Hi,
This post is regarding the applicability of topological FDR method (see the references 1,2 below) to EEG functional connectivity analysis that I am interested in trying for my study.
My measure of functional connectivity is a phase locking value - computed from pair-wise EEG signals that are obtained using 10-20 system. To compute the phase locking value, the signals were decomposed in a wavelet domain. My objective is to detect the electrode pairs, frequency bands, and time-intervals with significant phase locking value. My analysis accounts for possible electrode pairs in a pre-specified range of frequency-bands and time-intervals.
I do not have structural MRI data for subjects.
If it is at all possible to topologically reconstruct EEG signals without the structural scans, I am not sure how well the good lattice assumption that is required by random field theory will hold for such low-density EEG. Moreover, as I have understood the method can be either applied to topological space or over time, or over frequency but not for all the three dimensions simultaneously.
If there is some way this method can be applied/extended to the kind of analysis I mentioned above, I would be interested in getting some inputs from you.
1) Chumbley J, Worsley K, Flandin G, Friston K., Topological FDR for
neuroimaging. Neuroimage. 2010 Feb 15;49(4):3057-64
2) James M. Kilner and Karl J. Friston. Topological inference for EEG
and MEG. Ann. Appl. Stat. Volume 4, Number 3 (2010), 1272-1290
Thanks in advance,
Jiti
|