Error in Multilevel mediation fMRI walkthrough : Woo_2015_PlosBio_BMRK3_pain_6levels dataset example
dylansutterlin opened this issue · 1 comments
Hi,
I was going through the mediation_brain_multilevel_walkthrough1.html tutorial to run multi-level mediation analysis. While trying to figure out how to format my data to run the mediation_brain_multilevel function , I got stuck running the example code. I entered exactly the first 3 code blocks. I am working on matlab2023a. I also reproduced the error on a collegue's computer.
`%% canlab example
metadata_file = which('bmrk3_6levels_metadata.mat');
if isempty(metadata_file)
disp('You need the dataset Woo_2015_PlosBio_BMRK3_pain_6levels on your Matlab path.')
disp('This is in the CANlab Core toolbox.')
error('Check path and files.')
end
load(metadata_file);
% Re-find local path names for brain images
M = single_trial_image_names;
dir_old = fileparts(M{1});
dir_new = fileparts(metadata_file);
for i = 1:length(M), M{i} = strrep(M{i}, dir_old, dir_new); end
single_trial_image_names = M;
X = temperatures;
Y = ratings;
whos X Y single_trial_image_names
mkdir mediation_results
cd mediation_results
SETUP.mask = which('gray_matter_mask.nii');
SETUP.preprocX = 0;
SETUP.preprocY = 0;
SETUP.preprocM = 0;
% mediation_brain_multilevel(X, Y, M, [other inputs])
mediation_brain_multilevel(temperatures, ratings, single_trial_image_names, SETUP);
`
Full output !
`Search for mediators
Warning! Unrecognized field in SETUPions structure SETUP.
Warning! Unrecognized field in SETUPions structure SETUP.
First-level covariates: None
Second-level moderators: None
Found mask: /home/dsutterlin/projects/genPain/Toolboxes/CanlabCore/CanlabCore/canlab_canonical_brains/Canonical_brains_surfaces/gray_matter_mask.nii
Preparing data.
Mask info:
Dimensions: 79 95 68
Voxels in mask: 195612
Mapping all input data volumes to memory
Subject 1, 1 images.
Subject 2, 1 images.
Subject 3, 1 images.
Subject 4, 1 images.
Subject 5, 1 images.
Subject 6, 1 images.
Subject 7, 1 images.
Subject 8, 1 images.
Subject 9, 1 images.
Subject 10, 1 images.
Subject 11, 1 images.
Subject 12, 1 images.
Subject 13, 1 images.
Subject 14, 1 images.
Subject 15, 1 images.
Subject 16, 1 images.
Subject 17, 1 images.
Subject 18, 1 images.
Subject 19, 1 images.
Subject 20, 1 images.
Subject 21, 1 images.
Subject 22, 1 images.
Subject 23, 1 images.
Subject 24, 1 images.
Subject 25, 1 images.
Subject 26, 1 images.
Subject 27, 1 images.
Subject 28, 1 images.
Subject 29, 1 images.
Subject 30, 1 images.
Subject 31, 1 images.
Subject 32, 1 images.
Subject 33, 1 images.
Preprocessing is Off
...Creating: X-M_effect
...Creating: M-Y_effect
...Creating: X-Y_direct_effect
...Creating: X-Y_total_effect
...Creating: X-M-Y_effect
...Creating: X-M_ste
...Creating: M-Y_ste
...Creating: X-Y_direct_ste
...Creating: X-Y_total_ste
...Creating: X-M-Y_ste
...Creating: X-M_pvals
...Creating: M-Y_pvals
...Creating: X-Y_direct_pvals
...Creating: X-Y_total_pvals
...Creating: X-M-Y_pvals
...Creating: X-M_indiv_effect
...Creating: M-Y_indiv_effect
...Creating: X-Y_direct_indiv_effect
...Creating: X-Y_total_indiv_effect
...Creating: X-M-Y_indiv_effect
...Creating: X-M_indiv_ste
...Creating: M-Y_indiv_ste
...Creating: X-Y_direct_indiv_ste
...Creating: X-Y_total_indiv_ste
...Creating: X-M-Y_indiv_ste
Outputs: 25 images
X-M_effect.img - 1 volume(s)
M-Y_effect.img - 1 volume(s)
X-Y_direct_effect.img - 1 volume(s)
X-Y_total_effect.img - 1 volume(s)
X-M-Y_effect.img - 1 volume(s)
X-M_ste.img - 1 volume(s)
M-Y_ste.img - 1 volume(s)
X-Y_direct_ste.img - 1 volume(s)
X-Y_total_ste.img - 1 volume(s)
X-M-Y_ste.img - 1 volume(s)
X-M_pvals.img - 1 volume(s)
M-Y_pvals.img - 1 volume(s)
X-Y_direct_pvals.img - 1 volume(s)
X-Y_total_pvals.img - 1 volume(s)
X-M-Y_pvals.img - 1 volume(s)
X-M_indiv_effect.img - 33 volume(s)
M-Y_indiv_effect.img - 33 volume(s)
X-Y_direct_indiv_effect.img - 33 volume(s)
X-Y_total_indiv_effect.img - 33 volume(s)
X-M-Y_indiv_effect.img - 33 volume(s)
X-M_indiv_ste.img - 1 volume(s)
M-Y_indiv_ste.img - 1 volume(s)
X-Y_direct_indiv_ste.img - 1 volume(s)
X-Y_total_indiv_ste.img - 1 volume(s)
X-M-Y_indiv_ste.img - 1 volume(s)
This will be evaluated at each voxel:
[out1,out2,out3,out4,out5,out6,out7,out8,out9,out10,out11,out12,out13,out14,out15,out16,out17,out18,out19,out20,out21,out22,out23,out24,out25] = fhandle(Y);
Slice 1, 1005 in-mask voxels
Loading and preprocessing for this slice for subject: Summary of missing or bad voxels:
Dataset 1: 0 voxels have no data, and 0 voxels have missing data.
