Hi - in general it's better to use smooth basis functions (eg as used by 
default in FLOBS) than "square" bases like default FIR bases.  
There's some literature on that but I can't quite remember now who published 
that - but it seems logical given that you're fitting smooth data - assuming 
(eg) jittering of events relative to TRs.
Cheers.




> On 22 Sep 2016, at 21:44, Michael Dreyfuss <mdreyfus...@gmail.com> wrote:
> 
> OK, thank you. I've read both these papers but it's been a while - do you 
> mind if I ask where specifically you see that this misatribution is 
> problematic for events in mixed designs rather than events in an event only 
> design?
> 
> I would be interested in using the FIR function. I'm assuming that using a 
> fixed function is not problematic for modeling the blocks though, right? 
> 
> Unfortunately the fsl wiki appears to be down now, so I can't see how to 
> implement FLOBS. for FIR, I'm assuming I can just modify the fsf files before 
> feat_model.
> 
> Thank you,
> Michael
> 
> On Thu, Sep 22, 2016 at 3:35 PM, Burgess, Gregory <gburg...@wustl.edu 
> <mailto:gburg...@wustl.edu>> wrote:
> If you’re referring to what is sometimes called a “state-item” design (cf. 
> http://www.nil.wustl.edu/labs/schlaggar/Publications_files/MIxedBlockPaper_Final.pdf
>  
> <http://www.nil.wustl.edu/labs/schlaggar/Publications_files/MIxedBlockPaper_Final.pdf>),
>  you should not use a canonical / assumed response shape. That’s because the 
> variance that is not captured by your assumed HRF can be misattributed to 
> your state / sustained regressor.
> 
> For these designs, your event-related effects should be modeled with a basis 
> set that will capture varying response shapes (e.g., FIR or FLOBS) to ensure 
> that you do not misattribute poorly-modeled activation to the sustained 
> regressor. I don’t know much about the inverse logit basis set, but you might 
> consider looking at it too (Lindquist et al. 2009). An advantage of the FIR 
> basis set is that you can easily look for interactions with “time” to test if 
> the response shape varies between regions or individuals.
> 
> Lindquist, M. A., Meng Loh, J., Atlas, L. Y., & Wager, T. D. (2009). Modeling 
> the hemodynamic response function in fMRI: efficiency, bias and mis-modeling. 
> NeuroImage, 45(1 Suppl), S187–98. 
> http://doi.org/10.1016/j.neuroimage.2008.10.065 
> <http://doi.org/10.1016/j.neuroimage.2008.10.065>
> 
> --Greg
> 
> ____________________________________________________________________
> Greg Burgess, Ph.D.
> Staff Scientist, Human Connectome Project
> Washington University School of Medicine
> Department of Psychiatry
> Phone: 314-362-7864 <tel:314-362-7864>
> Email: gburg...@wustl.edu <mailto:gburg...@wustl.edu>
> 
> > On Sep 22, 2016, at 2:05 PM, Michael Dreyfuss <mdreyfus...@gmail.com 
> > <mailto:mdreyfus...@gmail.com>> wrote:
> >
> > Thank you both.
> >
> > This is for our task which is actually a mixed design. I'm not too 
> > concerned about the blocks because like you say the main goal is estimating 
> > amplitude there. For the jittered events, however, I would want more 
> > flexibility in the basis function because like you said the HRF could have 
> > quite different shapes in different regions and different individuals. 
> > Regardless, the activation patterns I'm seeing seem reasonable. I'm just 
> > wondering if the double gamma is also better fitted to visual cortex and so 
> > activation there is more detectable than in other regions, and if so maybe 
> > activity in other regions would be better detected using a more flexible 
> > basis function like FLOBS of FIR. I think your explanation about proximity 
> > to the head coil may be a big part of that too, though, so I'm reluctant to 
> > assume there is a problem with using double gamma (and there is a cost to 
> > estimating the basis function everywhere too).
> >
> > I will continue to look into these other options...
