Comparison of the Properties of EEG and MEG in Detecting the Electric Activity of the Brain

Malmivuo, Jaakko

doi:10.1007/s10548-011-0202-1

Cited by 93 publications

(36 citation statements)

References 31 publications

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“…The MRCP generated by cued unimanual and bimanual movements is different from the self-initiated MRCP described above, as reported in a number of studies Jankelowitz and Colebatch, 2002;Smith and Staines, 2006, 2010, 2012. Cued MRCP shows the same temporal pattern as spontaneous MRCP with a slow negativity of a couple of seconds before movement onset, a sharp negativity close to movement and positive deflection after movement.…”

Section: Event-related Potentialsmentioning

confidence: 55%

“…A variety of methods have been proposed (for reviews, see Hillebrand and Barnes, 2005 It is difficult to localize activity of deep brain structures by EEG/MEG given that the electrical signal is attenuated when being transmitted through the tissues, and that the magnetic field is reduced by the inverse of the squared distance. Computational and clinical studies state that EEG is more sensitive to deep brain structures than MEG (Ahlfors et al, 2010;Malmivuo, 2012;Wendel et al, 2009). However, there are MEG reports claiming activity to be originating in subcortical structures (Attal et al, 2012;Gross et al, 2002;Martin et al, 2006).…”

Section: Source Estimationmentioning

confidence: 99%

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Understanding bimanual coordination across small time scales from an electrophysiological perspective

Rueda‐Delgado

Solesio-Jofre

Serrien

et al. 2014

Neuroscience & Biobehavioral Reviews

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Bimanual movement involves a variety of coordinated functions, ranging from elementary patterns that are performed automatically to complex patterns that require practice to be performed skillfully. The neural dynamics accompanying these coordination patterns are complex and rapid. By means of electro- and magneto-encephalographic approaches, it has been possible to examine these dynamics during bimanual coordination with excellent temporal resolution, which complements other neuroimaging modalities with superb spatial resolution. This review focuses on EEG/MEG studies that unravel the processes involved in movement planning and execution, motor learning, and executive functions involved in task switching and dual tasking. Evidence is presented for a spatio-temporal reorganization of the neural networks within and between hemispheres to meet increased task difficulty demands, induced or spontaneous switches in coordination mode, or training-induced neuroplastic modulation in coordination dynamics. Future theoretical developments will benefit from the integration of research techniques unraveling neural activity at different time scales. Ultimately this work will contribute to a better understanding of how the human brain orchestrates complex behavior via the implementation of inter- and intra-hemispheric coordination networks.

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Section: Event-related Potentialsmentioning

confidence: 55%

Section: Source Estimationmentioning

confidence: 99%

Understanding bimanual coordination across small time scales from an electrophysiological perspective

Rueda‐Delgado

Solesio-Jofre

Serrien

et al. 2014

Neuroscience & Biobehavioral Reviews

View full text Add to dashboard Cite

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“…Several recent studies compared the two experimental techniques in terms of their spatial resolution and the amount of information they offer about the underlying brain activity. EEG and MEG were found similar in these respects [1]–[4] despite the fact that MEG is likely to be less affected by the skull's low conductivity than EEG [5], but also see [6]). …”

Section: Introductionmentioning

confidence: 83%

“…Therefore, it is not surprising that recording both EEG and MEG signals can provide additional information on the brain's activity by increasing the effective number of independent signals recorded [4], [8]. Simply increasing the number of EEG and MEG sensors might not have the same effect due to a significant cross-talk between sensors.…”

Section: Introductionmentioning

confidence: 99%

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Electric Field Encephalography as a Tool for Functional Brain Research: A Modeling Study

Petrov

Sridhar

2013

PLoS ONE

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We introduce the notion of Electric Field Encephalography (EFEG) based on measuring electric fields of the brain and demonstrate, using computer modeling, that given the appropriate electric field sensors this technique may have significant advantages over the current EEG technique. Unlike EEG, EFEG can be used to measure brain activity in a contactless and reference-free manner at significant distances from the head surface. Principal component analysis using simulated cortical sources demonstrated that electric field sensors positioned 3 cm away from the scalp and characterized by the same signal-to-noise ratio as EEG sensors provided the same number of uncorrelated signals as scalp EEG. When positioned on the scalp, EFEG sensors provided 2–3 times more uncorrelated signals. This significant increase in the number of uncorrelated signals can be used for more accurate assessment of brain states for non-invasive brain-computer interfaces and neurofeedback applications. It also may lead to major improvements in source localization precision. Source localization simulations for the spherical and Boundary Element Method (BEM) head models demonstrated that the localization errors are reduced two-fold when using electric fields instead of electric potentials. We have identified several techniques that could be adapted for the measurement of the electric field vector required for EFEG and anticipate that this study will stimulate new experimental approaches to utilize this new tool for functional brain research.

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Biomagnetism

Malmivuo

2017

Wiley Encyclopedia of Electrical and Electronics Engineering

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Biomagnetic fields are generated by the same phenomenon as the bioelectric fields. They are induced by the electric currents generated by the activating tissues. These are primarily nerve and muscle tissues. The theoretical difference between these fields is based on the distribution of the elements of the volume sources generating these fields. Bioelectric and biomagnetic fields are generated by the flux and vortex source distributions, respectively. Although the flux and vortex source distributions are independent, the fields they generate are only partially independent. This means that with the biomagnetic measurement it is possible to obtain only partially new independent information on the source in addition to the bioelectric measurement. This is the fundamental issue in the application of biomagnetic methods and this will be discussed in detail in this article. In addition to the theoretical difference, bioelectric and biomagnetic methods have technical differences due to the different technologies that they use. This issue is also discussed in this article.

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Comparison of the Properties of EEG and MEG in Detecting the Electric Activity of the Brain

Cited by 93 publications

References 31 publications

Understanding bimanual coordination across small time scales from an electrophysiological perspective

Understanding bimanual coordination across small time scales from an electrophysiological perspective

Electric Field Encephalography as a Tool for Functional Brain Research: A Modeling Study

Biomagnetism

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