On 07/10/2013 01:29 PM, Joseph Dien wrote:Sorry, not following what you are suggesting?Sorry, it had been a while since I read that paper. I did not know that
I want the second derivative for calculating the Calhoun et al 2004
derivative boost measure.
My understanding is that to the extent that the BOLD signal deviates
from the canonical hrf, the amplitude of the primary regressor will be
attenuated and the variance will instead end up in the first and
second derivatives (to the extent that they are able to accommodate
the divergence). By using a Calhoun measure that incorporates both
the first and second derivatives, in principle I'll have a BOLD
measure that is more robust to deviations from the canonical hrf.
they had a formulation that included the 2nd derivative.I don't know how much it will hurt the power. You'd have to look at the
However, if the way FSFAST is calculating the second derivative
regressor is resulting in loss of statistical power due to shared
variance with the primary regressor, then it would be best to just not
include it at all in the estimation step.
efficiency.
doug
On Jul 10, 2013, at 1:21 PM, Douglas N Greve
<greve@nmr.mgh.harvard.edu <mailto:greve@nmr.mgh.harvard.edu>> wrote:
Why not just create a new volume and then compute contrasts from the new
volume? What you are suggesting will work I think, but it leaves me a
little nervous. The p-values will be meaningless.
As for the 2nd derivative, I think it must be a numerical issue (it is
not computed analytically). Why do you need the 2nd derivative?
doug
On 07/10/2013 12:47 PM, Joseph Dien wrote:I'm thinking of generating a modified beta.nii.gz file where the
primary betas have been replaced with the Calhoun et al (2004)
derivative boost measure. What do you think? Also, please note my
question below about the second derivative as it is causing me concern
about my analysis. Thanks!
Joe
On Jul 10, 2013, at 12:39 PM, Douglas N Greve
<greve@NMR.MGH.HARVARD.EDU <mailto:greve@NMR.MGH.HARVARD.EDU>
<mailto:greve@NMR.MGH.HARVARD.EDU>> wrote:
I think that would work. You would need to change the time stamps
on the
.mat file in the analysis folder. When you re-run selxavg3-sess, it
will
see that the .mat files are newer than the beta and regenerate the
contrasts. But what are you planning to do the the beta file? It sounds
like a potentially bad idea
doug
On 07/09/2013 10:26 PM, Joseph Dien wrote:It looks as though selxavg3-sess generates the contrast analyses at
the same time as the beta weights. Would it be possible to
run selxavg3-sess once to obtain the beta weights, modify the
beta.nii.gz file, and then rerun selxavg3-sess to obtain the contrast
statistics using the modified beta weights?
Joe
On Jul 9, 2013, at 5:08 PM, Joseph Dien <jdien07@mac.com
<mailto:jdien07@mac.com>
<mailto:jdien07@mac.com>
<mailto:jdien07@mac.com>> wrote:I tried correlations and the 2nd derivative is definitely not
orthogonal.corrcoef([X(1:207,4) X(1:207,5) X(1:207,6)])
ans =
1.0000 -0.0000 -0.5427
-0.0000 1.0000 -0.0298
-0.5427 -0.0298 1.0000
I looked at the regressors that SPM generates for the same data:
ans =
1.0000 0.0436 0.1740
0.0436 1.0000 -0.0226
0.1740 -0.0226 1.0000
The first derivative is not as orthogonal but the second derivative
was much more orthogonal.
Does this have to do with what you noted below about how the second
derivative is being calculated?
So does this mean I should avoid the spmhrf 2 option entirely to
avoid loss of statistical power?
Thanks for the help!
Joe
On Jul 9, 2013, at 4:34 PM, Joseph Dien <jdien07@mac.com
<mailto:jdien07@mac.com>
<mailto:jdien07@mac.com>
<mailto:jdien07@mac.com>> wrote:Thanks for the quick response! So if I wanted to use the Calhoun
2004 approach, I should be able to use the Steffener 2010 correction
to address the violation of the assumption that the regressors were
standardized and generate a new beta.nii.gz file where the primary
beta values have been replaced with the Calhoun 2004 measure. Can I
assume the three regressors are more or less orthogonal? I got
non-zero numbers when I tried to test the assumption in the Xtmp.X
variable
sum(X(1:207,4).*X(1:207,5))
but not hugely non-zero so maybe just rounding errors?
On Jul 9, 2013, at 4:16 PM, Douglas N Greve
<greve@NMR.MGH.HARVARD.EDU <mailto:greve@NMR.MGH.HARVARD.EDU>
<mailto:greve@NMR.MGH.HARVARD.EDU>
<mailto:greve@NMR.MGH.HARVARD.EDU>> wrote:
On 07/09/2013 04:11 PM, Joseph Dien wrote:Hi,This is what happens. If you want to use the derivatives, then you
I have a question about how mkcontrast-sess works. I ran an
analysis using the mkanalysis-sess option spmhrf 2 so there are
three
regressors for each predictor, the primary, the latency, and the
dispersion. When specifying the contrast weights for
mkcontrast-sess,
the documentation indicates that they are specified in terms
of the
conditions as numbered in the paradigm file, not the individual
regressors. Furthermore there only appears to be one contrast
value
output for each contrast, not three.
How are the three regressors being handled? I can think of
several
scenarios:
1) the contrast weights are not actually in terms of
conditions (the
documentation is incorrect), they are actually in terms of the
regressors (so contrasting conditions 1 and 2 could be specified
as -a
1 -a 2 -a 3 -c 4 -c 5 -c 6).
2) the latency and dispersion regressors are being ignored (a
common
practice). The contrast weights should therefore be specified as
-a 1
-c 2.
need
to spec -setwdelay. When you run the command, it will prompt you
for 3
values to use. If you spec 1 0 0, then it will be the same as the
default. If you want to test only the first derivative, then you
would
spec 0 1 0. Note that the 3rd regressor is the 2nd derivative wrt
time,
not the first derivative wrt the dispersion parameter. You
cannot get
the Calhoun 2004 value using a contrast (it is non-linear).
doug
3) The Calhoun et al (2004) approach is being used to combine the
three regressors into a "derivative boost" amplitude
measure. The contrast weights should therefore be specified as -a
1 -c 2.
Thanks for any help you can give me!
Joe
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http://joedien.com//
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