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In response to question 1) See Jack Grinband's paper: Figure 4. There he clearly demonstrates what happens when epochs of varying length are convolved with the HRF. Jason On Wed, Mar 25, 2009 at 2:34 AM, MCLAREN, Donald <[log in to unmask]>wrote: > In response to question 2. The duration of each event within a condition > can vary and is set in the condition array. The condition array has the > onset times and durations specified. In this way, some events can have a 0s > duration and other can have the RT as the the duration. > > > On Wed, Mar 25, 2009 at 12:07 AM, Michael T Rubens <[log in to unmask]>wrote: > >> Hi Dorian, >> >> >> On Tue, Mar 24, 2009 at 3:28 PM, Dorian P. <[log in to unmask]> wrote: >> >>> Dear all, >>> >>> As I didn't receive an answer for this topic and it interest me quite >>> a lot I am repeating the question again. >>> >>> Given that: >>> 1. The only change between 0 duration and X duration is a simple >>> longer HRF for longer duartion values >> >> >> This is not true, the difference between 0 dur vs. dur>0 is the function >> convolved with your HRF. A stick function for events, resulting in a delta >> function vs. a boxcar. The difference between durations > 0 is in magnitude >> (amplitude). >> >>> >>> 2. The reaction times are shown to be better catched by variable >>> durations. >>> >>> Is it plausible to manually convolve only the regressor of RTs with >>> custom durations, while all other durations for events of interests >>> are 0 (ie event related design)??? >>> >> >> This should be possible. The only problem is that spm (as far as I know, >> but please correct me if wrong) only allows different durations for >> different covariates. To have different durations for some onsets within a >> covariate would require hacking the spm code. Perhaps the folks at columbia >> (grinband or wager) could provide the code they used. >> >> >>> >>> Would this manipulation of HRF convolve for a single regressor affect >>> the other regressors some way? >> >> >> the effect on other covariates should be minimal. >> >>> >>> >>> Thanks for any possible answer. >>> >>> Dorian. >> >> >> >> This method is quite different from adding time/dispersion derivatives to >> the hrf, because in my understanding, those derivatives regress out the >> temporal and shape differences in the irf. By manipulating the duration by >> rt you are essentially saying that magnitude of the irf is modulated >> linearly as a function of rt, which seems to be a way to normalize responses >> within a subject. What is your purpose for pursuing this technique? >> >> Cheers, >> Michael >> >> >> >> -- >> Research Associate >> Gazzaley Lab >> Department of Neurology >> University of California, San Francisco >> >>> >>> >>> 2009/3/18 Dorian P. <[log in to unmask]>: >>> > Hi all, >>> > >>> > Sorry but couldn't understand the difference between neural and >>> > haemodynamic variations. >>> > >>> > Probably I should read more on the topic, because I thought dispersion >>> > derivative was also trial specific. But I can imagine a model with >>> > mixed properties, so that normal regressors are convolved with impulse >>> > HRF functions (dur = 0), while RT regressors convolved with variable >>> > duration HRFs (dur = RT). At the end shouldn't be difficult for SPM to >>> > asses both regressors. They just get e beta value who tells how well >>> > the HRF for that regressor explains variability. Am I correct on this? >>> > >>> > Dorian. >>> > >>> > 2009/3/18 Jason Steffener <[log in to unmask]>: >>> >> Yes, you have it right. >>> >> >>> >> If you currently have events modeled their durations are 0. With the >>> >> variable epoch model the durations become the trial specific RTs. Just >>> make >>> >> sure you are consistent between whether you are specifying time in TRs >>> or >>> >> seconds. >>> >> >>> >> Jason >>> >> >>> >> On Wed, Mar 18, 2009 at 12:29 PM, Esther Fujiwara < >>> [log in to unmask]> >>> >> wrote: >>> >>> >>> >>> For my understanding, in SPM would a variable epoch model be >>> implemented >>> >>> by using the respective RTs as durations for single events, instead >>> of 0s? >>> >>> Or is there more to it? >>> >>> >>> >>> Esther >>> >>> >>> >>> Jason Steffener wrote: >>> >>>> >>> >>>> The variable epoch model uses the RT from each trial; therefore, it >>> is >>> >>>> able to capture trial specific variance. The impulse with HRF + >>> derivatives >>> >>>> may capture some of the variance due to RTs but it essentially takes >>> the >>> >>>> average RT over all trials for this condition. And as Chris points >>> out there >>> >>>> may be some RTs where the impulse model can in no way accuratly >>> account for. >>> >>>> >>> >>>> I also feel that the HRF + derivatives should be used to capture >>> >>>> hemodynamic variations and not neural variations. Otherwise you make >>> it very >>> >>>> difficult to tease about which is which. >>> >>>> >>> >>>> Jason. >>> >>>> >>> >>>> On Tue, Mar 17, 2009 at 6:19 PM, Chris Watson >>> >>>> <[log in to unmask] >>> >>>> <mailto:[log in to unmask]>> wrote: >>> >>>> >>> >>>> I think it would depend on the shape of your HRF. The variable >>> epoch >>> >>>> model has boxcars that are as long as the RT,. If you used an >>> >>>> impulse model, convolved with the canonical hemodynamic response, >>> >>>> even adding the dispersion derivative might not capture the >>> signal >>> >>>> for long RT's (as the shape of the HRF in the variable epoch >>> model >>> >>>> will be quite different from the canonical). E.g. in one of our >>> >>>> tasks, we see RT's of up to 7000ms. I don't think an impulse >>> model >>> >>>> even with both derivatives would do nearly as well as an epoch >>> model. >>> >>>> >>> >>>> >>> >>>> Dorian P. wrote: >>> >>>> >>> >>>> Dear all, >>> >>>> >>> >>>> Thinking about a previous discussion on the list, we said >>> that >>> >>>> reaction time effects are better captured by a variable epoch >>> >>>> durations, which adapts to reaction time length. >>> >>>> In a couple of papers was shown that a variable epoch aproach >>> is >>> >>>> better than parametric modulations. >>> >>>> >>> >>>> >>> >>>> >>> http://www.sciencedirect.com/science/article/B6WNP-4T77G33-4/2/cc5ef4a8e9fbff5b4a99bd5f05663bf9 >>> >>>> >>> >>>> >>> http://www.columbia.edu/cu/psychology/tor/Posters/grinband_HBM06.pdf >>> >>>> >>> >>>> But isn't this the same as adding a dispersion derivative, >>> which >>> >>>> would >>> >>>> convolve a longer HRF automatically for RTs and capture that >>> >>>> signal >>> >>>> the same way as a variable epoch approach? >>> >>>> >>> >>>> Best regards. >>> >>>> Dorian. >>> >>>> >>> >>>> >>> >>>> >>> >> >>> >> >>> > >>> >> >> >> >> > > > -- > Best Regards, Donald McLaren > ===================== > D.G. 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