143 Channel Whole-Cortex MEG System

Vrba, Jan; Angus, V.; Betts, K.; Burbank, M. B.; Cheung, Teresa; Fife, A. A.; Haid, G.; Kubik, P.R.; Lee, S.; Ludwig, W.; McCubbin, J. Adam; McKay, Jim; McKenzie, Doug; Robinson, Stephen E.; Smith, Marie L.; Spear, Peter D.; Taylor, Brian K.; Tillotson, M.; Cheyne, Douglas; Weinberg, H.

doi:10.1007/978-1-4612-1260-7_35

Cited by 11 publications

(18 citation statements)

References 2 publications

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“…To conclude this section, we shall show an example of dipole magnitudes which for a given noise produce SNR = 1. Assuming that the MEG sensor white noise was ν w = 5 f T rms Hz −1/2 , collection bandwidth BW = 50 Hz, number Noise spectra collected within a shielded room at an urban medical centre [46] using a 151-channel MEG system with primary sensors hardware first-order gradiometers with 5 cm baseline. The noise spectra of magnetometers, hardware primary first-order gradiometer sensors and synthetic third-order gradiometers are compared.…”

Section: Comparison Of Figures Of Meritmentioning

confidence: 99%

“…An example of typical noise magnitudes, observed within shielded rooms, is shown in figure 13 [46]. The magnetometer traces correspond to three orthogonal components and indicate that at 0.1 Hz the noise magnitude is about 1 nT rms Hz −1/2 and the intersect of the magnetometer low frequency noise with the sensor white noise level (about 5 f T rms Hz −1/2 ) is at about 10 Hz (at some sites the onset of magnetometer low frequency noise can be as high as 70 Hz).…”

Section: Sensitivity To the Environmental Noisementioning

confidence: 99%

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SQUID sensor array configurations for magnetoencephalography applications

Vrba¹,

Robinson²

2002

Supercond. Sci. Technol.

107

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Electrophysiological activity in the human brain generates a small magnetic field from the spatial superposition of individual neuronal source currents. At a distance of about 15 mm from the scalp, the observed field is of the order of 10−13 to 10−12 T peak-to-peak. This measurement process is termed magnetoencephalography (MEG). In order to minimize instrumental noise, the MEG is usually detected using superconducting flux transformers, coupled to SQUID (superconducting quantum interference device) sensors. Since MEG signals are also measured in the presence of significant environmental magnetic noise, flux transformers must be designed to strongly attenuate environmental noise, maintain low instrumental noise and maximize signals from the brain. Furthermore, the flux transformers must adequately sample spatial field variations if the brain activity is to be imaged. The flux transformer optimization for maximum brain signal-to-noise ratio (SNR) requires analysis of the spatial and temporal properties of brain activity, the environmental noise and how these signals are coupled to the flux transformer. Flux transformers that maximize SNR can detect the smallest brain signals and have the best ability to spatially separate dipolar sources. An optimal flux transformer design is a synthetic higher-order gradiometer based on relatively short-baseline first-order radial gradiometer primary sensors.

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Section: Comparison Of Figures Of Meritmentioning

confidence: 99%

Section: Sensitivity To the Environmental Noisementioning

confidence: 99%

SQUID sensor array configurations for magnetoencephalography applications

Vrba¹,

Robinson²

2002

Supercond. Sci. Technol.

107

View full text Add to dashboard Cite

show abstract

“…Brain magnetic activity was measured using the CTF 2 143 channels whole-scalp MEG equipment (Beisteiner, Vrba, & Deecke, 1998;Vrba et al, 1996), with a sample frequency of 250 Hz. The spatial distribution of the SQUID sensors all over the scalp is illustrated in Figure 7 in both two and three dimensions.…”

Section: Meg Recording and Analysismentioning

confidence: 99%

Modulation of Spatial Orientation Processing by Mental Imagery Instructions: A MEG Study of Representational Momentum

