Run GLMstandard on dataset 1
Contents
Download dataset 1 (if necessary)
DNBdownloaddata(1);
Downloading dataset01.mat (please be patient).
Downloading is done!
Load dataset 1
dataset = DNBloaddata(1,'all');
Inspect contents of dataset 1
dataset
dataset =
stimdur: 3
tr: 1.3238
motionparameters: {1x10 cell}
data: {1x10 cell}
design: {1x10 cell}
voxelsize: [2.5000 2.5000 2.5000]
runsets: [1 1 2 2 3 3 4 4 5 5]
runtypes: [1 2 1 2 1 2 1 2 1 2]
hrf: [40x5 single]
meanvol: [64x64x21 single]
brainmask: [64x64x21 logical]
dataset.data
ans =
Columns 1 through 4
[4-D single] [4-D single] [4-D single] [4-D single]
Columns 5 through 8
[4-D single] [4-D single] [4-D single] [4-D single]
Columns 9 through 10
[4-D single] [4-D single]
size(dataset.data{1})
ans =
64 64 21 265
dataset.design
ans =
Columns 1 through 4
[265x69 double] [265x69 double] [265x69 double] [265x69 double]
Columns 5 through 8
[265x69 double] [265x69 double] [265x69 double] [265x69 double]
Columns 9 through 10
[265x69 double] [265x69 double]
dataset.motionparameters
ans =
Columns 1 through 4
[265x6 double] [265x6 double] [265x6 double] [265x6 double]
Columns 5 through 8
[265x6 double] [265x6 double] [265x6 double] [265x6 double]
Columns 9 through 10
[265x6 double] [265x6 double]
Run GLMstandard (GLMdenoise without noise regressors) on dataset 1
DNBrun(1,'GLMstandard');
*** DNBevaluatemethod: evaluating method DNBmethod_GLMstandard on dataset 1. ***
*** DNBevaluatemethod: performing cross-validation iteration 1 of 5. ***
*** GLMdenoisedata: performing full fit to estimate global HRF. ***
fitting model...done.
preparing output...done.
computing SNR...done.
*** GLMdenoisedata: performing cross-validation to determine R^2 values. ***
cross-validating model........done.
computing model fits...done.
computing R^2...done.
computing SNR...done.
*** GLMdenoisedata: determining noise pool. ***
*** GLMdenoisedata: calculating global noise regressors. ***
*** GLMdenoisedata: selected number of PCs is 0. ***
*** GLMdenoisedata: fitting final model (no denoising, for comparison purposes). ***
bootstrapping model....................done.
preparing output...done.
computing model fits...done.
computing R^2...done.
computing SNR...done.
*** GLMdenoisedata: fitting final model (with denoising). ***
bootstrapping model....................done.
preparing output...done.
computing model fits...done.
computing R^2...done.
computing SNR...done.
*** GLMdenoisedata: calculating denoised data and PC weights. ***
*** GLMdenoisedata: generating figures. ***
*** DNBevaluatemethod: performing cross-validation iteration 2 of 5. ***
*** GLMdenoisedata: performing full fit to estimate global HRF. ***
fitting model...done.
preparing output...done.
computing SNR...done.
*** GLMdenoisedata: performing cross-validation to determine R^2 values. ***
cross-validating model........done.
computing model fits...done.
computing R^2...done.
computing SNR...done.
*** GLMdenoisedata: determining noise pool. ***
*** GLMdenoisedata: calculating global noise regressors. ***
*** GLMdenoisedata: selected number of PCs is 0. ***
*** GLMdenoisedata: fitting final model (no denoising, for comparison purposes). ***
bootstrapping model....................done.
preparing output...done.
computing model fits...done.
computing R^2...done.
computing SNR...done.
*** GLMdenoisedata: fitting final model (with denoising). ***
bootstrapping model....................done.
preparing output...done.
computing model fits...done.
computing R^2...done.
computing SNR...done.
*** GLMdenoisedata: calculating denoised data and PC weights. ***
*** GLMdenoisedata: generating figures. ***
*** DNBevaluatemethod: performing cross-validation iteration 3 of 5. ***
*** GLMdenoisedata: performing full fit to estimate global HRF. ***
fitting model...done.
preparing output...done.
computing SNR...done.
*** GLMdenoisedata: performing cross-validation to determine R^2 values. ***
cross-validating model........done.
computing model fits...done.
computing R^2...done.
computing SNR...done.
*** GLMdenoisedata: determining noise pool. ***
*** GLMdenoisedata: calculating global noise regressors. ***
*** GLMdenoisedata: selected number of PCs is 0. ***
*** GLMdenoisedata: fitting final model (no denoising, for comparison purposes). ***
bootstrapping model....................done.
preparing output...done.
computing model fits...done.
computing R^2...done.
computing SNR...done.
*** GLMdenoisedata: fitting final model (with denoising). ***
bootstrapping model....................done.
preparing output...done.
computing model fits...done.
computing R^2...done.
computing SNR...done.
*** GLMdenoisedata: calculating denoised data and PC weights. ***
*** GLMdenoisedata: generating figures. ***
*** DNBevaluatemethod: performing cross-validation iteration 4 of 5. ***
*** GLMdenoisedata: performing full fit to estimate global HRF. ***
fitting model...done.
preparing output...done.
computing SNR...done.
*** GLMdenoisedata: performing cross-validation to determine R^2 values. ***
cross-validating model........done.
computing model fits...done.
computing R^2...done.
computing SNR...done.
*** GLMdenoisedata: determining noise pool. ***
*** GLMdenoisedata: calculating global noise regressors. ***
*** GLMdenoisedata: selected number of PCs is 0. ***
*** GLMdenoisedata: fitting final model (no denoising, for comparison purposes). ***
bootstrapping model....................done.
preparing output...done.
computing model fits...done.
computing R^2...done.
computing SNR...done.
*** GLMdenoisedata: fitting final model (with denoising). ***
bootstrapping model....................done.
preparing output...done.
computing model fits...done.
computing R^2...done.
computing SNR...done.
*** GLMdenoisedata: calculating denoised data and PC weights. ***
*** GLMdenoisedata: generating figures. ***
*** DNBevaluatemethod: performing cross-validation iteration 5 of 5. ***
*** GLMdenoisedata: performing full fit to estimate global HRF. ***
fitting model...done.
preparing output...done.
computing SNR...done.
*** GLMdenoisedata: performing cross-validation to determine R^2 values. ***
cross-validating model........done.
computing model fits...done.
computing R^2...done.
computing SNR...done.
*** GLMdenoisedata: determining noise pool. ***
*** GLMdenoisedata: calculating global noise regressors. ***
*** GLMdenoisedata: selected number of PCs is 0. ***
*** GLMdenoisedata: fitting final model (no denoising, for comparison purposes). ***
bootstrapping model....................done.
preparing output...done.
computing model fits...done.
computing R^2...done.
computing SNR...done.
*** GLMdenoisedata: fitting final model (with denoising). ***
bootstrapping model....................done.
preparing output...done.
computing model fits...done.
computing R^2...done.
computing SNR...done.
*** GLMdenoisedata: calculating denoised data and PC weights. ***
*** GLMdenoisedata: generating figures. ***
*** DNBevaluatemethod: evaluating predictions against the data. ***
*** DNBevaluatemethod: complete! ***
Inspect the result
a1 = load(strrep(which('DNBrun'),'DNBrun.m',fullfile('DNBresults','GLMstandard_dataset01.mat')));
figure;
imagesc(makeimagestack(signedarraypower(a1.performance/100,0.5),[0 1]),[0 1]);
colormap(hot);
