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Subject:

Re: Time derivative in event related design

From:

Jonas Persson <[log in to unmask]>

Reply-To:

Jonas Persson <[log in to unmask]>

Date:

Mon, 30 May 2011 13:58:00 +0100

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text/plain

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Thanks for the reference.

I've read through the article and played around with the Matlab scripts provided. I have a few potentially stupid questions though:

1. The ratio value which is used to calculate the contrast weights, is it always .44 and -.34 respectively if you want to keep the same physiological contraints as the author or do you have to calculate them for your design? If so, how?

2. I'm not sure how to expand this method to cases where you want to compare activation between 2 experimental conditions. The scripts seem to be designed for 2 regressors corresponding to the HRF and derivative for a single condition only.

Thank you for being patient with me.

/Jonas Persson

On Fri, 20 May 2011 17:00:39 -0400, MCLAREN, Donald <[log in to unmask]> wrote:

>See Investigating hemodynamic response variability at the group level
>using basis functions by Steffener et al.
>
>
>On Friday, May 20, 2011, Jonas Persson <[log in to unmask]> wrote:
>> Hello fellow SPM:ers,
>>
>> I am a bit confused with regards to using the time derivative in SPM.
>>
>> The issue is that I have an event related paradigm where I do post hoc sorting of stimuli to 2 conditions. At the last SPM course I learned that slice time correction should be avoided, so instead of using time slice correction I wanted to include a second basis function to account for timing differences in data acquisition between slices.
>>
>> To check for regions significantly more activated in cond 1 vs cond 2 I did an F-contrast [1 0 -1 0; 0 1 0 -1] to look for voxels associated with either the HRF or td. I masked this contrast inclusive with a t-contrast [1 0 -1 0] to only look at voxels with activation corresponding to the HRF. The problem here is that I'm telling SPM to look for voxels with different timing depending on condition, while I'm interested in allowing for timing differences between regions regardless of condition.
>>
>> Another variant I've thought of is to merely do a t-contrast [1 0 -1 0], controlling for any variance associated with the td, but I read that this may give biased results.
>>
>> The next issue is how to perform the 2nd level analysis. With the latter method it's straightforward, but from what I understand I can't do a random effects on F-contrasts?
>>
>> Thank you for any suggestions!
>>
>> Bert regards,
>>
>> Jonas Persson
>>
>
>--
>
>Best Regards, Donald McLaren
>=================
>D.G. McLaren, Ph.D.
>Postdoctoral Research Fellow, GRECC, Bedford VA
>Research Fellow, Department of Neurology, Massachusetts General Hospital and
>Harvard Medical School
>Office: (773) 406-2464
>=====================
>This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED
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