Dear Joe,
the z maps are an indication of whether or not the coefficient for a given
functional model is greater than zero. That is,
Y = bX + c
where X is a study design (single trials or blocked baseline vs activation
modulation) convolved with the HRF and b is the coefficient that provides
the best least-squared fit for that model to the observed BOLD response (Y).
Can the b values be converted to correlation coefficients or %variance
accounted for (R^2)? I wonder if that could provide some useful index for
thresholding? That is, I wonder how to weigh up the spatial extent vs the
degree of fit. Surely it is possible to have a very focal, isolated
activation with a very high degree of fit. Maybe this is implicit in the z
scores already, although a correlation coefficient might be more readily
understood.
Best regards, Darren
----- Original Message -----
From: "Joseph Devlin" <[log in to unmask]>
To: <[log in to unmask]>
Sent: Friday, May 02, 2003 6:04 PM
Subject: Re: [FSL] Higher Level Analysis Thresholding Wisdom Needed
> Hi Darren,
>
> >I am getting clusters that contain 20,000
> > > voxels. For instance:
> > >
> > > Cluster List
> > >
> > > Cluster Index Voxels P -log10(P) Max Z x (mm)
> > y (mm) z (mm)
> > >
> > 2 20330 0 48.6 8.06
> > -30 -92 4
> > > 1 675 0.000699
> > 3.16 5.23 26 20 26
>
> Yep, that's not too surprising. The thresholding defaults in the FEAT
> analysis aren't very helpful (no offense Steve -- I don't think any
default
> would ever be generally helpful across fMRI studies). Setting the
> thresholds appropriately involves some effort.
>
> First, it's important to be clear about what question(s) you want to ask
of
> your data. For initial analyses, I typically just want to get a feel for
> what activity is present in my contrasts. To do this, I generally use
> voxel level statistics (rather than clusters) because I don't care at this
> stage how big my clusters are. I just want to know where the activation
> is. In Feat4 there was a bug in voxel-stats, though, such that it didn't
> produce the table of results so I typically use cluster stats with a
> Z-value of either 2.3 or 3.1 (depending on how lenient I want to be) and a
> p value of 1.0 -- which is equivalent to an uncorrected voxel level
p-value
> of 0.001 for Z=3.1.
>
> The issue in your data seems to come from the nature of a cluster level
> statistic. Briefly, this is based on setting a completely arbitrary
height
> threshold (the Z value, 2.3 is the default in FEAT) and then only
accepting
> clusters above a given size (extent) as significant. THe size is
> determined by the height threshold you chose plus the volume of data and
> its smoothness. Essentially, what you wiill accept as significant is any
> cluster which is larger than you would expect *by chance* when
thresholding
> a gaussian random field at the specified height threshold. Obviously the
> chance clusters will be larger the lower the height threshold. For a low
> height threshold such as 2.3, you'd need HUGE clusters for them to be
> significant. Thus your 20,000 voxel cluster in one case and no clusters
in
> the other. But as you said, this is hardly meaningful. What you probably
> want is to use a higher Z-value (maybe 3.1, maybe higher) and possible
> loosen up the p-value a bit -- especially for data exploration. If you
are
> looking for activation in a specific area, cluster stats may be the wrong
> way to go. Matthew Brett has an excellent web page with some sample
matlab
> code to illustrate voxel and cluster stats
> (www.mrc-cbu.cam.ac.uk/Imaging/randomfields.html).
>
> In my experience, it's well worth working through the differences between
> voxel and cluster statistics (at least conceptually) in some detail
because
> it is crucial to asking the questions one's interested in. I think this
is
> one of the single biggest difficulties in using cluster stats for most
> people but once you crack it, it's easy and you'll never have trouble with
> it again.
>
> Hope this was some help.
>
> Joe
>
> --------------------
> Joseph T. Devlin, Ph. D.
> FMRIB Centre, Dept. of Clinical Neurology
> University of Oxford
> John Radcliffe Hospital
> Headley Way, Headington
> Oxford OX3 9DU
> Phone: 01865 222 738
> Email: [log in to unmask]
>
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