Dear experts:
The mask of my preprocessed data is a .nii file, whose paramter is 617361 .but the maskind that is generated by my data during ICA has 57549 voxels, which means there are 57549 values in each IC. Now I operate these IC(compSet.ic in ica_br.mat) to generate a new matix which has 57549 elements, and I want to create a .nii file based on it. How canI do this? I know this step need value of each voxel and a mask, but where can I find the mask?
By the way, I find a function in the Group ICA package, could I use this ?
function [tc, spatial_maps] = icatb_dual_regress(y, X)
%% Use dual regression approach to compute the spatial maps and time
% courses
%
% Inputs:
% 1. y - Observations in columns (Voxels by time points)
% 2. X - design matrix (Voxels by components)
%
% Outputs:
% 1. tc - Time courses (Timepoints by components)
% 2. spatial_maps - Spatial maps (Components by voxels)
%
%% First step. Fit model matrix to the data to get time courses.
X = icatb_remove_mean(X);
Hello, I have a question about the templates in icatb/icatb_templates/RSN.zip. I'd like to know the basics of the way to distinguish those networks(like a paper, maybe?), and which space is used? When I display it in an MNI space, I find there are some parts out of the brain. Is it defined in a Talairach space?
Looking forward to your reply,thank you!
Best regards
If you would like to refer to this comment somewhere else in this project, copy and paste the following link:
Dear experts:
The mask of my preprocessed data is a .nii file, whose paramter is 617361 .but the maskind that is generated by my data during ICA has 57549 voxels, which means there are 57549 values in each IC. Now I operate these IC(compSet.ic in ica_br.mat) to generate a new matix which has 57549 elements, and I want to create a .nii file based on it. How canI do this? I know this step need value of each voxel and a mask, but where can I find the mask?
By the way, I find a function in the Group ICA package, could I use this ?
function [tc, spatial_maps] = icatb_dual_regress(y, X)
%% Use dual regression approach to compute the spatial maps and time
% courses
%
% Inputs:
% 1. y - Observations in columns (Voxels by time points)
% 2. X - design matrix (Voxels by components)
%
% Outputs:
% 1. tc - Time courses (Timepoints by components)
% 2. spatial_maps - Spatial maps (Components by voxels)
%
%% First step. Fit model matrix to the data to get time courses.
X = icatb_remove_mean(X);
tc = pinv(X)*icatb_remove_mean(y);
tc = tc';
clear X;
% Store mean of timecourses
mean_tc = mean(tc);
% Remove mean of timecourse
tc = icatb_remove_mean(tc);
Dear experts:
Hello, I have a question about the templates in icatb/icatb_templates/RSN.zip. I'd like to know the basics of the way to distinguish those networks(like a paper, maybe?), and which space is used? When I display it in an MNI space, I find there are some parts out of the brain. Is it defined in a Talairach space?
Looking forward to your reply,thank you!
Best regards