Hi Will,
At the present time, when you compute the time-frequency decomposition of a source matrix, it actually does the TF decomposition of the recordings, and then multiplies it by the inversion kernel at the desired vertices or time points. The full TF matrix is never fully computed.
It is theoretically possible to compute this full time frequency decomposition of a full source file. The size of the matrix would be, for a small file (let’s say 15000 vertices, 2000 time samples and 60 frequency bins):
15000 * 2000 * 60 * 8 / 1024^3 = 13.4Gb
For its manipulation, even if the code was extremely optimized, you would need at least 3 times the amount of memory, ie. about 40Gb of RAM. So it would not work, even on your 64bits linux system with 18Gb RAM.
Conclusion: this operation is not, and will never be, an option. The alternatives are the following:
[ul]
[li]Source reconstruction by frequency bands: Interesting option but would require some research and a lot of development. Will not be available in Brainstorm before 2012.
[/li][li]Time-frequency decomposition of some scouts time series. If you want a representation of the entire cortex, you can create a parcellation of the cortex in scouts with the menu New>Surface clustering in the Scout tab. Or use the Tzourio-Mazoyer atlas on Colin brain (load scout > scout_tzourio-mazoyer.mat). But you’d have to analyze the results by yourself, there are no display functions for this kind of data.
[/li][li]Do you time-frequency analysis at the sensor level only
[/li][/ul]
Francois