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Multimodal, Multisubject data fusion


  • Henson, R.N., Mattout, J., Phillips, C. and Friston, K.J. (2009). Selecting forward models for MEG source-reconstruction using model-evidence. Neuroimage, 46, 168-176.
  • Henson, R.N., Wakeman, D.G., Litvak, V. and Friston, K.J. (2011). A Parametric Empirical Bayesian framework for the EEG/MEG inverse problem: generative models for multisubject and multimodal integration. Frontiers in Human Neuroscience, 5, 76, 1-16.
  • Wakeman, D.G. and Henson, R.N. A multi-subject, multi-modal human neuroimaging dataset. Scientific Data, 2:150001.


This work was supported by MRC (A060_MC_5PR10). The author (RNH) thanks Rebecca Beresford, Hunar Abdulraham, Daniel Wakeman, Guillaume Flandin and Vladimir Litvak for their help.



  3. On Linux, from the command line, you can type the following to download all of the relevant data from Subject 15:

    wget -r -nH –cut-dirs=3 -X "/*/*/*/*/DWI/,/*/*/*/*/FLASH/" –reject raw.fif

    On Windows, you can access the FTP server from the File Explorer and copy the entire folder on your hard disk. Alternatively, you can use dedicated software such as FileZilla or WinSCP

  4. Note that you can create a MATLAB variable containing the weights of the F-contrast with C = kron(eye(3),[1 0 0]), and then enter C, 0.5*C(1,:)+0.5*C(2,:)-C(3,:), C(1,:), C(2,:) and C(3,:) respectively for the 5 contrasts specified above.