Amorim

Lang

Lindinger

et al. 2000

Journal of Cognitive Neuroscience

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Under appropriate conditions, an observer's memory for the final position of an abruptly halted moving object is distorted in the direction of the represented motion. This phenomenon is called "representational momentum" (RM). We examined the effect of mental imagery instructions on the modulation of spatial orientation processing by testing for RM under conditions of picture versus body rotation perception and imagination. Behavioral data were gathered via classical reaction time and error measurements, whereas brain activity was recorded with the help of magnetoencephalography (MEG). Due to the so-called inverse problem and to signal complexity, results were described at the signal level rather than with the source location modeling. Brain magnetic field strength and spatial distribution, as well as latency of P200m evoked fields were used as neurocognitive markers. A task was devised where a subject examined a rotating sea horizon as seen from a virtual boat in order to extrapolate either the picture motion or the body motion relative to the picture while the latter disappeared temporarily until a test-view was displayed as a final orientation candidate. Results suggest that perceptual interpretation and extrapolation of visual motion in the roll plane capitalize on the fronto-parietal cortical networks involving working memory processes. Extrapolation of the rotational dynamics of sea horizon revealed a RM effect simulating the role of gravity in rotational equilibrium. Modulation of the P200m component reflected spatial orientation processing and a non-voluntary detection of an incongruity between displayed and expected final orientations given the implied motion. Neuromagnetic properties of anticipatory (Contingent Magnetic Variation) and evoked (P200m) brain magnetic fields suggest, respectively, differential allocation of attentional resources by mental imagery instructions (picture vs. body tilt), and a communality of neural structures (in the right centro-parietal region) for the control of both RM and mental rotation processes. Finally, the RM of the body motion is less prone to forward shifts than that of picture motion evidencing an internalization of the implied mass of the virtual body of the observer.

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“…A sample frequency of 625 Hz was used and the standard preprocessing steps undertaken at our lab to reduce noise are, spatial filtering using third order gradiometers (Vrba et al, 1999), band pass filtering, and visual inspection (see criteria in Data Processing) discarding data contaminated by artifacts. Visual inspection may be preferred over automatic approaches, since, for instance, an independent component analysis may introduce complex new artifacts or biases (Gross et al, 2013).…”

Section: Methodsmentioning

confidence: 99%

Resting-State Oscillatory Activity in Children Born Small for Gestational Age: An MEG Study

Boersma¹,

Bie²,

Oostrom³

et al. 2013

Front. Hum. Neurosci.

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Growth restriction in utero during a period that is critical for normal growth of the brain, has previously been associated with deviations in cognitive abilities and brain anatomical and functional changes. We measured magnetoencephalography (MEG) in 4- to 7-year-old children to test if children born small for gestational age (SGA) show deviations in resting-state brain oscillatory activity. Children born SGA with postnatally spontaneous catch-up growth [SGA+; six boys, seven girls; mean age 6.3 year (SD = 0.9)] and children born appropriate for gestational age [AGA; seven boys, three girls; mean age 6.0 year (SD = 1.2)] participated in a resting-state MEG study. We calculated absolute and relative power spectra and used non-parametric statistics to test for group differences. SGA+ and AGA born children showed no significant differences in absolute and relative power except for reduced absolute gamma band power in SGA children. At the time of MEG investigation, SGA+ children showed significantly lower head circumference (HC) and a trend toward lower IQ, however there was no association of HC or IQ with absolute or relative power. Except for reduced absolute gamma band power, our findings suggest normal brain activity patterns at school age in a group of children born SGA in which spontaneous catch-up growth of bodily length after birth occurred. Although previous findings suggest that being born SGA alters brain oscillatory activity early in neonatal life, we show that these neonatal alterations do not persist at early school age when spontaneous postnatal catch-up growth occurs after birth.

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143 Channel Whole-Cortex MEG System

Cited by 11 publications

References 2 publications

SQUID sensor array configurations for magnetoencephalography applications

SQUID sensor array configurations for magnetoencephalography applications

Modulation of Spatial Orientation Processing by Mental Imagery Instructions: A MEG Study of Representational Momentum

Resting-State Oscillatory Activity in Children Born Small for Gestational Age: An MEG Study

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