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Hi,

the last 22 columns are the subject-specific time courses - the first column is the single best Eigen-timecourse which explains the largest amount of variance in the set of 22 time courses. This is not the mean time course but the output from the rank-1 approximation. The difference is important: imagine that half of your population have the same associated temporal response and the other half have exactly the inverse (e.g. on/off blocked response in the one half and off/on blocked response in the other). Calculating the mean will give you something close to constant zero whereas the rank-1 approximation gives you the on/off pattern and a vector of -1 ... -1 1 ...1 as the subject mode .... much more informative than calculating the mean only!

This Eigen-timecourse is what is plotted in the web report as the time course of the component. In case you have specified a GLM design matrix in the GUI for post-hoc fitting there will be another time course in the text file which shows the full model fit. This time course will also be plotted in the web report. 

hope this helps

Christian

_______________________________________________

Christian F. Beckmann, DPhil

Senior Lecturer, Clinical Neuroscience Department

Division of Neuroscience and Mental Health

Imperial College London

Hammersmith Campus, Rm 247, Cyclotron Bldg

Du Cane Road, London W12 0NN, UK

Tel.: +44 (0) 208 383 8598   ---   Fax: +44 (0) 208 383 2029

Email: [log in to unmask]   

http://www.imperial.ac.uk/medicine/people/c.beckmann/