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Computational Intelligence and Neuroscience
Volume 2011, Article ID 156869, 9 pages
http://dx.doi.org/10.1155/2011/156869
Research Article

FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data

1Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, 6500 HB Nijmegen, The Netherlands
2Ernst Strüngmann Institute and Max Planck Society, D-60528 Frankfurt, Germany

Received 26 August 2010; Accepted 18 October 2010

Academic Editor: Sylvain Baillet

Copyright © 2011 Robert Oostenveld et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. A. Delorme and S. Makeig, “EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis,” Journal of Neuroscience Methods, vol. 134, no. 1, pp. 9–21, 2004. View at Publisher · View at Google Scholar · View at Scopus
  2. M. Scherg, “Fundamentals of dipole source potential analysis,” in Advances in Audiology. Auditory Evoked Magnetic Fields and Electric Potentials, vol. 6, pp. 40–69, Karger, Basel, Switzerland, 1990. View at Google Scholar
  3. M. S. Hämäläinen and R. J. Ilmoniemi, “Interpreting magnetic fields of the brain: minimum norm estimates,” Medical and Biological Engineering and Computing, vol. 32, no. 1, pp. 35–42, 1994. View at Google Scholar · View at Scopus
  4. B. D. Van Veen, W. Van Drongelen, M. Yuchtman, and A. Suzuki, “Localization of brain electrical activity via linearly constrained minimum variance spatial filtering,” IEEE Transactions on Biomedical Engineering, vol. 44, no. 9, pp. 867–880, 1997. View at Publisher · View at Google Scholar · View at Scopus
  5. J. Gross, J. Kujala, M. Hämäläinen, L. Timmermann, A. Schnitzler, and R. Salmelin, “Dynamic imaging of coherent sources: studying neural interactions in the human brain,” Proceedings of the National Academy of Sciences of the United States of America, vol. 98, no. 2, pp. 694–699, 2001. View at Publisher · View at Google Scholar · View at Scopus
  6. A. M. Dale, B. Fischl, and M. I. Sereno, “Cortical surface-based analysis—I. Segmentation and surface reconstruction,” NeuroImage, vol. 9, no. 2, pp. 179–194, 1999. View at Publisher · View at Google Scholar · View at Scopus
  7. E. Maris and R. Oostenveld, “Nonparametric statistical testing of EEG- and MEG-data,” Journal of Neuroscience Methods, vol. 164, no. 1, pp. 177–190, 2007. View at Publisher · View at Google Scholar · View at Scopus
  8. P. P. Mitra and B. Pesaran, “Analysis of dynamic brain imaging data,” Biophysical Journal, vol. 76, no. 2, pp. 691–708, 1999. View at Google Scholar · View at Scopus
  9. J. Cui, L. Xu, S. L. Bressler, M. Ding, and H. Liang, “BSMART: a Matlab/C toolbox for analysis of multichannel neural time series,” Neural Networks, vol. 21, no. 8, pp. 1094–1104, 2008. View at Publisher · View at Google Scholar · View at Scopus
  10. J.-P. Lachaux, E. Rodriguez, J. Martinerie, and F. J. Varela, “Measuring phase synchrony in brain signals,” Human Brain Mapping, vol. 8, no. 4, pp. 194–208, 1999. View at Publisher · View at Google Scholar · View at Scopus
  11. G. Nolte, O. Bai, L. Wheaton, Z. Mari, S. Vorbach, and M. Hallett, “Identifying true brain interaction from EEG data using the imaginary part of coherency,” Clinical Neurophysiology, vol. 115, no. 10, pp. 2292–2307, 2004. View at Publisher · View at Google Scholar · View at Scopus
  12. C. J. Stam, G. Nolte, and A. Daffertshofer, “Phase lag index: assessment of functional connectivity from multi channel EEG and MEG with diminished bias from common sources,” Human Brain Mapping, vol. 28, no. 11, pp. 1178–1193, 2007. View at Publisher · View at Google Scholar · View at Scopus
  13. L. A. Baccalá and K. Sameshima, “Partial directed coherence: a new concept in neural structure determination,” Biological Cybernetics, vol. 84, no. 6, pp. 463–474, 2001. View at Google Scholar · View at Scopus
  14. M. Kamiński, M. Ding, W. A. Truccolo, and S. L. Bressler, “Evaluating causal relations in neural systems: granger causality, directed transfer function and statistical assessment of significance,” Biological Cybernetics, vol. 85, no. 2, pp. 145–157, 2001. View at Publisher · View at Google Scholar · View at Scopus
  15. A. Brovelli, M. Ding, A. Ledberg, Y. Chen, R. Nakamura, and S. L. Bressler, “Beta oscillations in a large-scale sensorimotor cortical network: directional influences revealed by Granger causality,” Proceedings of the National Academy of Sciences of the United States of America, vol. 101, no. 26, pp. 9849–9854, 2004. View at Publisher · View at Google Scholar · View at Scopus
  16. B. N. Cuffin and D. Cohen, “Magnetic fields of a dipole in special volume conductor shapes,” IEEE Transactions on Biomedical Engineering, vol. 24, no. 4, pp. 372–381, 1977. View at Google Scholar · View at Scopus
  17. M. X. Huang, J. C. Mosher, and R. M. Leahy, “A sensor-weighted overlapping-sphere head model and exhaustive head model comparison for MEG,” Physics in Medicine and Biology, vol. 44, no. 2, pp. 423–440, 1999. View at Publisher · View at Google Scholar · View at Scopus
  18. G. Nolte, “The magnetic lead field theorem in the quasi-static approximation and its use for magnetoenchephalography forward calculation in realistic volume conductors,” Physics in Medicine and Biology, vol. 48, no. 22, pp. 3637–3652, 2003. View at Publisher · View at Google Scholar · View at Scopus
  19. G. Adde, M. Clerc, O. Faugeras, R. Keriven, J. Kybic, and T. Papadopoulo, “Symmetric BEM formulation for the M/EEG forward problem,” Information Processing in Medical Imaging, vol. 18, pp. 524–535, 2003. View at Google Scholar · View at Scopus
  20. T. F. Oostendorp and A. Van Oosterom, “Source parameter estimation in inhomogeneous volume conductors of arbitrary shape,” IEEE Transactions on Biomedical Engineering, vol. 36, no. 3, pp. 382–391, 1989. View at Google Scholar · View at Scopus
  21. M. van Gerven, C. Hesse, O. Jensen, and T. Heskes, “Interpreting single trial data using groupwise regularisation,” NeuroImage, vol. 46, no. 3, pp. 665–676, 2009. View at Publisher · View at Google Scholar · View at Scopus