> >
> > Thanks again,
> > Michael
> >
> > On Thu, Sep 22, 2016 at 2:31 PM, Burgess, Gregory 
> > <burge...@psychiatry.wustl.edu <mailto:burge...@psychiatry.wustl.edu>> 
> > wrote:
> > Hi Michael,
> >
> > A few things:
> > 1) Matt’s point about the increased activation estimates in visual cortex 
> > is a good one. There is increased signal in occipital cortex in functional 
> > connectivity analyses that do not assume a response shape. In part, this 
> > may result from the back of the head being closer to the head coil than 
> > other brain regions (because participants are laying down).
> > 2) To the best of my knowledge, the HCP consortium has not ventured to 
> > recommend a single, ideal HRF for use in task fMRI analysis. In fact, I’d 
> > wager that most people in the consortium expect the hemodynamic response to 
> > vary across brain regions and across people in such a way that there is no 
> > single ideal canonical HRF.
> > 3) We chose the double-gamma during very early analysis of HCP pilot data. 
> > Using 2.5s TR data, the default double-gamma showed zstat maps with 
> > slightly higher statistical significance at the group-level than the 
> > default gamma HRF (in Feat). The double-gamma also seemed to be used more 
> > widely in the literature, in part due to the commonly observed undershoot 
> > at the end of the hemodynamic response (see Glover, 1999). We made this 
> > choice in piloting, and stayed with it for analysis of the Phase II HCP. We 
> > did not re-evaluate HRFs in the fast TR HCP data.
> > 4) In HCP tfMRI, we utilized blocked designs. Blocked designs are good for 
> > detecting the response, but are not good for estimating the shape of the 
> > response function. It may follow that differences between canonical HRFs 
> > will matter less for blocked designs, but I don’t know if anyone has looked 
> > at that systematically.
> > 5) If you’re referring to analysis of your own data using an event-related 
> > design, your best bet will likely be using a basis set. FSL has FLOBS, 
> > folks at Wash U tend to use FIR basis sets, but there are others out there 
> > as well. There are quite a few papers out there to help you choose between 
> > those basis sets. However, I’m not sure it would make much sense in the 
> > context of a blocked design.
> >
> > Hope this all helps!
> > --Greg
> >
> > ____________________________________________________________________
> > Greg Burgess, Ph.D.
> > Staff Scientist, Human Connectome Project
> > Washington University School of Medicine
> > Department of Psychiatry
> > Phone: 314-362-7864 <tel:314-362-7864>
> > Email: gburg...@wustl.edu <mailto:gburg...@wustl.edu>
> >
> > > On Sep 22, 2016, at 12:25 PM, Glasser, Matthew <glass...@wustl.edu 
> > > <mailto:glass...@wustl.edu>> wrote:
> > >
> > > BOLD fluctuations are generally stronger on the occipital cortex
> > > (independent of the chosen HRF).  See for example the attached functional
> > > CNR map (BOLDVariance / UnstructuredNoiseVariance).
> > >
> > > Peace,
> > >
> > > Matt.
> > >
> > > On 9/21/16, 7:29 PM, "hcp-users-boun...@humanconnectome.org 
> > > <mailto:hcp-users-boun...@humanconnectome.org> on behalf of
> > > Michael Dreyfuss" <hcp-users-boun...@humanconnectome.org 
> > > <mailto:hcp-users-boun...@humanconnectome.org> on behalf of
> > > mdreyfus...@gmail.com <mailto:mdreyfus...@gmail.com>> wrote:
> > >
> > >> Hello,
> > >>
> > >> What kind of basis function are you recommending for tfMRI data?I have
> > >> been using double-gamma HRF but I notice that the signal is always
> > >> strongest in occipital cortex, so I was wondering if this is not optimal
> > >> for other regions. If so, do you have a more customized recommendation
> > >> that would better fit HRF functions in other parts of the brain to detect
> > >> signal there?
> > >>
> > >> Thank you,
> > >> Michael
> > >> _______________________________________________
> > >> HCP-Users mailing list
> > >> HCP-Users@humanconnectome.org <mailto:HCP-Users@humanconnectome.org>
> > >> http://lists.humanconnectome.org/mailman/listinfo/hcp-users 
> > >> <http://lists.humanconnectome.org/mailman/listinfo/hcp-users>
> > >
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