Hi Thomas,
Could you tell me if we have BIS/BAS scores for:
172
176
260
262
265
Thanks,
Greg
On 13-03-20 01:00 , SPM automatic digest system wrote:
> There are 30 messages totaling 3943 lines in this issue.
>
> Topics of the day:
>
> 1. postdoc position in Vision
> 2. SPM 12 batch problems with dependency after realing and unwarp
> 3. Feature request
> 4. Covariate with (almost) zero values (2)
> 5. Strange effects with
> 6. fMRI preprocessing for longitudinal data (3)
> 7. Convert voxel size in a Anatomy mask (2)
> 8. overlay result images (9)
> 9. 12b Batch Preprocess Error
> 10. Colinear covariates (3)
> 11. asking about radius of SVC
> 12. Where is spm_check_version.m? (2)
> 13. Use of source priors on some, but not all participants?
> 14. MNI coordinates of activations map (2)
>
> ----------------------------------------------------------------------
>
> Date: Tue, 19 Mar 2013 01:48:19 +0000
> From: "Dr. Krishna Miyapuram" <[log in to unmask]>
> Subject: postdoc position in Vision
>
> Applications are invited for one postdoctoral position at Indian Institute of Technology Gandhinagar for a period of one year in the area of Computational and Cognitive approaches in Vision with Dr. Krishna Prasad. The primary work would involve developing experimental paradigms for behavioural and neuroimaging (EEG/fMRI) experiments to uncover cognitive aspects of human vision inspired from a computational viewpoint. Future research is expected to cover the area of Biologically inspired computer vision. The postdoc is also expected to contribute to the research and teaching activities of cognitive science group at IIT Gandhinagar, working in a team with other faculty members, and informal guidance for post-graduate/doctoral students.
> Eligibility to apply: Applicants should have a PhD (or Waiting for thesis defense after submission of thesis) in Cognitive science or closely related fields such as Psychology/ Computer Science/ Natural sciences. Previous knowledge and experience of experimental design (behavioural and neuroimaging), programming, statistical data analysis and interpretation of results is essential and should be
> demonstratable through research communications in conferences and journals.
> Applications can be sent via e-mail given below in the prescribed format as given on http://www.iitgn.ac.in/pd-fellowships.htm
> The General terms and conditions of the appointment can also be obtained from the above website.
> Please arrange for two letters of recommendation to be sent to kprasad[at]iitgn.ac.in with the subject: "Application for PDF positions - Candidate Name".
> To receive full consideration, applications should be received by 28 March 2013.
> Queries may be directed to Krishna Prasad [kprasad[at]iitgn.ac.in].
>
> Krishna Prasad Miyapuram (Ph.D. Cantab)
> Assistant Professor (Cognitive Science & Computer Science)
> Indian Institute of Technology Gandhinagar
> VGEC Campus | Chandkheda
>
> ------------------------------
>
> Date: Tue, 19 Mar 2013 13:05:25 +0100
> From: boris suchan ruhr universität
> <[log in to unmask]>
> Subject: SPM 12 batch problems with dependency after realing and unwarp
>
> Dear all,
> I tried tosetup a preprocessing batch with SPM12
> after Realign and unwarp I wanted to start to co-register my T1 image to
> the mean unwarp image.
> An error message appears:
>
> Item 'Images to Write', field 'val': Number of matching files (0) less
> than required (1).
>
> The other error message that pops up says that Dependency is resolved
> but not suitable for this item.
>
> When starting the natch manually at this time by chosing the mean unwarp
> image, everything is fine...
> Has anybody an idea?
> Many thanks
> boris
>
> ------------------------------
>
> Date: Tue, 19 Mar 2013 13:35:23 +0000
> From: Dave Langers <[log in to unmask]>
> Subject: Feature request
>
> Would it be too late to request a feature for the SPM12 release that is
> equally simple as handy?
>
> It is a log-transform of all images in a run according to
> y = 100*ln(x) [+offset]
> The use would be that by transforming all EPI fMRI images during
> preprocessing already, the output of a regression model would
> automagically be expressed as percentage signal change!
> I get the impression that people currently either often forget this
> step, or need to do it afterwards by dividing the estimated betas by the
> baseline or mean image, which is quite cumbersome. Using a log-transform
> this can be taken care of during preprocessing and then be forgotten about.
> I always do it using a script, and I love it; given its generality, it
> would be nice if it becomes a standard function.
> Note that the ImCalc function is not very suitable. First, ImCalc
> produces only one output image but cannot be run on a whole series of
> images; second, all images in a series should be given the same offset,
> which should be suitably scaled to make use of the dynamic range in the
> (integer) representation of images.
>
> The pseudo-code I use (for 16-bit images):
>
> %% LOG-TRANSFORM
> % specify images
> files = {'file1.img', 'file2.img', ..., 'fileN.img'};
> % read representative (i.e. first) image to assess scale
> img = spm_read_vols(spm_vol(files{1}));
> % determine mean tissue signal
> level = mean(img(img > mean(img(:))/10));
> % use 16-bit integer range at 0.01% signal change resolution
> level = level/exp(0.0001*32768/2);
> % apply transform to all images
> for f = 1:length(files)
> hdr = spm_vol(files{f});
> img = spm_read_vols(hdr);
> hdr.pinfo = [0.01; 0; 0];
> hdr.fname = strcat('l', files{f});
> img = 100.0*log(max(img/level, 1.0));
> spm_write_vol(hdr, img);
> end
>
> I am willing to contribute an "spm_logtransform.m" function, if
> necessary, although I can't oversee exactly which other functions need
> to be modified to integrate this feature in the utilities and batch
> functionality.
>
> Best,
> Dave
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> ------------------------------
>
> Date: Tue, 19 Mar 2013 16:08:36 +0100
> From: David Andel <[log in to unmask]>
> Subject: Covariate with (almost) zero values
>
> Hi
>
> I am comparing (H2O) PET images between a placebo and a drug condition.
> In this context, I also want to analyse the correlations of activity
> (perfusion) with psychometric variables. For this I use a covariate
> without interaction (the data of the covariate appear in one line
> beneath each other in the design matrix).
> The problem is that some of those covariates are specific for the drug
> condition, with (almost) zero values in the placebo condition.
> Now, when computing a design containing both the placebo and drug
> images and the covariate for both conditions (the placebo ones being
> almost zero), the result is almost identical with the result obtained
> from computing a design consisting of the placebo condition alone. When
> computing the analogous design consisting of the drug condition alone
> with its covariate the result looks very different.
>
> Why does the placebo condition apparently dominate the drug condition
> in this setup? Is it - as I would assume - due to the near-zero values
> of the covariate in the placebo condition?
>
> Is there any approach to include the differences of the images
> (perfusion) between placebo and drug conditions without distorting the
> analysis by the near-zero covariate in one condition?
>
> Or is it best to just compute the correlations of the perfusion with
> the covariate in the drug condition alone?
>
> Thanks a lot and best regards,
> David
>
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