Dataset 2: 0 voxels have no data, and 0 voxels have missing data.
Dataset 3: 0 voxels have no data, and 0 voxels have missing data.
Dataset 4: 0 voxels have no data, and 0 voxels have missing data.
Dataset 5: 0 voxels have no data, and 0 voxels have missing data.
Dataset 6: 0 voxels have no data, and 0 voxels have missing data.
Dataset 7: 0 voxels have no data, and 0 voxels have missing data.
Dataset 8: 0 voxels have no data, and 0 voxels have missing data.
Dataset 9: 0 voxels have no data, and 0 voxels have missing data.
Dataset 10: 0 voxels have no data, and 0 voxels have missing data.
Dataset 11: 0 voxels have no data, and 0 voxels have missing data.
Dataset 12: 0 voxels have no data, and 0 voxels have missing data.
Dataset 13: 0 voxels have no data, and 0 voxels have missing data.
Dataset 14: 0 voxels have no data, and 0 voxels have missing data.
Dataset 15: 0 voxels have no data, and 0 voxels have missing data.
Dataset 16: 0 voxels have no data, and 0 voxels have missing data.
Dataset 17: 0 voxels have no data, and 0 voxels have missing data.
Dataset 18: 0 voxels have no data, and 0 voxels have missing data.
Dataset 19: 0 voxels have no data, and 0 voxels have missing data.
Dataset 20: 0 voxels have no data, and 0 voxels have missing data.
Dataset 21: 0 voxels have no data, and 0 voxels have missing data.
Dataset 22: 0 voxels have no data, and 0 voxels have missing data.
Dataset 23: 0 voxels have no data, and 0 voxels have missing data.
Dataset 24: 0 voxels have no data, and 0 voxels have missing data.
Dataset 25: 0 voxels have no data, and 0 voxels have missing data.
Dataset 26: 0 voxels have no data, and 0 voxels have missing data.
Dataset 27: 0 voxels have no data, and 0 voxels have missing data.
Dataset 28: 0 voxels have no data, and 0 voxels have missing data.
Dataset 29: 0 voxels have no data, and 0 voxels have missing data.
Dataset 30: 0 voxels have no data, and 0 voxels have missing data.
Dataset 31: 0 voxels have no data, and 0 voxels have missing data.
Dataset 32: 0 voxels have no data, and 0 voxels have missing data.
Dataset 33: 0 voxels have no data, and 0 voxels have missing data.
Elapsed: 0 s
Analysis ...Error using tcdf
Degrees of freedom must be positive.
Error in mediation>get_ols_stats (line 1514)
stats.p = min(1, (2 .* (1 - tcdf(abs(stats.t), stats.df))));
Error in mediation (line 305)
stats = get_ols_stats(paths(i,:) , sterrs(i,:), n(i), num_additionalM); % setup dummy stats structure
Error in mediation_brain_multilev_wrapper (line 28)
[indiv_paths, toplevelstats, firstlevelstats] = mediation(X, Y, M, varargin{:});
Error in mediation_brain_multilevel>@(M)mediation_brain_multilev_wrapper(X,Y,M,varargin{:}) (line 110)
fhandle = @(M) mediation_brain_multilev_wrapper(X, Y, M, varargin{:});
Error in image_eval_function_multisubj/analyze_slice_data (line 333)
eval(fstr)
Error in image_eval_function_multisubj (line 272)
sliceoutputs = analyze_slice_data;
Error in mediation_brain_multilevel (line 181)
image_eval_function_multisubj(M, fhandle, 'mask', SETUP.mask, 'preprochandle', preprochandle, 'outnames', SETUP.outputnames, 'start', SETUP.startslice);
`
See attached image for only the error message. Thanks for any support/suggrestions!
Best
Turns out that you need to remove the SPM(12 in my case)/external folder and its subfolder from path. This fixed the issue.