, namely, TA, continuous polyfrequency, and continuous slow activity were also observed in the neonatal MEG [3]. The occurrence of discontinuous and continuous brain patterns, similar to EEG studies of preterm neonates at comparable post-CA, was also observed in fetal MEG recordings [4].…”

Section: Introductionmentioning

confidence: 98%

“…Based on the MEG technology, a first-of-a-kind device named SQUID Array for Reproductive Assessment (SARA) was designed and installed at the University of Arkansas for Medical Sciences specifically to study the maternal–fetal electrophysiology. Information about SARA and the recording procedure to acquire neonatal and fetal brain signals can be found in [3] and [4]. …”

Section: Introductionmentioning

confidence: 99%

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Detection of Discontinuous Patterns in Spontaneous Brain Activity of Neonates and Fetuses

Eswaran

Haddad

Rose

et al. 2009

IEEE Trans. Biomed. Eng.

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The discontinuous patterns in neonatal magnetoencephalographic (MEG) data are quantified with a novel Hilbert phase (HP) based approach. The expert neurologists' scores were used as the gold standard. The performance of this approach was analyzed using a receiver operating characteristic (ROC) curve, and it was compared with two other approaches, namely spectral ratio (SR) and discrete wavelet transform (DWT) that have been proposed for the detection of discontinuous patterns in neonatal EEG. The area under the ROC curve (AUC) was used as a performance measure. AUCs obtained for SR, HP, and DWT were 0.87, 0.80, and 0.56, respectively. Although the performance of HP was lower than SR, it carries information about the frequency content of the signal that helps to distinguish brain patterns from artifacts such as cardiac residuals. Based on this property, the HP approach was extended to fetal MEG data. Further, using the frequency property of the HP approach,

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Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Detection of Discontinuous Patterns in Spontaneous Brain Activity of Neonates and Fetuses

Eswaran

Haddad

Rose

et al. 2009

IEEE Trans. Biomed. Eng.

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“…Infant language development has also been studied with ERPs (Buiatti et al, 2009; Cohen et al, 2000; Dehaene-Lambertz et al, 2006). MEG has become a new modality of studying infant brain activity in infant speech perception (Imada et al, 2006; Kujala et al, 2004), sensory perception during sleep (Kakigi et al, 2003), somatosensory development (Pihko et al, 2009), vision (Haddad et al, 2006), and auditory response as an immature brain marker (Wakai et al, 2007). MEG instruments optimized for the pediatric population are beginning to be developed (e.g.…”

Section: Introductionmentioning

confidence: 99%

Effects of sutures and fontanels on MEG and EEG source analysis in a realistic infant head model

et al. 2013

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In infants, the fontanels and sutures as well as conductivity of the skull influence the volume currents accompanying primary currents generated by active neurons and thus the associated electroencephalography (EEG) and magnetoencephalography (MEG) signals. We used a finite element method (FEM) to construct a realistic model of the head of an infant based on MRI images. Using this model, we investigated the effects of the fontanels, sutures and skull conductivity on forward and inverse EEG and MEG source analysis. Simulation results show that MEG is better suited than EEG to study early brain development because it is much less sensitive than EEG to distortions of the volume current caused by the fontanels and sutures and to inaccurate estimates of skull conductivity. Best results will be achieved when MEG and EEG are used in combination.

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“…Magnetoencephalography (MEG) is being investigated to fill this gap (Haddad et al, 2006). In a recent paper, we demonstrated reproducible features in spontaneous fetal brain activity as recorded by MEG.…”

Section: Introductionmentioning

confidence: 99%

Correlation between fetal brain activity patterns and behavioral states: An exploratory fetal magnetoencephalography study

Haddad

Govindan

Vairavan

et al. 2011

Experimental Neurology

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The fetal brain remains inaccessible to neurophysiological studies. Magnetoencephalography (MEG) is being assessed to fill this gap. We performed 40 fetal MEG (fMEG) recordings with gestational ages (GA) ranging from 30 to 37 weeks. The data from each recording were divided into 15 second epochs which in turn were classified as continuous (CO), discontinuous (DC), or artifact. The fetal behavioral state, quiet or active sleep, was determined using previously defined criteria based on fetal movements and heart rate variability. We studied the correlation between the fetal state, the GA and the percentage of CO and DC epochs. We also analyzed the Spectral Edge Frequency (SEF) and studied its relation with state and GA. We found that the odds of a DC epoch decreased by 6% per week as the GA increased (P=0.0036). This decrease was mainly generated by changes during quiet sleep, which showed 52% DC epochs before 35 weeks GA versus 38% after 35 weeks (P=0.0006). Active sleep did not show a significant change in DC epochs with GA. When both states were compared for MEG patterns within each GA group (before and after 35 weeks), the early group was found to have more DC epochs in quiet sleep (54%) compared to active sleep (42%) (P=0.036). No significant difference in DC epochs between the two states was noted in the late GA group. Analysis of SEF showed a significant difference (P=0.0014) before and after 35 weeks GA, with higher SEF noted at late GA. However, when both quiet and active sleep states were compared within each GA group, the SEF did not show a significant difference. We conclude that fMEG shows reproducible variations in gross features and frequency content, depending on GA and behavioral state. Fetal MEG is a promising tool to investigate fetal brain physiology and maturation.

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Magnetoencephalography in healthy neonates

Cited by 16 publications

References 13 publications

Detection of Discontinuous Patterns in Spontaneous Brain Activity of Neonates and Fetuses

Detection of Discontinuous Patterns in Spontaneous Brain Activity of Neonates and Fetuses

Effects of sutures and fontanels on MEG and EEG source analysis in a realistic infant head model

Correlation between fetal brain activity patterns and behavioral states: An exploratory fetal magnetoencephalography study

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