Dear Martin
Greetings. The problem is in spm_spm_Bayes.m when one uses Matlab R14 or
greater. If you go to approx lines 294 and 301 this code :
tmp = tmp + NaN*(~tmp);
produces the NaN's.
I have updated this in the FIL version of the file and hopefully it will
make its way to wider distribution at a future update (or it may have
already).
In any case replace the above with this line in both places.
tmp(~tmp) = NaN;
You will have to re-estimate the dataset, but then all should be fine.
Attached is also an updated version of spm_spm_Bayes.m
Regards,
Darren
> -----Original Message-----
> From: SPM (Statistical Parametric Mapping)
> [mailto:[log in to unmask]] On Behalf Of Martin Kronbichler
> Sent: Tuesday, January 30, 2007 4:12 AM
> To: [log in to unmask]
> Subject: [SPM] spm5 bayesian problems
>
> Dear SPM Experts,
>
> i have recently started to use variational bayesian first
> level analyses for analysing presurgical language and motor
> experiments because i had the feeling that the posterior
> probalities are easier to communicate and easier to
> understand (especially when making inferences on how likely
> increased activatity for speech or motor is in regions near
> to the lesions).
> Generally, the bayesian analyses worked extremly well.
> However i have stumpled across a strange result i do not
> understand when analysing a block-design language experiment
> (2 blockedc onditions: simple tones vs. auditory words
> presented in 2 sessions). Whatever effect size threshold
> (even completerly unrealistic values like > 1000) or
> posterior probality i choose the PPM shows the whole brains
> as exhibiting posterior prob. of 1 (i.e. the whole brain is
> "activated"). SPM5 displays the following error message when
> is estimate the contrasts:
>
> spm{P} image 1 : ...computing
> Warning: Returning NaN for out of range arguments
> > In /opt/spm5/spm_Ncdf.m at line 80
> In /opt/spm5/spm_contrasts.m at line 214
> In /opt/spm5/spm_getSPM.m at line 474
> In /opt/spm5/spm_results_ui.m at line 264
> ...written spmP_0001.img
> SPM computation :
> ...initialising
> SPM computation :
> ...done
> SPM computation :
> ...done
>
> I have tried to remove and add motion parameters, analyse
> only one session, use different basis functions etc... but
> whatever i do the problem persits.
> Inspection of the files generated by SPM5 shows that the beta
> and SDbeta images look reasonable. The spmP and con_SD images
> however contain only NaNs..
> I might add that a conventional analysis results in
> stastically highly signficant voxels...
> Anybody has any idea what is causing this problem?
>
> Greetings from Salzburg,
>
> Martin
>
>
> Martin Kronbichler, M.Sc.
> ---------------------------------------------
> Department of Psychology
>
>
> Center for Neurocognitive Research
> University of Salzburg
>
> Hellbrunnerstr.34, A 5020 Salzburg, Austria
> e-mail:[log in to unmask]
> Tel.:+43/(0)/662/8044-5162
>
> Fax:+43/(0)/662/8044-5126
>
> ---------------------------------------------
> Department of Neurology
> Center for Neurocognitive Research Christian-Doppler Clinic,
> Paracelsus Private Medical University Ignaz Harrerstr.79, A
> 5020 Salzburg, Austria e-mail:[log in to unmask]
> Tel.:+43/(0)/662/4483-3966
> ---------------------------------------------
>
