> 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. <
alb.net@
gmail.com> 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. <
alb.net@
gmail.com>:
>>>> > 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. McLaren
>> University of Wisconsin - Madison
>> Neuroscience Training Program
>> Office: (608) 265-9672
>> Lab: (608) 256-1901 ext 12914
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>