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Dear Vladimir, Thank you so much for your detailed reply. I will always support your work, and I wish you success in your work! Best regards! Haoran 在 2011-11-24 00:17:51，"Vladimir Litvak" <[log in to unmask]> 写道： >Dear Haoran, > >On Wed, Nov 23, 2011 at 3:02 PM, 飞鸟 <[log in to unmask]> wrote: >> Dear Vladimir, >> Thank you very much for your long term help. Last time you said you >> would update the spm and improve DCM, thus, I thought the problems I >> confronted might faciliate your work. I have confronted several problems >> about DCM for induced responses recently. But, I could not make them clear. >> The problems come as follow: >> 1. As mentioned in last letter, several steps in EM iteration might be >> time-consuming during dcm_ind computation, and might take 1 or 2 hours.The >> ensuing results appeared in matlab command window would be "...actual: NaN >> (3285.06 sec)". At the same time, other steps only took several seconds. >> This phenomenon would appeare if I changed the time-bin of DCM.options.Tdcm. >> Anyhow, time-consuming phenomenon was an event of low probability. I >> wondered whether it has special relationship with my dataset I choosed or >> the time-window I selected. > >As I said, you should try the next SPM update. At the moment we are >still testing the modified code so I'd suggest that you wait till we >officially release it. > >> 2. Considering the above problem might be resulted from the time-window, I >> checked the "spm_dcm_ind_data.m". As Chen said "Baseline power was removed >> by subtracting the frequency-specific power at the first time-bin "(Chen, >> C.-C., S. J. Kiebel, et al. "A dynamic causal model for evoked and induced >> responses." NeuroImage(0).). I checked the code which realizes this >> function in "spm_dcm_ind_data.m". But it seemed that we just subtracted the >> frequnecy-specific power at the first time point. I didn't know if it was >> the reason caused that problem. And I wondered whether it would be better to >> subtract the averaged frequnecy -specific power over a time window (eg. from >> -50 to 0 ms) but not at a time point '-50'. > >Yes, this is one of the things the inversion is sensitive to. The >modified code averages over slightly longer window. > >> 3. The results I got under one condtion showed that non-linear frequency >> coupling existed, though I just set it as linear in matrix A. Was it >> reasonable? > >Because of reduction of frequency spaces to a small number of modes >linear coupling shows as things which are on the diagonal or symmetric >with respect to the diagonal. I suspect what you saw is some coupling >which was not on the diagonal but symmetric. It is not non-linear. >Non-linear would be something asymmetric with respect to the diagonal. > >> 4. In Chen's paper(aforementioned above), it said we could not only deal >> with evoked reponses but also induced reponses by DCM_IND. I was confused >> with this because the framework of DCM_IND kept same but its funciton >> expanded a bit sudden relative to the first paper of DCM of induced >> responses (Chen, C. C., S. J. Kiebel, et al. (2008). "Dynamic causal >> modelling of induced responses." NeuroImage 41(4): 1293-1312.). Does >> spm8_4290 supply this function? >> 5. What if we take averaged trials into dcm_induced analysis? I know we >> can also get cross-coupling results. Intuitively, it seems to reflect the >> frequncey features of ERP, but is it meaningful? >> Thank you again for your great help to our research work. Best regards! >> > >In the later paper what is meant by evoked responses is exactly ERPs >which are subjected to time-frequency analysis. So in this sense >DCM-IR can handle 'evoked responses' but it does not do the same thing >as DCM-ERP. The idea was to ask whether the features of the dynamics >requiring nonlinear coupling to model them are present in the evoked >response (i.e. things which are phase-locked to the stimulus) or they >are only in the part which is not phase-locked. For asking this kind >of question it makes sense to use averaging prior to DCM-IR but it >does not make sense in general. > >Best, > >Vladimir > >> -- >> Haoran LI (MS) >> Brain Imaging Lab, >> Research Center for Learning Science, >> Southeast University >> 2 Si Pai Lou , Nanjing, 210096, P.R.China