[pymvpa] RSA in different species

Dear PyMVPA community, I would like to get your feedback for an analysis I'm trying, I think I'm in the right track but I don't want to miss something. I have a block design in which I presented images belonging to 4 categories and I took 6 acquisitions. The thing is that I scanned dogs and human

[pymvpa] Consistently bad accuracy?

Dear PyMVPA community, I'm doing classification in ROI's, I'm performing a simple 2 way classification using LSVM, and a leave-one-run-out cross-validation on 4 acquisitions. On some ROI's, I get a good accuracy for the number of participants (60%), but in others I get consistently bad accuracy (3

Re: [pymvpa] Consistently bad accuracy?

No, it is balanced. It has the same number of observations for each class. On Mon, Nov 26, 2018 at 12:52 PM Kaustubh Patil wrote: > Just for clarification. > > Is that data imbalanced, i.e. many more observations from one class? > > Best, > Kaustubh > > On Mon, Nov 2

Re: [pymvpa] Consistently bad accuracy?

ing is not right in data handling/evaluation. > > Best > > On Mon, Nov 26, 2018 at 1:27 PM Raúl Hernández > wrote: > >> No, it is balanced. It has the same number of observations for each class. >> >> On Mon, Nov 26, 2018 at 12:52 PM Kaustubh Patil >> wrote

Re: [pymvpa] Consistently bad accuracy?

, not on the > cross-validation folds within each person. > > Jo > > > On 11/26/2018 7:05 AM, Raúl Hernández wrote: > > I also consider that option, but when I try the very same thing with a > > different, region (not related to the task). I get accuracies of 50%. So >

Re: [pymvpa] Consistently bad accuracy?

rmalization/detrending problem. > I used to have below-chance accuracy in across-subject analyses, but this > is not your case! > > Bests, > R > > On Mon, 26 Nov 2018 at 16:29, Raúl Hernández wrote: > >> Thank you for the link, I will look into it carefully. &

Re: [pymvpa] Difficulty importing PyMVPA tutorial datasets

Check the path in a terminal. Copy and paste the path you get from the error, do 'cd' to it. cd ./haxby2001/sub001/masks/orig/ If you get no error, try it in Python. Regards, El mar., 18 dic. 2018 19:12, Yaroslav O Halchenko escribió: > > On Mon, 17 Dec 2018, Lyam Bailey wrote: > > >Dear

Re: [pymvpa] Searchligh SVM on fMRI Beta Values in PyMVPA

Hi, For sure there is a better approach, but I also had the same issue. What I ended up doing is pretending that each beta map was a volume of a raw fMRI acquisition. So I calculated the beta maps and then used the FSL command fslmerge to concatenate every beta map to analyze. Then I put the resul

[pymvpa] Noise normalization

Dear PyMVPA community, I'm a bit confused with noise normalization and I was hoping someone can clarify it for me. Walther et al., (2016) mentions that noise normalization is an important step in multivariate fMRI. For what I understand, if I Z-score each voxel, I'm performing a univariate noise n

Re: [pymvpa] Noise normalization

Thank you!, this is very helpful and clear :) Regards, Raul On Wed, Apr 1, 2020 at 6:25 PM wrote: > > On Wed, 01 Apr 2020, Raúl Hernández wrote: > > >Dear PyMVPA community, > >I'm a bit confused with noise normalization and I was hoping someone > can >