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
