The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
EEG and MEG Data Analysis in SPM8
Open accessAbstract
SPM is a free and open source software written in MATLAB (The MathWorks, Inc.). In addition to standard M/EEG preprocessing, we presently offer three main analysis tools: (i) statistical analysis of scalp-maps, time-frequency images, and volumetric 3D source reconstruction images based on the general linear model, with correction for multiple comparisons using random field theory; (ii) Bayesian M/EEG source reconstruction, including support for group studies, simultaneous EEG and MEG, and fMRI priors; (iii) dynamic causal modelling (DCM), an approach combining neural modelling with data analysis for which there are several variants dealing with evoked responses, steady state responses (power spectra and cross-spectra), induced responses, and phase coupling. SPM8 is integrated with the FieldTrip toolbox , making it possible for users to combine a variety of standard analysis methods with new schemes implemented in SPM and build custom analysis tools using powerful graphical user interface (GUI) and batching tools.
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
Statistical parametric maps in functional imaging: A general linear approach
Friston, K. J., Holmes, A. P., Worsley, K. J., Poline, J. ‐., Frith, C. D., & Frackowiak, R. S. J. (1994) · Human Brain Mapping · doi:10.1002/hbm.460020402 · Cited by 9,688
Self-citationVoxel-Based Morphometry—The Methods
Ashburner, J., & Friston, K. J. (2000) · NeuroImage · doi:10.1006/nimg.2000.0582 · Cited by 8,676
Self-citationVan 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
Realistic conductivity geometry model of the human head for interpretation of neuromagnetic data
Hamalainen, M. S., & Sarvas, J. (1989) · IEEE Transactions on Biomedical Engineering · doi:10.1109/10.16463 · Cited by 989
Comparing dynamic causal models.
Penny, W. D., Stephan, K. E., Mechelli, A., & Friston, K. J. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.03.026 · Cited by 848
Self-citationA multiple source approach to the correction of eye artifacts
Berg, P., & Scherg, M. (1994) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/0013-4694(94)90094-9 · Cited by 696
Comparing families of dynamic causal models
Penny, W. D., Stephan, K. E., Daunizeau, J., Rosa, M. J., Friston, K. J., Schofield, T. M., & Leff, A. P. (2010) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000709 · Cited by 688
Self-citationDynamic causal modeling of evoked responses in EEG and MEG
David, O., Kiebel, S. J., Harrison, L. M., Mattout, J., Kilner, J. M., & Friston, K. J. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2005.10.045 · Cited by 620
Self-citationMultiple sparse priors for the M/EEG inverse problem.
Friston, K., Harrison, L., Daunizeau, J., Kiebel, S., Phillips, C., Trujillo-Barreto, N., Henson, R., Flandin, G., & Mattout, J. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2007.09.048 · Cited by 589
Self-citationThe functional anatomy of the MMN: a DCM study of the roving paradigm
Garrido, M. I., Friston, K. J., Kiebel, S. J., Stephan, K. E., Baldeweg, T., & Kilner, J. M. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.05.018 · Cited by 458
Self-citation
Cited by
Rogasch, N. C., Sullivan, C., Thomson, R. H., Rose, N. S., Bailey, N. W., Fitzgerald, P. B., Farzan, F., & Hernandez-Pavon, J. C. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2016.10.031 · Cited by 411
The Virtual Brain Integrates Computational Modeling and Multimodal Neuroimaging
Ritter, P., Schirner, M., McIntosh, A. R., & Jirsa, V. K. (2013) · Brain Connectivity · doi:10.1089/brain.2012.0120 · Cited by 268
Neural masses and fields in dynamic causal modeling
Moran, R., Pinotsis, D. A., & Friston, K. (2013) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2013.00057 · Cited by 255
Self-citationAttentional Modulation of Alpha/Beta and Gamma Oscillations Reflect Functionally Distinct Processes
Bauer, M., Stenner, M.-P., Friston, K. J., & Dolan, R. J. (2014) · The Journal of Neuroscience · doi:10.1523/jneurosci.3474-13.2014 · Cited by 224
Self-citationAn in vivo assay of synaptic function mediating human cognition
Moran, R. J., Symmonds, M., Stephan, K. E., Friston, K. J., & Dolan, R. J. (2011) · Current Biology · doi:10.1016/j.cub.2011.06.053 · Cited by 137
Self-citation
Metadata
- Authors
- Litvak, V., Mattout, J., Kiebel, S., Phillips, C., Henson, R., Kilner, J., Barnes, G., Oostenveld, R., Daunizeau, J., Flandin, G., Penny, W., & Friston, K.
- Venue
- Computational Intelligence and Neuroscience
- Publisher
- Wiley
- Published
- 2011
- Volume
- 2011
- Pages
- 1-32
- ISSN
- 1687-5265 (ISSN-L)
- 1687-5273
- OpenAlex
- W2028985479
- Cited by
- 581
- References
- 14
- FWCI
- 17.94
- Type
- journal article
- Language
- en
- Open access
- hybrid
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: EEG and MEG Data Analysis in SPM8. https://app.cochat.ai/papers/10.1155/2011/852961
- The paper
- Litvak, V., Mattout, J., Kiebel, S., Phillips, C., Henson, R., Kilner, J., Barnes, G., Oostenveld, R., Daunizeau, J., Flandin, G., Penny, W., & Friston, K. (2011). EEG and MEG Data Analysis in SPM8. Computational Intelligence and Neuroscience. https://doi.org/10.1155/2011/852961
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.