Hi everyone,
I am a new user of TDT. I think TDT is very useful! I really appreciate the authors.
Now I’m trying to perform RSA-GLM, but it does not work well. Please let me know what is wrong…
I would like to obtain whole-brain rsa_beta.nii files (3 behavioral measures) against neural dissimilarity matrix across each trial for each participant.
I think what I want to do is similar to the previous post by Ryuhei （https://neurostars.org/t/tdt-how-to-perform-rsa-glm-and-obtain-beta-values/7039）. I followed his post to the setting, but it did not work.
My current settings are…
trial_number =36 ;
cfg.files.chunk=ones(trial_number,1); %%%because non cross validated analysis
cfg.files.components.matrix = {DistA,DistB,DistC,intercept}; %%three different RDMs and intercept(consists only of ones)
cfg.files.components.index = (1:numel(DistC))’;
cfg.files.components.get_inv=1;
cfg.files.name=[‘G:/GLM_n183/sub’ num2str(s) ‘/trial36CF_subspace/beta_0001.nii’
‘G:/GLM_n183/sub’ num2str(s) ‘/trial36CF_subspace/beta_0002.nii’
…
‘G:/GLM_n183/sub’ num2str(s) ‘/trial36CF_subspace/beta_0036.nii’];
cfg.decoding.software=‘similarity’;
cfg.decoding.method=‘classification’;
cfg.decoding.train.classification.model_parameters=‘zcorr’;
cfg.results.output = {‘rsa_beta’,‘other’};
cfg.design=make_design_rsa(cfg);
cfg.design.unbalanced_data = ‘ok’
cfg.searchlight.unit = ‘mm’;
cfg.searchlight.radius = 3;
results = decoding(cfg);
TDT version 3.999.
This script seemed to successfully run but it was not true. After running the script, I could get the res_other.mat consisting of output (searchlight_number x 1 cells, each cell had a trial_number x trial_number size matrix) and
res_rsa_beta.mat consisting of all NaN .
I could not obtain the res_rsa_beta.nii.
My first question is
why the values in the res_rsa_beta.mat are all NaN? What should I do?
Second question is
can I obtain the 3 different res_rsa_beta.nii files usind TDT?
I would appreciate your advice.
Thank you.
Toshiko