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