Paving the way for cross-site pooling of magnetoencephalography (MEG) data

Weisend, Michael P.; Hanlon, Faith M.; Montaño, R.; Ahlfors, Seppo P.; Leuthold, Arthur C.; Pantazis, Dimitrios; Georgopoulos, Apostolos P.; Hämäläinen, Matti S.; Aine, Cheryl J.

doi:10.1016/j.ics.2006.12.095

Cited by 14 publications

(12 citation statements)

References 3 publications

(1 reference statement)

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“…The replication across MEG systems is consistent with our preliminary study by Weisend et al (2007) showing essentially identical results within participants across three commercially available MEG systems. Since the current study recruited a different group of NE individuals from the previous normal aging study (three individuals were tested using both MEG systems), this provides additional evidence supporting a gender difference in SI timecourses, suggesting that gender should be accounted for when evaluating sensory responses in the elderly.…”

Section: Discussionsupporting

confidence: 88%

Somatosensory responses in normal aging, mild cognitive impairment, and Alzheimer’s disease

et al. 2009

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As a part of a larger study of normal aging and Alzheimer's disease (AD), which included patients with mild cognitive impairment (MCI), we investigated the response to median nerve stimulation in primary and secondary somatosensory areas. We hypothesized that the somatosensory response would be relatively spared given the reported late involvement of sensory areas in the progression © Springer-Verlag 2009 Correspondence to: Julia M. Stephen, jstephen@mrn.org. of AD. We applied brief pulses of electric current to left and right median nerves to test the somatosensory response in normal elderly (NE), MCI, and AD. MEG responses were measured and were analyzed with a semi-automated source localization algorithm to characterize source locations and timecourses. We found an overall difference in the amplitude of the response of the primary somatosensory source (SI) based on diagnosis. Across the first three peaks of the SI response, the MCI patients exhibited a larger amplitude response than the NE and AD groups (P < 0.03). Additional relationships between neuropsychological measures and SI amplitude were also determined. There was no significant difference in amplitude for the contralateral secondary somatosensory source across diagnostic category. These results suggest that somatosensory cortex is affected early in the progression of AD and may have some consequence on behavioral and functional measures. NIH Public Access

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Section: Discussionsupporting

confidence: 88%

Somatosensory responses in normal aging, mild cognitive impairment, and Alzheimer’s disease

et al. 2009

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“…The rich temporal information in MEG data enables us to extend the comparison to the single-trial level. Compared with the results of the prior work based on the averages of hundreds of trials [5,13], our results reveal stronger consistency between the systems, and within each subject. We employ two approaches in characterizing the source of variability: the variance component analysis (VCA), which assumes a Gaussian model, and the nonparametric Kullback-Leibler (KL) divergence analysis to directly measure the differences between two sets of data.…”

Section: Introductionsupporting

confidence: 43%

“…On the other hand, the source estimates relate more directly to the neuronal phenomenon of interest. Weisend et al [13] reported consistent source localization when using data from the same subject on different MEG systems. These two approaches were tailored to study inter-system variability only.…”

Section: Introductionmentioning

confidence: 92%

Sources of Variability in MEG

Ou¹,

Golland²,

Hämäläinen

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007

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Abstract. This paper investigates and characterizes sources of variability in MEG signals in multi-site, multi-subject studies. Understanding these sources will help to develop efficient strategies for comparing and pooling data across repetitions of an experiment, across subjects, and across sites. In this work, we investigated somatosensory MEG data collected at three different sites and applied variance component analysis and nonparametric KL divergence analysis in order to characterize the sources of variability. Our analysis showed that inter-subject differences are the biggest factor in the signal variability. We demonstrated that the timing of the deflections is very consistent in the early somatosensory response, which justifies a direct comparison of deflection peak times acquired from different visits, subjects, and systems. Compared with deflection peak times, deflection magnitudes have larger variation across sites; modeling of this variability is necessary for data pooling.

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“…Data of five subjects of the MIND multi-site MEG study [27,20] using two different auditory recordings for each subject were used to evaluate the four reduction methods. In the auditory task of this study, three pure tones of different frequencies (500 Hz, 2000 Hz, and 4000 Hz) were presented to obtain a tonotopic map.…”

Section: Methodsmentioning

confidence: 99%

Real-Time MEG Source Localization Using Regional Clustering

et al. 2015

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With its millisecond temporal resolution, Magnetoencephalography (MEG) is well suited for real-time monitoring of brain activity. Real-time feedback allows the adaption of the experiment to the subject’s reaction and increases time efficiency by shortening acquisition and offline analysis. Two formidable challenges exist in real-time analysis: the low signal-to-noise ratio (SNR) and the limited time available for computations. Since the low SNR reduces the number of distinguishable sources, we propose an approach which downsizes the source space based on a cortical atlas and allows to discern the sources in the presence of noise. Each cortical region is represented by a small set of dipoles, which is obtained by a clustering algorithm. Using this approach, we adapted dynamic statistical parametric mapping (dSPM) for real-time source localization. In terms of point spread and crosstalk between regions the proposed clustering technique performs better than selecting spatially evenly distributed dipoles. We conducted real-time source localization on MEG data from an auditory experiment. The results demonstrate that the proposed real-time method localizes sources reliably in the superior temporal gyrus. We conclude that real-time source estimation based on MEG is a feasible, useful addition to the standard on-line processing methods, and enables feedback based on neural activity during the measurements.

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Paving the way for cross-site pooling of magnetoencephalography (MEG) data

Cited by 14 publications

References 3 publications

Somatosensory responses in normal aging, mild cognitive impairment, and Alzheimer’s disease

Somatosensory responses in normal aging, mild cognitive impairment, and Alzheimer’s disease

Sources of Variability in MEG

Real-Time MEG Source Localization Using Regional Clustering

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