The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
MEG versus EEG localization test using implanted sources in the human brain
Abstract
It is believed that the magnetoencephalogram (MEG) localizes an electrical source in the brain to within several millimeters and is therefore more accurate than electroencephalogram (EEG) localization, reported as 20 mm. To test this belief, the localization accuracy of the MEG and EEG were directly compared. The signal source was a dipole at a known location in the brain; this was made by passing a weak current pulse simulating a neural signal through depth electrodes already implanted in patients for seizure monitoring. First, MEGs and EEGs from this dipole were measured at 16 places on the head. Then, computations were performed on the MEG and EEG data separately to determine the apparent MEG and EEG source locations. Finally, these were compared with the actual source location to determine the MEG and EEG localization errors. Measurements were made of four dipoles in each of three patients. After MEGs with weak signals were discounted, the MEG average error of localization was found to be 8 mm, which was worse than expected. The average EEG error was 10 mm, which was better than expected. These results suggest that the MEG offers no significant advantage over the EEG in localizing a focal source. However, this does not diminish other uses of the MEG.
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Citations
Cites
Electric Dipole Tracing in the Brain by Means of the Boundary Element Method and Its Accuracy
He, B., Musha, T., Okamoto, Y., Homma, S., Nakajima, Y., & Sato, T. (1987) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.1987.326056 · Cited by 334
Cited by
Hämäläinen, M., Hari, R., Ilmoniemi, R. J., Knuutila, J., & Lounasmaa, O. V. (1993) · Reviews of Modern Physics · doi:10.1103/revmodphys.65.413 · Cited by 4,684
EEG and MEG: Relevance to Neuroscience
Lopes da Silva, F. (2013) · Neuron · doi:10.1016/j.neuron.2013.10.017 · Cited by 900
Nunez, P. L., & Silberstein, R. B. (2000) · Brain Topography · doi:10.1023/a:1026683200895 · Cited by 307
Virtual Reality for Anxiety Reduction Demonstrated by Quantitative EEG: A Pilot Study
Tarrant, J., Viczko, J., & Cope, H. (2018) · Frontiers in Psychology · doi:10.3389/fpsyg.2018.01280 · Cited by 198
Noninvasive cortical imaging of epileptiform activities from interictal spikes in pediatric patients
Lai, Y., Zhang, X., van Drongelen, W., Korhman, M., Hecox, K., Ni, Y., & He, B. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.07.026 · Cited by 22
Metadata
- Authors
- Cohen, D., Cuffin, B. N., Yunokuchi, K., Maniewski, R., Purcell, C., Cosgrove, G. R., Ives, J., Kennedy, J. G., & Schomer, D. L.
- Venue
- Annals of Neurology
- Publisher
- Wiley
- Published
- 1990-12
- Volume
- 28
- Issue
- 6
- Pages
- 811-817
- ISSN
- 0364-5134 (ISSN-L)
- 1531-8249
- OpenAlex
- W2125202715
- Cited by
- 294
- References
- 1
- FWCI
- 8.00
- Type
- journal article
- Language
- en
- Open access
- closed
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.