Dear Vladimir,
Thank you so much for the detailed reply. Could I conclude your replies as follows?
1. Try to do correction for multiple comparisons to avoid false positive.
2. If there is no hypothesis IN ADVANCE, SPM is better than SPSS because the former can provide a significant map with both temporal and spatial information.
3. Use small time window of interest to do analysis.
4. Cluster-level inference is welcome, so large extent threshold is good.
However, I would still like to ask more clearly
1. If there is no significance left (I am often unlucky to meet such results) after correction for multiple comparisons (FWE or FDR), could I use uncorrected p value (p < 0.05) with large extent threshold such as k > 400? Because it seems impossible that more than 400 adjacent voxels are all false positive. If you are the reviewer, could you accept that result?
2. You said that it is "absolutely statistically invalid thing to do is to find an uncorrected effect in SPM and then go and
test the same channel and time window in SPSS." However, I found that if the uncorrected effect (e.g. p < 0.05 uncorrected, k > 400) appeared at some sites in SPM, SPSS analysis involving the same channel and time window would show a more significant result. Because most ERP researchers now accept the results by SPSS, is it a way to use SPM as a guide to show the possible significant ROI (temporally and spatially) and use SPSS to get the statistical significance?
3. If the small time window of interest is more sensitive, could I use several consecutive small time window (e.g. 50 ms) of interest to analysis long component such as LPC (I know some researchers use consecutive time window to analysis LPC component by SPSS) or as an exploring tool to investigate the possible significant result on dataset without hypothesis IN ADVANCE?
4. Because of the head shape and some other reasons, the 2D projection map of each individual' sensors on scalp is some different from the standard template provided by SPM. Is it correct to put each subjects' images based on their own 2D sensors' map into the GLM model for specification, or use images based on standard 2D sensors' map instead? I have tested both ways and found that the previous method may lead to some stripe like significance at the border of mask. I do no know why.
Sorry for asking some weak questions, however, I really like the EEG/MEG module of SPM8.
Bests,
Sun Delin
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