The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Electromagnetic brain mapping
Abstract
There has been tremendous advances in our ability to produce images of human brain function. Applications of functional brain imaging extend from improving our understanding of the basic mechanisms of cognitive processes to better characterization of pathologies that impair normal function. Magnetoencephalography (MEG) and electroencephalography (EEG) (MEG/EEG) localize neural electrical activity using noninvasive measurements of external electromagnetic signals. Among the available functional imaging techniques, MEG and EEG uniquely have temporal resolutions below 100 ms. This temporal precision allows us to explore the timing of basic neural processes at the level of cell assemblies. MEG/EEG source localization draws on a wide range of signal processing techniques including digital filtering, three-dimensional image analysis, array signal processing, image modeling and reconstruction, and, blind source separation and phase synchrony estimation. We describe the underlying models currently used in MEG/EEG source estimation and describe the various signal processing steps required to compute these sources. In particular we describe methods for computing the forward fields for known source distributions and parametric and imaging-based approaches to the inverse problem.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Van Veen, B. D., Van Drongelen, W., Yuchtman, M., & Suzuki, A. (1997) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.623056 · Cited by 2,561
Cohen, D. (1972) · Science · doi:10.1126/science.175.4022.664 · Cited by 785
Source localization using recursively applied and projected (RAP) MUSIC
Mosher, J. C., & Leahy, R. M. (1999) · IEEE Transactions on Signal Processing · doi:10.1109/78.740118 · Cited by 398
Self-citationNunez, P. L., & Silberstein, R. B. (2000) · Brain Topography · doi:10.1023/a:1026683200895 · Cited by 307
Cited by
Brain Computer Interfaces, a Review
Nicolas-Alonso, L. F., & Gomez-Gil, J. (2012) · Sensors · doi:10.3390/s120201211 · Cited by 2,143
Identifying true brain interaction from EEG data using the imaginary part of coherency
Nolte, G., Bai, O., Wheaton, L., Mari, Z., Vorbach, S., & Hallett, M. (2004) · Clinical Neurophysiology · doi:10.1016/j.clinph.2004.04.029 · Cited by 1,756
Review on solving the inverse problem in EEG source analysis
Grech, R., Cassar, T., Muscat, J., Camilleri, K. P., Fabri, S. G., Zervakis, M., Xanthopoulos, P., Sakkalis, V., & Vanrumste, B. (2008) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/1743-0003-5-25 · Cited by 1,193
Topographic ERP Analyses: A Step-by-Step Tutorial Review
Murray, M. M., Brunet, D., & Michel, C. M. (2008) · Brain Topography · doi:10.1007/s10548-008-0054-5 · Cited by 1,127
Magnetoencephalography for Brain Electrophysiology and Imaging
Baillet, S. (2017) · Nature Neuroscience · doi:10.1038/nn.4504 · Cited by 992
Self-citation
Metadata
- Authors
- Baillet, S., Mosher, J. C., & Leahy, R. M.
- Venue
- IEEE Signal Processing Magazine
- Published
- 2001
- Volume
- 18
- Issue
- 6
- Pages
- 14-30
- ISSN
- 1053-5888 (ISSN-L)
- OpenAlex
- W2016980059
- Cited by
- 1,692
- References
- 4
- FWCI
- 11.03
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Electromagnetic brain mapping. https://app.cochat.ai/papers/10.1109/79.962275
- The paper
- Baillet, S., Mosher, J. C., & Leahy, R. M. (2001). Electromagnetic brain mapping. IEEE Signal Processing Magazine. https://doi.org/10.1109/79.962275
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.