Dear Mark & Joe,
thanks for clarifying this issue; I've learned something from this and
appreciate your comments. Thanks for the tip on the covariance matrix, Jo,
that is useful - there's more to fMRI analysis than clicking buttons! Mark,
can we look forward to hearing more about the modelling work in 2003? I
hope your verifications are fun and fruitful ;-)
Cheers, Darren
----- Original Message -----
From: "Joe Devlin" <[log in to unmask]>
To: <[log in to unmask]>
Sent: Thursday, January 02, 2003 8:01 PM
Subject: Re: mcflirt for multiple runs
> Hi Mark,
>
> Can I just follow up on your comments about motion correction and
including
> motion parameters as covariates? One thing that I think is important to
> mention is that "motion correction" is a misnomer -- the process actually
> realigns the 3D volumes to minimize the effects of minor head
> movements. It does not "correct for motion" for all the reasons Mark
> said. As a result, there are still motion effects in one's data set after
> realignment.
>
> In my experience, including the estimates motion params as covariates of
no
> interest is often helpful in improving statistical sensitivity despite the
> caveats Mark mentioned. But the main thing to consider is whether the
> motion is correlated with your experimental paradigm. If it is, then
these
> covariates may remove signal that *may be* related to your experimental
> manipulation. As the two are correlated, however, there is no way to tell
> for certain where the activation is coming from (motion or experiment or
> both). Personally, when that happens in one of my subjects, I throw the
> data from that subject (or session) out. BTW, one easy/informal way to
> check for correlated motion is to look at the covariance matrix provided
in
> the FEAT web report.
>
> With that in mind, I can't see any good reason why one would ever 1) not
> realign data but only include motion estimates as covariates or 2) only
> realign without including motion estimates in the model. It seems to me
> that together the two are more powerful than either alone (assuming the
> data aren't confounded by stimulus-correlated motion for which there is no
> solution). And even together, they still don't "correct for motion" as
the
> process introduces additional smoothing, residual non-linear effects
> remain, etc.
>
> Is this a fair summary or am I still missing some issues?
> Joe
>
> Joseph Devlin, Ph. D.
> FMRIB, Dept. of Clinical Neurology
> University of Oxford
> John Radcliffe Hospital
> Headley Way, Headington
> Oxford OX3 9DU, U.K.
> Phone: +44 (0)1865 222 738
> Fax: +44 (0)1865 222 717
> Email: [log in to unmask]
>
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