that's right, if you only have a contrast for the first regressor, then
you can just use the Cbeta_0001.img.
There is no spatial prior for the 2nd level, as I understand it. I'll
just paste here what Will Penny wrote some time ago:
2nd level PPMs use a prior over the regression coefficients, beta, with
zero mean and (co)variance Cb. The quantity SPM.PPM.Cb is an empirical
estimate of Cb. The rest of the formula computes how much of this
variance projects onto the contrast you are testing."
"The procedure here is to Specify a 2nd level model - t-tests, ANOVA etc
- then estimate it with the Classical option
(you can also play with some contrasts here). Then estimate the model
again using the Bayesian 2nd level option and you can create parameter
inference and model comparison maps  by specifying contrasts in the
Its perfectly valid to compare parameters to a threshold of zero."
I hope this helps.
On 09.03.2015 13:46, Anders Eklund wrote:
> Dear Glad,
> since I'm interested only in the first regressor, I assume that a
> contrast of [1 0 0 0 0 0 0 0] will give a file con_0001.img that is
> identical to Cbeta_0001.img ?
> No I did not smooth the fMRI data, since SPM uses a spatial prior. I,
> however, assumed that a spatial prior was also used for the group
> analysis, and that the posterior variance was also included.
> - Anders
> 2015-03-09 10:08 GMT+01:00 Paul Glad Mihai
> <[log in to unmask]
> <mailto:[log in to unmask]>>:
> Dear Anders,
> Why don't you calculate the contrasts on the 1st level? You will then
> get an idea of what the activation looks like. I hope you didn't smooth
> your EPIs prior to the 1st level Bayesian analysis.
> After you have your 1st level contrasts you will have to smooth them in
> order to increase the chance of overlap between subjects. The smoothing
> factor depends on what you want to look at. Here's a paper about
> Ball, T., Breckel, T. P. K., Mutschler, I., Aertsen, A.,
> Schulze-Bonhage, A., Hennig, J., & Speck, O. (2011). Variability of
> fMRI-response patterns at different spatial observation scales. Human
> Brain Mapping, 1171(January 2011), 1155–1171. doi:10.1002/hbm.21274
> At the 2nd level you will take the smoothed con images, do a classical
> estimation and then do a Bayesian estimation. I usually use the batch
> editor and estimate on the prior dependency for the classical way, then
> create another dependency from the classical to do the Bayesian
> estimation. The standard deviation from each subject is not used in the
> 2nd level analysis, since you only plug in the contrasts.
> I hope this helps.
> On 08.03.2015 10:54, Anders Eklund wrote:
> > Dear SPM users,
> > I'm trying to do a Bayesian group analysis in SPM8. I have looked
> at the
> > SPM8 manual but it is still a bit unclear to me.
> > I have gone through each subject with a Bayesian first level analysis,
> > so I have Cbeta_* and SD_beta* for all regressors. I would like to
> > obtain a group level PPM of the first beta weight being larger
> than 0. I
> > used "Specify 2nd-level" and selected the Cbeta_0001.img for each
> > subject. I then first do a classical estimation (which seems to be
> > required prior to a 2nd level Bayesian estimation) and then do the
> > Bayesian 2nd-level estimation. Does this procedure seem correct?
> > If the procedure is correct, is the standard deviation from each
> > subject, i.e. SDbeta_0001.img, used in the group analysis, or is only
> > the posterior mean of each subject used?
> > Regards,
> > Anders
> P. Glad MIHAI, M.Sc. Biomedical Physics
> Functional Imaging | University Clinic Greifswald
> Walther-Rathenau-Straße 46 | 17475 Greifswald | Germany
> Tel: +49 3834 86 69 44 <tel:%2B49%203834%2086%2069%2044> | Fax: +49
> 3834 86 68 98 <tel:%2B49%203834%2086%2068%2098>
> www.baltic-imaging-center.de <http://www.baltic-imaging-center.de>
> Anders Eklund, PhD
P. Glad MIHAI, M.Sc. Biomedical Physics
Functional Imaging | University Clinic Greifswald
Walther-Rathenau-Straße 46 | 17475 Greifswald | Germany
Tel: +49 3834 86 69 44 | Fax: +49 3834 86 68 98